chore: Release v7.9.6

* feat: add semver targeting support to local flag evaluation

Implement 9 semver comparison operators (semver_eq, semver_neq, semver_gt, semver_gte, semver_lt, semver_lte, semver_tilde, semver_caret, semver_wildcard) for feature flag local evaluation. Uses regex-based parsing that matches the server-side sortableSemver behavior to handle v-prefix, whitespace, pre-release suffixes, and non-standard version formats.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

* fix: guard against ReDoS in semver regex parsing

Add input length limit before regex search to prevent polynomial
backtracking on adversarial input (CodeQL py/polynomial-redos).

* fix: replace regex with string parsing to resolve ReDoS warning

Replace SEMVER_EXTRACT_RE regex with simple string splitting to
eliminate nested quantifiers that CodeQL flagged as polynomial-redos.

* refactor: inline semver operator tuple to match existing patterns

* refactor: add PROPERTY_OPERATORS constant for match_property

Extract all operator strings into a single source-of-truth tuple and
validate against it early in match_property, replacing the fallthrough
at the end of the function.

* refactor: split PROPERTY_OPERATORS into composable sub-groups

Break the flat tuple into category-specific tuples (EQUALITY_OPERATORS,
STRING_OPERATORS, etc.) that compose into PROPERTY_OPERATORS via
concatenation. The semver dispatch code now references
SEMVER_OPERATORS and SEMVER_COMPARISON_OPERATORS instead of
repeating the full operator lists inline.

* fix: add unreachable fallthrough to satisfy mypy return check

* add release

---------

Co-authored-by: Claude Haiku 4.5 <noreply@anthropic.com>

.env.example

@@ -0,0 +1,11 @@
+# PostHog API Configuration
+# Copy this file to .env and update with your actual values
+
+# Your project API key (found on the /setup page in PostHog)
+POSTHOG_PROJECT_API_KEY=phc_your_project_api_key_here
+
+# Your personal API key (for local evaluation and other advanced features)
+POSTHOG_PERSONAL_API_KEY=phx_your_personal_api_key_here
+
+# PostHog host URL (remove this line if using posthog.com)
+POSTHOG_HOST=http://localhost:8000

.github/dependabot.yml

@@ -0,0 +1,36 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "daily"
+      time: "10:00"
+      timezone: "UTC"
+    groups:
+      ai-providers:
+        patterns:
+          - "openai"
+          - "anthropic"
+          - "google-genai"
+          - "langchain-core"
+          - "langchain-community"
+          - "langchain-openai"
+          - "langchain-anthropic"
+          - "langgraph"
+    allow:
+      - dependency-name: "openai"
+      - dependency-name: "anthropic"
+      - dependency-name: "google-genai"
+      - dependency-name: "langchain-core"
+      - dependency-name: "langchain-community"
+      - dependency-name: "langchain-openai"
+      - dependency-name: "langchain-anthropic"
+      - dependency-name: "langgraph"
+    open-pull-requests-limit: 1
+    reviewers:
+      - "PostHog/team-llm-analytics"
+    # Uncomment below to enable auto-merge for minor updates when CI passes
+    # pull-request-branch-name:
+    #   separator: "/"
+    # assignees:
+    #   - "PostHog/ai-team"

.github/workflows/ci.yml

@@ -3,6 +3,9 @@ name: CI
 on:
     - pull_request
 
+permissions:
+    contents: read
+
 jobs:
     code-quality:
         name: Code quality checks
@@ -33,6 +36,10 @@ jobs:
               run: |
                   ruff format --check .
 
+            - name: Lint with ruff
+              run: |
+                  ruff check .
+
             - name: Check types with mypy
               run: |
                   mypy --no-site-packages --config-file mypy.ini  . | mypy-baseline filter
@@ -42,7 +49,7 @@ jobs:
         runs-on: ubuntu-latest
         strategy:
             matrix:
-                python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
+                python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
 
         steps:
             - uses: actions/checkout@85e6279cec87321a52edac9c87bce653a07cf6c2
@@ -68,3 +75,57 @@ jobs:
             - name: Run posthog tests
               run: |
                   pytest --verbose --timeout=30
+
+    import-check:
+        name: Python ${{ matrix.python-version }} import check
+        runs-on: ubuntu-latest
+        strategy:
+            matrix:
+                python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
+
+        steps:
+            - uses: actions/checkout@85e6279cec87321a52edac9c87bce653a07cf6c2
+              with:
+                  fetch-depth: 1
+
+            - name: Set up Python ${{ matrix.python-version }}
+              uses: actions/setup-python@8d9ed9ac5c53483de85588cdf95a591a75ab9f55
+              with:
+                  python-version: ${{ matrix.python-version }}
+
+            - name: Install posthog
+              run: pip install .
+
+            - name: Check import produces no warnings
+              run: python -W error -c "import posthog"
+
+    django5-integration:
+        name: Django 5 integration tests
+        runs-on: ubuntu-latest
+
+        steps:
+            - uses: actions/checkout@85e6279cec87321a52edac9c87bce653a07cf6c2
+              with:
+                  fetch-depth: 1
+
+            - name: Set up Python 3.12
+              uses: actions/setup-python@8d9ed9ac5c53483de85588cdf95a591a75ab9f55
+              with:
+                  python-version: 3.12
+
+            - name: Install uv
+              uses: astral-sh/setup-uv@0c5e2b8115b80b4c7c5ddf6ffdd634974642d182 # v5.4.1
+              with:
+                  enable-cache: true
+                  pyproject-file: 'integration_tests/django5/pyproject.toml'
+
+            - name: Install Django 5 test project dependencies
+              shell: bash
+              working-directory: integration_tests/django5
+              run: |
+                  UV_PROJECT_ENVIRONMENT=$pythonLocation uv sync
+
+            - name: Run Django 5 middleware integration tests
+              working-directory: integration_tests/django5
+              run: |
+                  uv run pytest test_middleware.py test_exception_capture.py --verbose

.github/workflows/codeql.yml

@@ -0,0 +1,45 @@
+name: 'CodeQL Advanced'
+
+on:
+  push:
+    branches: ['master']
+  pull_request:
+    branches: ['master']
+  schedule:
+    - cron: '32 13 * * 1'
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    runs-on: 'ubuntu-latest'
+    permissions:
+      security-events: write
+      # required to fetch internal or private CodeQL packs
+      packages: read
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - language: actions
+            build-mode: none
+          - language: python
+            build-mode: none
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+
+      - name: Initialize CodeQL
+        uses: github/codeql-action/init@5d4e8d1aca955e8d8589aabd499c5cae939e33c7 # v4.31.9
+        with:
+          languages: ${{ matrix.language }}
+          build-mode: ${{ matrix.build-mode }}
+          # Disable TRAP caching - it creates a new cache per commit SHA which
+          # is never reused, causing wasted cache space.
+          # See: https://github.com/github/codeql-action/issues/2030
+          trap-caching: false
+
+      - name: Perform CodeQL Analysis
+        uses: github/codeql-action/analyze@5d4e8d1aca955e8d8589aabd499c5cae939e33c7 # v4.31.9
+        with:
+          category: '/language:${{matrix.language}}'

.github/workflows/generate-references.yml

@@ -0,0 +1,49 @@
+name: "Generate References"
+
+on:
+  workflow_dispatch:
+
+jobs:
+  docs-generation:
+    name: Generate references
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout the repository
+        uses: actions/checkout@85e6279cec87321a52edac9c87bce653a07cf6c2
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@8d9ed9ac5c53483de85588cdf95a591a75ab9f55
+        with:
+          python-version: 3.11.11
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@0c5e2b8115b80b4c7c5ddf6ffdd634974642d182 # v5.4.1
+        with:
+            enable-cache: true
+            pyproject-file: 'pyproject.toml'
+
+      - name: Generate references
+        run: |
+          uv run bin/docs generate-references
+
+      - name: Check for changes in references
+        id: changes
+        run: |
+          if [ -n "$(git status --porcelain references/)" ]; then
+            echo "changed=true" >> $GITHUB_OUTPUT
+            echo "New references generated in references directory:"
+            git status --porcelain references/
+          else
+            echo "changed=false" >> $GITHUB_OUTPUT
+            echo "No new references generated in references directory"
+          fi
+
+      - uses: stefanzweifel/git-auto-commit-action@778341af668090896ca464160c2def5d1d1a3eb0
+        if: steps.changes.outputs.changed == 'true'
+        with:
+          commit_message: "Update generated references"
+          file_pattern: references/

.github/workflows/release.yaml

@@ -1,51 +0,0 @@
-name: "Release"
-
-on:
-  push:
-    branches:
-      - master
-    paths:
-      - "posthog/version.py"
-  workflow_dispatch:
-
-jobs:
-  release:
-    name: Publish release
-    runs-on: ubuntu-latest
-    env:
-      TWINE_USERNAME: __token__
-      TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
-    steps:
-      - name: Checkout the repository
-        uses: actions/checkout@85e6279cec87321a52edac9c87bce653a07cf6c2
-        with:
-          fetch-depth: 0
-          token: ${{ secrets.POSTHOG_BOT_GITHUB_TOKEN }}
-
-      - name: Set up Python
-        uses: actions/setup-python@8d9ed9ac5c53483de85588cdf95a591a75ab9f55
-        with:
-          python-version: 3.11.11
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@0c5e2b8115b80b4c7c5ddf6ffdd634974642d182 # v5.4.1
-        with:
-            enable-cache: true
-            pyproject-file: 'pyproject.toml'
-            
-      - name: Detect version
-        run: echo "REPO_VERSION=$(python3 posthog/version.py)" >> $GITHUB_ENV
-
-      - name: Prepare for building release
-        run: uv sync --extra dev
-
-      - name: Push releases to PyPI
-        run: uv run make release && uv run make release_analytics
-
-      - name: Create GitHub release
-        uses: actions/create-release@0cb9c9b65d5d1901c1f53e5e66eaf4afd303e70e # v1
-        env:
-          GITHUB_TOKEN: ${{ secrets.POSTHOG_BOT_GITHUB_TOKEN }}
-        with:
-          tag_name: v${{ env.REPO_VERSION }}
-          release_name: ${{ env.REPO_VERSION }}

.github/workflows/release.yml

@@ -0,0 +1,249 @@
+name: "Release"
+
+on:
+  pull_request:
+    types: [closed]
+    branches: [master]
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+# Concurrency control: only one release process can run at a time
+# This prevents race conditions if multiple PRs with 'release' label merge simultaneously
+concurrency:
+  group: release
+  cancel-in-progress: false
+
+jobs:
+  check-release-label:
+    name: Check for release label
+    runs-on: ubuntu-latest
+    # Run when PR with 'release' label is merged to master
+    if: |
+      github.event_name == 'workflow_dispatch' ||
+       (github.event_name == 'pull_request' &&
+        github.event.pull_request.merged == true &&
+        contains(github.event.pull_request.labels.*.name, 'release'))
+    outputs:
+      should-release: ${{ steps.check.outputs.should-release }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          ref: master
+          fetch-depth: 0
+
+      - name: Check release conditions
+        id: check
+        run: |
+          changeset_count=$(find .sampo/changesets -name '*.md' 2>/dev/null | wc -l)
+          if [ "$changeset_count" -gt 0 ]; then
+            echo "should-release=true" >> "$GITHUB_OUTPUT"
+            echo "Found $changeset_count changeset(s), ready to release"
+          else
+            echo "should-release=false" >> "$GITHUB_OUTPUT"
+            echo "No changesets to release"
+          fi
+
+  notify-approval-needed:
+    name: Notify Slack - Approval Needed
+    needs: check-release-label
+    if: needs.check-release-label.outputs.should-release == 'true'
+    uses: posthog/.github/.github/workflows/notify-approval-needed.yml@main
+    with:
+      slack_channel_id: ${{ vars.SLACK_APPROVALS_CLIENT_LIBRARIES_CHANNEL_ID }}
+      slack_user_group_id: ${{ vars.GROUP_CLIENT_LIBRARIES_SLACK_GROUP_ID }}
+    secrets:
+      slack_bot_token: ${{ secrets.SLACK_CLIENT_LIBRARIES_BOT_TOKEN }}
+      posthog_project_api_key: ${{ secrets.POSTHOG_PROJECT_API_KEY }}
+
+  release:
+    name: Release and publish
+    needs: [check-release-label, notify-approval-needed]
+    runs-on: ubuntu-latest
+    # Use `always()` to ensure the job runs even if notify-approval-needed is skipped,
+    # but still depend on it to access `needs.notify-approval-needed.outputs.slack_ts`
+    if: always() && needs.check-release-label.outputs.should-release == 'true'
+    environment: "Release" # This will require an approval from a maintainer, they are notified in Slack above
+    permissions:
+      contents: write
+      actions: write
+      id-token: write
+    steps:
+      - name: Notify Slack - Approved
+        if: needs.notify-approval-needed.outputs.slack_ts != ''
+        uses: posthog/.github/.github/actions/slack-thread-reply@main
+        with:
+          slack_bot_token: ${{ secrets.SLACK_CLIENT_LIBRARIES_BOT_TOKEN }}
+          slack_channel_id: ${{ vars.SLACK_APPROVALS_CLIENT_LIBRARIES_CHANNEL_ID }}
+          thread_ts: ${{ needs.notify-approval-needed.outputs.slack_ts }}
+          message: "✅ Release approved! Version bump in progress..."
+          emoji_reaction: "white_check_mark"
+
+      - name: Get GitHub App token
+        id: releaser
+        uses: actions/create-github-app-token@v2
+        with:
+          app-id: ${{ secrets.GH_APP_POSTHOG_PYTHON_RELEASER_APP_ID }}
+          private-key: ${{ secrets.GH_APP_POSTHOG_PYTHON_RELEASER_PRIVATE_KEY }}
+
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          ref: master
+          fetch-depth: 0
+          token: ${{ steps.releaser.outputs.token }}
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: 3.11.11
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+          pyproject-file: "pyproject.toml"
+
+      - name: Install Rust
+        uses: dtolnay/rust-toolchain@0b1efabc08b657293548b77fb76cc02d26091c7e
+        with:
+          toolchain: 1.91.1
+          components: cargo
+
+      - name: Cache Sampo CLI
+        id: cache-sampo
+        uses: actions/cache@v3
+        with:
+          path: ~/.cargo/bin/sampo
+          key: sampo-${{ runner.os }}-${{ runner.arch }}
+
+      - name: Install Sampo CLI
+        if: steps.cache-sampo.outputs.cache-hit != 'true'
+        run: cargo install sampo
+
+      - name: Install dependencies
+        run: uv sync --extra dev
+
+      - name: Configure Git
+        run: |
+          git config user.name "github-actions[bot]"
+          git config user.email "github-actions[bot]@users.noreply.github.com"
+
+      - name: Prepare release with Sampo
+        id: sampo-release
+        env:
+          GITHUB_TOKEN: ${{ steps.releaser.outputs.token }}
+        run: |
+          sampo release
+          new_version=$(python3 -c "import tomllib; print(tomllib.load(open('pyproject.toml', 'rb'))['project']['version'])")
+          echo "new_version=$new_version" >> "$GITHUB_OUTPUT"
+
+      - name: Sync version to posthog/version.py
+        run: |
+          echo 'VERSION = "${{ steps.sampo-release.outputs.new_version }}"' > posthog/version.py
+
+      - name: Commit release changes
+        id: commit-release
+        env:
+          GITHUB_TOKEN: ${{ steps.releaser.outputs.token }}
+        run: |
+          git add -A
+          if git diff --staged --quiet; then
+            echo "No changes to commit"
+            echo "committed=false" >> "$GITHUB_OUTPUT"
+          else
+            git commit -m "chore: Release v${{ steps.sampo-release.outputs.new_version }}"
+            git push origin master
+            echo "committed=true" >> "$GITHUB_OUTPUT"
+          fi
+
+      # Publishing is done manually (not via `sampo publish`) because we need to
+      # publish both `posthog` and `posthoganalytics` packages to PyPI.
+      # Sampo only knows about the `posthog` package, so we handle both here.
+      # Both packages use PyPI OIDC trusted publishing (no API tokens needed).
+      - name: Build posthog
+        if: steps.commit-release.outputs.committed == 'true'
+        run: uv run make build_release
+
+      - name: Publish posthog to PyPI
+        if: steps.commit-release.outputs.committed == 'true'
+        uses: pypa/gh-action-pypi-publish@release/v1
+
+      # The `posthoganalytics` package is a mirror of `posthog` published under
+      # a different name for backwards compatibility. The make target handles
+      # copying, renaming imports, and building the dist automatically.
+      - name: Build posthoganalytics
+        if: steps.commit-release.outputs.committed == 'true'
+        run: uv run make build_release_analytics
+
+      - name: Publish posthoganalytics to PyPI
+        if: steps.commit-release.outputs.committed == 'true'
+        uses: pypa/gh-action-pypi-publish@release/v1
+
+      # We skip `sampo publish` (which normally creates the tag) because we
+      # need to publish both posthog and posthoganalytics manually, so we
+      # create the tag ourselves.
+      - name: Tag release
+        if: steps.commit-release.outputs.committed == 'true'
+        run: git tag "v${{ steps.sampo-release.outputs.new_version }}"
+
+      - name: Push tags
+        if: steps.commit-release.outputs.committed == 'true'
+        run: git push origin --tags
+
+      - name: Create GitHub Release
+        if: steps.commit-release.outputs.committed == 'true'
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: gh release create "v${{ steps.sampo-release.outputs.new_version }}" --generate-notes
+
+      - name: Dispatch generate-references
+        if: steps.commit-release.outputs.committed == 'true'
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: gh workflow run generate-references.yml --ref master
+
+      # Notify in case of a failure
+      - name: Send failure event to PostHog
+        if: ${{ failure() }}
+        uses: PostHog/posthog-github-action@v0.1
+        with:
+          posthog-token: "${{ secrets.POSTHOG_PROJECT_API_KEY }}"
+          event: "posthog-python-github-release-workflow-failure"
+          properties: >-
+            {
+              "commitSha": "${{ github.sha }}",
+              "jobStatus": "${{ job.status }}",
+              "ref": "${{ github.ref }}",
+              "version": "v${{ steps.sampo-release.outputs.new_version }}"
+            }
+
+      - name: Notify Slack - Failed
+        if: ${{ failure() && needs.notify-approval-needed.outputs.slack_ts != '' }}
+        uses: posthog/.github/.github/actions/slack-thread-reply@main
+        with:
+          slack_bot_token: ${{ secrets.SLACK_CLIENT_LIBRARIES_BOT_TOKEN }}
+          slack_channel_id: ${{ vars.SLACK_APPROVALS_CLIENT_LIBRARIES_CHANNEL_ID }}
+          thread_ts: ${{ needs.notify-approval-needed.outputs.slack_ts }}
+          message: "❌ Failed to release `posthog-python@v${{ steps.sampo-release.outputs.new_version }}`! <https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}|View logs>"
+          emoji_reaction: "x"
+
+  notify-released:
+    name: Notify Slack - Released
+    needs: [check-release-label, notify-approval-needed, release]
+    runs-on: ubuntu-latest
+    if: always() && needs.release.result == 'success' && needs.notify-approval-needed.outputs.slack_ts != ''
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Notify Slack - Released
+        uses: posthog/.github/.github/actions/slack-thread-reply@main
+        with:
+          slack_bot_token: ${{ secrets.SLACK_CLIENT_LIBRARIES_BOT_TOKEN }}
+          slack_channel_id: ${{ vars.SLACK_APPROVALS_CLIENT_LIBRARIES_CHANNEL_ID }}
+          thread_ts: ${{ needs.notify-approval-needed.outputs.slack_ts }}
+          message: "🚀 posthog-python released successfully!"
+          emoji_reaction: "rocket"

.github/workflows/sdk-compliance.yml

@@ -0,0 +1,21 @@
+name: SDK Compliance Tests
+
+permissions:
+  contents: read
+  packages: read
+  pull-requests: write
+
+on:
+  pull_request:
+  push:
+    branches:
+      - master
+
+jobs:
+  compliance:
+    name: PostHog SDK compliance tests
+    uses: PostHog/posthog-sdk-test-harness/.github/workflows/test-sdk-action.yml@main
+    with:
+      adapter-dockerfile: "sdk_compliance_adapter/Dockerfile"
+      adapter-context: "."
+      test-harness-version: "latest"

.gitignore

@@ -18,3 +18,5 @@ posthog-analytics
 pyrightconfig.json
 .env
 .DS_Store
+posthog-python-references.json
+.claude/settings.local.json

.sampo/config.toml

@@ -0,0 +1,19 @@
+# Sampo configuration
+version = 1
+
+[git]
+default_branch = "master"
+short_tags = "posthog"    # Tag with v1.2.3 rather than posthog-v1.2.3
+
+[github]
+repository = "posthog/posthog-python"
+
+[changelog]
+# Options for release notes generation.
+# show_commit_hash = true (default)
+# show_acknowledgments = true (default)
+
+[packages]
+# Options for package discovery and filtering.
+# ignore_unpublished = false (default)
+# ignore = ["internal-*", "examples/*"]

CHANGELOG.md

@@ -1,8 +1,343 @@
-# 5.3.0 - 2025-06-19
+# posthog
+
+## 7.9.6 — 2026-03-02
+
+### Patch changes
+
+- [8d83315](https://github.com/posthog/posthog-python/commit/8d83315b67c21eb9e7d6c17bae27ada98ca2643d) add PROPERTY_OPERATORS constant for match_property — Thanks @dmarticus!
+
+## 7.9.5 — 2026-03-02
+
+### Patch changes
+
+- [830244b](https://github.com/posthog/posthog-python/commit/830244bd409b1992ae2e49610f8f87d2cdfc8096) add semver targeting support to local evaluation — Thanks @dmarticus!
+
+## 7.9.4 — 2026-02-25
+
+### Patch changes
+
+- [a68a6a6](https://github.com/posthog/posthog-python/commit/a68a6a6d045072c88eeee7acac441536919b5954) feat(llma): add `$ai_tokens_source` property ("sdk" or "passthrough") to all `$ai_generation` events to detect when token values are externally overridden via `posthog_properties` — Thanks @carlos-marchal-ph!
+
+## 7.9.3 — 2026-02-18
+
+### Patch changes
+
+- [9f9553a](https://github.com/posthog/posthog-python/commit/9f9553a420d22e5e6435b775993f61a059280c2a) Fix posthoganalytics release, previously broken — Thanks @rafaeelaudibert!
+
+## 7.9.2 — 2026-02-18
+
+### Patch changes
+
+- [f1dc4d7](https://github.com/posthog/posthog-python/commit/f1dc4d73914712983a7f715ee4fe1b70e66e770a) Add sampo to the project — Thanks @rafaeelaudibert!
+
+## 7.9.1 - 2026-02-17
+
+fix(llma): make prompt fetches deterministic by requiring project_api_key and sending it as token query param
+
+## 7.9.0 - 2026-02-17
+
+feat: Support device_id as bucketing identifier for local evaluation
+
+## 7.8.6 - 2026-02-09
+
+fix: limit collections scanning in code variables
+
+## 7.8.5 - 2026-02-09
+
+fix: further optimize code variables pattern matching
+
+## 7.8.4 - 2026-02-09
+
+fix: do not pattern match long values in code variables
+
+## 7.8.3 - 2026-02-06
+
+fix: openAI input image sanitization
+
+## 7.8.2 - 2026-02-04
+
+fix(llma): fix prompts default url
+
+## 7.8.1 - 2026-02-03
+
+fix(llma): small fixes for prompt management
+
+## 7.8.0 - 2026-01-28
+
+feat(llma): add prompt management
+
+Adds the Prompt Management feature. At the time of release, this feature is in a closed alpha.
+
+## 7.7.0 - 2026-01-15
+
+feat(ai): Add OpenAI Agents SDK integration
+
+Automatic tracing for agent workflows, handoffs, tool calls, guardrails, and custom spans. Includes `$ai_total_tokens`, `$ai_error_type` categorization, and `$ai_framework` property.
+
+## 7.6.0 - 2026-01-12
+
+feat: add device_id to flags request payload
+
+Add device_id parameter to all feature flag methods, allowing the server to track device identifiers for flag evaluation. The device_id can be passed explicitly or set via context using `set_context_device_id()`.
+
+## 7.5.1 - 2026-01-07
+
+fix: avoid return from finally block to fix Python 3.14 SyntaxWarning (#361) - thanks @jodal
+
+## 7.5.0 - 2026-01-06
+
+feat: Capture Langchain, OpenAI and Anthropic errors as exceptions (if exception autocapture is enabled)
+feat: Add reference to exception in LLMA trace and span events
+
+## 7.4.3 - 2026-01-02
+
+Fixes cache creation cost for Langchain with Anthropic
+
+## 7.4.2 - 2025-12-22
+
+feat: add `in_app_modules` option to control code variables capturing
+
+## 7.4.1 - 2025-12-19
+
+fix: extract model from response for OpenAI stored prompts
+
+When using OpenAI stored prompts, the model is defined in the OpenAI dashboard rather than passed in the API request. This fix adds a fallback to extract the model from the response object when not provided in kwargs, ensuring generations show up with the correct model and enabling cost calculations.
+
+## 7.4.0 - 2025-12-16
+
+feat: Add automatic retries for feature flag requests
+
+Feature flag API requests now automatically retry on transient failures:
+
+- Network errors (connection refused, DNS failures, timeouts)
+- Server errors (500, 502, 503, 504)
+- Up to 2 retries with exponential backoff (0.5s, 1s delays)
+
+Rate limit (429) and quota (402) errors are not retried.
+
+## 7.3.1 - 2025-12-06
+
+fix: remove unused $exception_message and $exception_type
+
+## 7.3.0 - 2025-12-05
+
+feat: improve code variables capture masking
+
+## 7.2.0 - 2025-12-01
+
+feat: add $feature_flag_evaluated_at properties to $feature_flag_called events
+
+## 7.1.0 - 2025-11-26
+
+Add support for the async version of Gemini.
+
+## 7.0.2 - 2025-11-18
+
+Add support for Python 3.14.
+Projects upgrading to Python 3.14 should ensure any Pydantic models passed into the SDK use Pydantic v2, as Pydantic v1 is not compatible with Python 3.14.
+
+## 7.0.1 - 2025-11-15
+
+Try to use repr() when formatting code variables
+
+## 7.0.0 - 2025-11-11
+
+NB Python 3.9 is no longer supported
+
+- chore(llma): update LLM provider SDKs to latest major versions
+  - openai: 1.102.0 → 2.7.1
+  - anthropic: 0.64.0 → 0.72.0
+  - google-genai: 1.32.0 → 1.49.0
+  - langchain-core: 0.3.75 → 1.0.3
+  - langchain-openai: 0.3.32 → 1.0.2
+  - langchain-anthropic: 0.3.19 → 1.0.1
+  - langchain-community: 0.3.29 → 0.4.1
+  - langgraph: 0.6.6 → 1.0.2
+
+## 6.9.3 - 2025-11-10
+
+- feat(ph-ai): PostHog properties dict in GenerationMetadata
+
+## 6.9.2 - 2025-11-10
+
+- fix(llma): fix cache token double subtraction in Langchain for non-Anthropic providers causing negative costs
+
+## 6.9.1 - 2025-11-07
+
+- fix(error-tracking): pass code variables config from init to client
+
+## 6.9.0 - 2025-11-06
+
+- feat(error-tracking): add local variables capture
+
+## 6.8.0 - 2025-11-03
+
+- feat(llma): send web search calls to be used for LLM cost calculations
+
+## 6.7.14 - 2025-11-03
+
+- fix(django): Handle request.user access in async middleware context to prevent SynchronousOnlyOperation errors in Django 5+ (fixes #355)
+- test(django): Add Django 5 integration test suite with real ASGI application testing async middleware behavior
+
+## 6.7.13 - 2025-11-02
+
+- fix(llma): cache cost calculation in the LangChain callback
+
+## 6.7.12 - 2025-11-02
+
+- fix(django): Restore process_exception method to capture view and downstream middleware exceptions (fixes #329)
+- fix(ai/langchain): Add LangChain 1.0+ compatibility for CallbackHandler imports (fixes #362)
+
+## 6.7.11 - 2025-10-28
+
+- feat(ai): Add `$ai_framework` property for framework integrations (e.g. LangChain)
+
+## 6.7.10 - 2025-10-24
+
+- fix(django): Make middleware truly hybrid - compatible with both sync (WSGI) and async (ASGI) Django stacks without breaking sync-only deployments
+
+## 6.7.9 - 2025-10-22
+
+- fix(flags): multi-condition flags with static cohorts returning wrong variants
+
+## 6.7.8 - 2025-10-16
+
+- fix(llma): missing async for OpenAI's streaming implementation
+
+## 6.7.7 - 2025-10-14
+
+- fix: remove deprecated attribute $exception_personURL from exception events
+
+## 6.7.6 - 2025-09-16
+
+- fix: don't sort condition sets with variant overrides to the top
+- fix: Prevent core Client methods from raising exceptions
+
+## 6.7.5 - 2025-09-16
+
+- feat: Django middleware now supports async request handling.
+
+## 6.7.4 - 2025-09-05
+
+- fix: Missing system prompts for some providers
+
+## 6.7.3 - 2025-09-04
+
+- fix: missing usage tokens in Gemini
+
+## 6.7.2 - 2025-09-03
+
+- fix: tool call results in streaming providers
+
+## 6.7.1 - 2025-09-01
+
+- fix: Add base64 inline image sanitization
+
+## 6.7.0 - 2025-08-26
+
+- feat: Add support for feature flag dependencies
+
+## 6.6.1 - 2025-08-21
+
+- fix: Prevent `NoneType` error when `group_properties` is `None`
+
+## 6.6.0 - 2025-08-15
+
+- feat: Add `flag_keys_to_evaluate` parameter to optimize feature flag evaluation performance by only evaluating specified flags
+- feat: Add `flag_keys_filter` option to `send_feature_flags` for selective flag evaluation in capture events
+
+## 6.5.0 - 2025-08-08
+
+- feat: Add `$context_tags` to an event to know which properties were included as tags
+
+## 6.4.1 - 2025-08-06
+
+- fix: Always pass project API key in `remote_config` requests for deterministic project routing
+
+## 6.4.0 - 2025-08-05
+
+- feat: support Vertex AI for Gemini
+
+## 6.3.4 - 2025-08-04
+
+- fix: set `$ai_tools` for all providers and `$ai_output_choices` for all non-streaming provider flows properly
+
+## 6.3.3 - 2025-08-01
+
+- fix: `get_feature_flag_result` now correctly returns FeatureFlagResult when payload is empty string instead of None
+
+## 6.3.2 - 2025-07-31
+
+- fix: Anthropic's tool calls are now handled properly
+
+## 6.3.0 - 2025-07-22
+
+- feat: Enhanced `send_feature_flags` parameter to accept `SendFeatureFlagsOptions` object for declarative control over local/remote evaluation and custom properties
+
+## 6.2.1 - 2025-07-21
+
+- feat: make `posthog_client` an optional argument in PostHog AI providers wrappers (`posthog.ai.*`), intuitively using the default client as the default
+
+## 6.1.1 - 2025-07-16
+
+- fix: correctly capture exceptions processed by Django from views or middleware
+
+## 6.1.0 - 2025-07-10
+
+- feat: decouple feature flag local evaluation from personal API keys; support decrypting remote config payloads without relying on the feature flags poller
+
+## 6.0.4 - 2025-07-09
+
+- fix: add POSTHOG_MW_CLIENT setting to django middleware, to support custom clients for exception capture.
+
+## 6.0.3 - 2025-07-07
+
+- feat: add a feature flag evaluation cache (local storage or redis) to support returning flag evaluations when the service is down
+
+## 6.0.2 - 2025-07-02
+
+- fix: send_feature_flags changed to default to false in `Client::capture_exception`
+
+## 6.0.1
+
+- fix: response `$process_person_profile` property when passed to capture
+
+## 6.0.0
+
+This release contains a number of major breaking changes:
+
+- feat: make distinct_id an optional parameter in posthog.capture and related functions
+- feat: make capture and related functions return `Optional[str]`, which is the UUID of the sent event, if it was sent
+- fix: remove `identify` (prefer `posthog.set()`), and `page` and `screen` (prefer `posthog.capture()`)
+- fix: delete exception-capture specific integrations module. Prefer the general-purpose django middleware as a replacement for the django `Integration`.
+
+To migrate to this version, you'll mostly just need to switch to using named keyword arguments, rather than positional ones. For example:
+
+```python
+# Old calling convention
+posthog.capture("user123", "button_clicked", {"button_id": "123"})
+# New calling convention
+posthog.capture(distinct_id="user123", event="button_clicked", properties={"button_id": "123"})
+
+# Better pattern
+with posthog.new_context():
+    posthog.identify_context("user123")
+
+    # The event name is the first argument, and can be passed positionally, or as a keyword argument in a later position
+    posthog.capture("button_pressed")
+```
+
+Generally, arguments are now appropriately typed, and docstrings have been updated. If something is unclear, please open an issue, or submit a PR!
+
+## 5.4.0 - 2025-06-20
+
+- feat: add support to session_id context on page method
+
+## 5.3.0 - 2025-06-19
 
 - fix: safely handle exception values
 
-# 5.2.0 - 2025-06-19
+## 5.2.0 - 2025-06-19
 
 - feat: construct artificial stack traces if no traceback is available on a captured exception
 

Makefile

@@ -5,12 +5,26 @@ test:
 	coverage run -m pytest
 	coverage report
 
-release:
+build_release:
 	rm -rf dist/*
 	python setup.py sdist bdist_wheel
-	twine upload dist/*
 
-release_analytics:
+# Builds the `posthoganalytics` PyPI package, which is a mirror of `posthog`
+# published under a different name for internal use by posthog/posthog.
+#
+# The process works in three phases:
+#   1. posthog -> posthoganalytics: Copy the source, rewrite all imports,
+#      remove the original posthog/ dir, and build the dist.
+#   2. posthoganalytics -> posthog: Reverse the import rewrites, copy
+#      everything back into posthog/, and clean up.
+#   3. Restore pyproject.toml from backup (setup_analytics.py modifies it).
+#
+# This ensures the working tree is left in the same state it started in.
+#
+# NOTE: This target clears dist/ before building. In the release workflow,
+# `build_release` (posthog) must be published BEFORE running this target,
+# otherwise the posthog dist artifacts will be lost.
+build_release_analytics:
 	rm -rf dist
 	rm -rf build
 	rm -rf posthoganalytics
@@ -21,7 +35,6 @@ release_analytics:
 	find ./posthoganalytics -name "*.bak" -delete
 	rm -rf posthog
 	python setup_analytics.py sdist bdist_wheel
-	twine upload dist/*
 	mkdir posthog
 	find ./posthoganalytics -type f -name "*.py" -exec sed -i.bak -e 's/from posthoganalytics /from posthog /g' {} \;
 	find ./posthoganalytics -type f -name "*.py" -exec sed -i.bak -e 's/from posthoganalytics\./from posthog\./g' {} \;
@@ -54,4 +67,4 @@ prep_local:
 	@echo "Local copy created at ../posthog-python-local"
 	@echo "Install with: pip install -e ../posthog-python-local"
 
-.PHONY: test lint release e2e_test prep_local
+.PHONY: test lint build_release build_release_analytics e2e_test prep_local

README.md

@@ -12,6 +12,14 @@
 
 Please see the [Python integration docs](https://posthog.com/docs/integrations/python-integration) for details.
 
+## Python Version Support
+
+| SDK Version   | Python Versions Supported    | Notes                      |
+| ------------- | ---------------------------- | -------------------------- |
+| 7.3.1+        | 3.10, 3.11, 3.12, 3.13, 3.14 | Added Python 3.14 support  |
+| 7.0.0 - 7.0.1 | 3.10, 3.11, 3.12, 3.13       | Dropped Python 3.9 support |
+| 4.0.1 - 6.x   | 3.9, 3.10, 3.11, 3.12, 3.13  | Python 3.9+ required       |
+
 ## Development
 
 ### Testing Locally
@@ -19,20 +27,20 @@ Please see the [Python integration docs](https://posthog.com/docs/integrations/p
 We recommend using [uv](https://docs.astral.sh/uv/). It's super fast.
 
 1. Run `uv venv env` (creates virtual environment called "env")
-    * or `python3 -m venv env`
+   - or `python3 -m venv env`
 2. Run `source env/bin/activate` (activates the virtual environment)
 3. Run `uv sync --extra dev --extra test` (installs the package in develop mode, along with test dependencies)
-    * or `pip install -e ".[dev,test]"`
+   - or `pip install -e ".[dev,test]"`
 4. you have to run `pre-commit install` to have auto linting pre commit
 5. Run `make test`
-  1. To run a specific test do `pytest -k test_no_api_key`
+6. To run a specific test do `pytest -k test_no_api_key`
 
 ## PostHog recommends `uv` so...
 
 ```bash
-uv python install 3.9.19
-uv python pin 3.9.19
-uv venv env
+uv python install 3.12
+uv python pin 3.12
+uv venv
 source env/bin/activate
 uv sync --extra dev --extra test
 pre-commit install
@@ -43,14 +51,10 @@ make test
 
 Assuming you have a [local version of PostHog](https://posthog.com/docs/developing-locally) running, you can run `python3 example.py` to see the library in action.
 
-### Releasing Versions
-
-Updates are released using GitHub Actions: after bumping `version.py` in `master` and adding to `CHANGELOG.md`, go to [our release workflow's page](https://github.com/PostHog/posthog-python/actions/workflows/release.yaml) and dispatch it manually, using workflow from `master`.
-
-
 ### Testing changes locally with the PostHog app
 
 You can run `make prep_local`, and it'll create a new folder alongside the SDK repo one called `posthog-python-local`, which you can then import into the posthog project by changing pyproject.toml to look like this:
+
 ```toml
 dependencies = [
     ...
@@ -61,4 +65,16 @@ dependencies = [
 [tools.uv.sources]
 posthoganalytics = { path = "../posthog-python-local" }
 ```
+
 This'll let you build and test SDK changes fully locally, incorporating them into your local posthog app stack. It mainly takes care of the `posthog -> posthoganalytics` module renaming. You'll need to re-run `make prep_local` each time you make a change, and re-run `uv sync --active` in the posthog app project.
+
+## Releasing
+
+This repository uses [Sampo](https://github.com/bruits/sampo) for versioning, changelogs, and publishing to crates.io.
+
+1. When making changes, include a changeset: `sampo add`
+2. Create a PR with your changes and the changeset file
+3. Add the `release` label and merge to `main`
+4. Approve the release in Slack when prompted — this triggers version bump, crates.io publish, git tag, and GitHub Release
+
+You can also trigger a release manually via the workflow's `workflow_dispatch` trigger (still requires pending changesets).

README_ANALYTICS.md

@@ -0,0 +1,11 @@
+# posthoganalytics
+
+> **Do not use this package.** Use [`posthog`](https://pypi.org/project/posthog/) instead.
+
+```bash
+pip install posthog
+```
+
+This package exists solely for internal use by [posthog/posthog](https://github.com/posthog/posthog) to avoid import conflicts with the local `posthog` package in that repository. It is an automatically generated mirror of `posthog` — same code, same versions, just published under a different name.
+
+If you are not working on the PostHog main repository, you should never need this package. All documentation, issues, and development happen in [`posthog-python`](https://github.com/posthog/posthog-python).

bin/docs

@@ -0,0 +1,8 @@
+#!/usr/bin/env bash
+#/ Usage: bin/docs
+#/ Description: Generate documentation for the PostHog Python SDK
+source bin/helpers/_utils.sh
+set_source_and_root_dir
+ensure_virtual_env
+
+exec python3 "$(dirname "$0")/docs_scripts/generate_json_schemas.py" "$@" 

bin/docs_scripts/doc_constant.py

@@ -0,0 +1,43 @@
+"""
+Constants for PostHog Python SDK documentation generation.
+"""
+
+from typing import Dict, Union
+from posthog.version import VERSION
+
+# Documentation generation metadata
+DOCUMENTATION_METADATA = {
+    "hogRef": "0.3",
+    "slugPrefix": "posthog-python",
+    "specUrl": "https://github.com/PostHog/posthog-python",
+}
+
+# Docstring parsing patterns for new format
+DOCSTRING_PATTERNS = {
+    "examples_section": r"Examples:\s*\n(.*?)(?=\n\s*\n\s*Category:|\Z)",
+    "args_section": r"Args:\s*\n(.*?)(?=\n\s*\n\s*Examples:|\n\s*\n\s*Details:|\n\s*\n\s*Category:|\Z)",
+    "details_section": r"Details:\s*\n(.*?)(?=\n\s*\n\s*Examples:|\n\s*\n\s*Category:|\Z)",
+    "category_section": r"Category:\s*\n\s*(.+?)\s*(?:\n|$)",
+    "code_block": r"```(?:python)?\n(.*?)```",
+    "param_description": r"^\s*{param_name}:\s*(.+?)(?=\n\s*\w+:|\Z)",
+    "args_marker": r"\n\s*Args:\s*\n",
+    "examples_marker": r"\n\s*Examples:\s*\n",
+    "details_marker": r"\n\s*Details:\s*\n",
+    "category_marker": r"\n\s*Category:\s*\n",
+}
+
+# Output file configuration
+OUTPUT_CONFIG: Dict[str, Union[str, int]] = {
+    "output_dir": "./references",
+    "filename": f"posthog-python-references-{VERSION}.json",
+    "filename_latest": "posthog-python-references-latest.json",
+    "indent": 2,
+}
+
+# Documentation structure defaults
+DOC_DEFAULTS = {
+    "showDocs": True,
+    "releaseTag": "public",
+    "return_type_void": "None",
+    "max_optional_params": 3,
+}

bin/docs_scripts/generate_json_schemas.py

@@ -0,0 +1,498 @@
+#!/usr/bin/env python3
+"""
+Generate comprehensive SDK documentation JSON from PostHog Python SDK.
+This script inspects the code and docstrings to create documentation in the specified format.
+"""
+
+import json
+import inspect
+import re
+from dataclasses import is_dataclass, fields
+from typing import get_origin, get_args, Union
+from textwrap import dedent
+from doc_constant import (
+    DOCUMENTATION_METADATA,
+    DOCSTRING_PATTERNS,
+    OUTPUT_CONFIG,
+    DOC_DEFAULTS,
+)
+import os
+
+
+def extract_examples_from_docstring(docstring: str) -> list:
+    """Extract code examples from docstring."""
+    if not docstring:
+        return []
+
+    examples = []
+
+    # Look for Examples section in the new format
+    examples_section_match = re.search(
+        DOCSTRING_PATTERNS["examples_section"], docstring, re.DOTALL
+    )
+    if examples_section_match:
+        examples_content = examples_section_match.group(1).strip()
+        # Extract code blocks from the Examples section
+        code_blocks = re.findall(
+            DOCSTRING_PATTERNS["code_block"], examples_content, re.DOTALL
+        )
+        for i, code_block in enumerate(code_blocks):
+            # Remove common leading whitespace while preserving relative indentation
+            code = dedent(code_block).strip()
+
+            # Extract name from first comment line if present
+            lines = code.split("\n")
+            name = f"Example {i + 1}"  # Default fallback
+
+            if lines and lines[0].strip().startswith("#"):
+                # Extract name from first comment, keep the comment in the code
+                comment_text = lines[0].strip()[1:].strip()
+                if comment_text:
+                    name = comment_text
+
+            examples.append({"id": f"example_{i + 1}", "name": name, "code": code})
+
+    return examples
+
+
+def extract_details_from_docstring(docstring: str) -> str:
+    """Extract details section from docstring."""
+    if not docstring:
+        return ""
+
+    # Look for Details section
+    details_match = re.search(
+        DOCSTRING_PATTERNS["details_section"], docstring, re.DOTALL
+    )
+    if details_match:
+        details_content = details_match.group(1).strip()
+        # Clean up formatting
+        return details_content.replace("\n", " ")
+
+    return ""
+
+
+def parse_docstring_tags(docstring: str) -> dict:
+    """Parse tags from docstring Category section."""
+    if not docstring:
+        return {}
+
+    tags = {}
+
+    # Extract Category section
+    category_match = re.search(DOCSTRING_PATTERNS["category_section"], docstring)
+    if category_match:
+        category_value = category_match.group(1).strip()
+        tags["category"] = category_value
+
+    return tags
+
+
+def extract_description_from_docstring(docstring: str) -> str:
+    """Extract main description from docstring."""
+    if not docstring:
+        return ""
+
+    # Clean up the docstring
+    cleaned = dedent(docstring).strip()
+
+    # Find the end of the description by looking for first section marker
+    # Check for Args:, Examples:, Details:, or Category: sections
+    section_patterns = [
+        DOCSTRING_PATTERNS["args_marker"],
+        DOCSTRING_PATTERNS["examples_marker"],
+        DOCSTRING_PATTERNS["details_marker"],
+        DOCSTRING_PATTERNS["category_marker"],
+    ]
+
+    end_pos = len(cleaned)
+    for pattern in section_patterns:
+        match = re.search(pattern, cleaned)
+        if match:
+            end_pos = min(end_pos, match.start())
+
+    # Extract description up to the first section marker
+    description = cleaned[:end_pos].strip()
+
+    # Remove one level of \n since it will be rendered as markdown
+    # and \n will be padded in later steps
+    description = description.replace("\n", " ")
+
+    return description
+
+
+def get_type_name(type_annotation) -> str:
+    """Convert type annotation to string name."""
+    if type_annotation is None or type_annotation is type(None):
+        return "any"
+
+    # Handle typing constructs
+    origin = get_origin(type_annotation)
+    if origin is not None:
+        # Handle Union types (including Optional)
+        if origin is Union:
+            args = get_args(type_annotation)
+            if len(args) == 2 and type(None) in args:
+                # This is Optional[Type] - get the non-None type
+                non_none_type = next(arg for arg in args if arg is not type(None))
+                return f"Optional[{get_type_name(non_none_type)}]"
+            else:
+                # Regular Union - list all types
+                type_names = [get_type_name(arg) for arg in args]
+                return f"Union[{', '.join(type_names)}]"
+
+        # Handle other generic types (List, Dict, etc.)
+        origin_name = getattr(origin, "__name__", str(origin))
+        args = get_args(type_annotation)
+        if args:
+            arg_names = [get_type_name(arg) for arg in args]
+            return f"{origin_name}[{', '.join(arg_names)}]"
+        else:
+            return origin_name
+
+    # Handle regular types
+    elif hasattr(type_annotation, "__name__"):
+        return type_annotation.__name__
+    else:
+        return str(type_annotation)
+
+
+def analyze_parameter(param: inspect.Parameter, docstring: str = "") -> dict:
+    """Analyze a function parameter and return its documentation."""
+    # Determine if parameter is optional (has default value)
+    is_optional = param.default == inspect.Parameter.empty
+
+    # Get the type annotation
+    type_annotation = param.annotation
+    param_type = "any"
+
+    if type_annotation != inspect.Parameter.empty:
+        # Handle Union/Optional types first
+        origin = get_origin(type_annotation)
+        if origin is Union:
+            args = get_args(type_annotation)
+            if len(args) == 2 and type(None) in args:
+                # This is Optional[Type]
+                non_none_type = next(arg for arg in args if arg is not type(None))
+                param_type = get_type_name(non_none_type)
+                is_optional = True
+            else:
+                # Other Union types, use first type
+                param_type = get_type_name(args[0]) if args else "any"
+        else:
+            param_type = get_type_name(type_annotation)
+    elif param.default != inspect.Parameter.empty:
+        # No type annotation, but has default value - infer type from default
+        param_type = get_type_name(type(param.default))
+
+    # Extract parameter description from Args section
+    param_description = ""
+    if docstring:
+        # Look for Args section and extract description for this parameter
+        args_section_match = re.search(
+            DOCSTRING_PATTERNS["args_section"], docstring, re.DOTALL
+        )
+        if args_section_match:
+            args_content = args_section_match.group(1)
+            # Look for the parameter description
+            param_pattern = DOCSTRING_PATTERNS["param_description"].format(
+                param_name=re.escape(param.name)
+            )
+            param_match = re.search(
+                param_pattern, args_content, re.MULTILINE | re.DOTALL
+            )
+            if param_match:
+                param_description = param_match.group(1).strip().replace("\n", " ")
+
+    param_info = {
+        "name": param.name,
+        "description": param_description,
+        "isOptional": is_optional,
+        "type": param_type,
+    }
+
+    return param_info
+
+
+def analyze_function(func, name: str) -> dict:
+    """Analyze a function and return its documentation."""
+    try:
+        sig = inspect.signature(func)
+        docstring = inspect.getdoc(func) or ""
+
+        # Skip functions with empty docstrings
+        if not docstring.strip():
+            return {}
+
+        # Extract parameters (excluding 'self')
+        params = []
+        for param_name, param in sig.parameters.items():
+            if param_name != "self":
+                params.append(analyze_parameter(param, docstring))
+
+        # Special handling for constructor
+        display_name = name
+        if name == "__init__":
+            display_name = func.__qualname__.split(".")[0]
+
+        # Parse tags from docstring
+        tags = parse_docstring_tags(docstring)
+
+        category = tags.get("category", None)
+
+        # Extract description
+        description = extract_description_from_docstring(docstring)
+
+        # Skip if no meaningful description
+        if not description.strip():
+            return {}
+
+        # Extract details section (only if it exists)
+        details = extract_details_from_docstring(docstring)
+
+        # Get examples from docstring, do not generate fallback examples
+        examples = extract_examples_from_docstring(docstring)
+        # If no examples, do not include the examples key or set to empty list
+
+        result = {
+            "id": name,
+            "title": display_name,
+            "description": description,
+            "details": details,
+            "category": category,
+            "params": params,
+            "showDocs": DOC_DEFAULTS["showDocs"],
+            "releaseTag": DOC_DEFAULTS["releaseTag"],
+            "returnType": {
+                "id": "return_type",
+                "name": get_type_name(sig.return_annotation)
+                if sig.return_annotation != inspect.Signature.empty
+                else DOC_DEFAULTS["return_type_void"],
+            },
+        }
+        if examples:
+            result["examples"] = examples
+        return result
+    except Exception as e:
+        print(f"Error analyzing function {name}: {e}")
+        return {}
+
+
+def analyze_class(cls) -> dict:
+    """Analyze a class and return its documentation."""
+    class_doc = inspect.getdoc(cls) or f"Class: {cls.__name__}"
+
+    # Get all public methods and constructor
+    functions = []
+    for method_name in dir(cls):
+        if method_name.startswith("_") and method_name != "__init__":
+            continue
+
+        method = getattr(cls, method_name)
+        if callable(method):
+            func_info = analyze_function(method, method_name)
+            if func_info:  # Only add if not None (empty docstring check)
+                functions.append(func_info)
+
+    return {
+        "id": cls.__name__,
+        "title": cls.__name__,
+        "description": extract_description_from_docstring(class_doc),
+        "functions": functions,
+    }
+
+
+def analyze_type(cls) -> dict:
+    """Analyze a type/dataclass and return its documentation."""
+    type_info = {
+        "id": cls.__name__,
+        "name": cls.__name__,
+        "path": f"{cls.__module__}.{cls.__name__}",
+        "properties": [],
+        "example": "",
+    }
+
+    if is_dataclass(cls):
+        # Handle dataclass
+        for field in fields(cls):
+            prop = {
+                "name": field.name,
+                "type": get_type_name(field.type),
+                "description": f"Field: {field.name}",
+            }
+            type_info["properties"].append(prop)
+    elif hasattr(cls, "__annotations__"):
+        # Handle TypedDict or annotated class
+        for field_name, field_type in cls.__annotations__.items():
+            prop = {
+                "name": field_name,
+                "type": get_type_name(field_type),
+                "description": f"Field: {field_name}",
+            }
+            type_info["properties"].append(prop)
+
+    return type_info
+
+
+def generate_sdk_documentation():
+    """Generate complete SDK documentation in the requested format."""
+
+    # Import PostHog components
+    import posthog
+    from posthog.client import Client
+    import posthog.types as types_module
+    import posthog.args as args_module
+    from posthog.version import VERSION
+
+    # Main SDK info
+    sdk_info = {
+        "version": VERSION,
+        "id": "posthog-python",
+        "title": "PostHog Python SDK",
+        "description": "Integrate PostHog into any python application.",
+        "slugPrefix": DOCUMENTATION_METADATA["slugPrefix"],
+        "specUrl": DOCUMENTATION_METADATA["specUrl"],
+    }
+
+    # Collect types
+    types_list = []
+
+    # Types from posthog.types
+    for name in dir(types_module):
+        obj = getattr(types_module, name)
+        if inspect.isclass(obj) and not name.startswith("_"):
+            try:
+                type_info = analyze_type(obj)
+                types_list.append(type_info)
+            except Exception as e:
+                print(f"Error analyzing type {name}: {e}")
+
+    # Types from posthog.args
+    for name in dir(args_module):
+        obj = getattr(args_module, name)
+        if inspect.isclass(obj) and not name.startswith("_"):
+            try:
+                type_info = analyze_type(obj)
+                types_list.append(type_info)
+            except Exception as e:
+                print(f"Error analyzing type {name}: {e}")
+
+    # Clean types of empty types
+
+    # Remove types that have no properties and no examples
+    # Remove types that have no properties and no examples
+    types_list = [
+        t for t in types_list if len(t["properties"]) > 0 or t["example"] != ""
+    ]
+
+    # Collect classes
+    classes_list = []
+
+    # Main PostHog class (renamed from Client)
+    client_class = analyze_class(Client)
+    client_class["id"] = "PostHog"
+    client_class["title"] = "PostHog"
+    classes_list.append(client_class)
+
+    # Global module functions (functions callable as posthog.function_name)
+    global_functions = []
+    for func_name in dir(posthog):
+        # Skip private functions and non-callables
+        if func_name.startswith("_") or not callable(getattr(posthog, func_name)):
+            continue
+
+        func = getattr(posthog, func_name)
+        # Only include functions actually defined in the posthog module (not imported)
+        # and exclude class references
+        if (
+            func_name not in ["Client", "Posthog"]
+            and hasattr(func, "__module__")
+            and func.__module__ == "posthog"
+        ):
+            try:
+                func_info = analyze_function(func, func_name)
+                if func_info:  # Only add if not None (has proper docstring)
+                    global_functions.append(func_info)
+            except Exception:
+                continue
+
+    # Add global functions as a "class"
+    if global_functions:
+        classes_list.append(
+            {
+                "id": "PostHogModule",
+                "title": "PostHog Module Functions",
+                "description": "Global functions available in the PostHog module",
+                "functions": global_functions,
+            }
+        )
+
+    # Collect categories from functions
+    categories = ["Initialization", "Identification", "Capture"]
+    seen_categories = set(categories)
+    for class_info in classes_list:
+        if "functions" in class_info:
+            for func in class_info["functions"]:
+                if (
+                    "category" in func
+                    and func["category"] not in seen_categories
+                    and func["category"]
+                ):
+                    categories.append(func["category"])
+                    seen_categories.add(func["category"])
+
+    # Create the final structure
+    result = {
+        "id": "posthog-python",
+        "hogRef": DOCUMENTATION_METADATA["hogRef"],
+        "info": sdk_info,
+        "types": types_list,
+        "classes": classes_list,
+        "categories": categories,
+    }
+
+    return result
+
+
+if __name__ == "__main__":
+    print("Generating PostHog Python SDK documentation...")
+
+    try:
+        documentation = generate_sdk_documentation()
+
+        # Ensure output directory exists
+        output_dir = str(OUTPUT_CONFIG["output_dir"])
+        os.makedirs(output_dir, exist_ok=True)
+
+        output_file = os.path.join(
+            str(OUTPUT_CONFIG["output_dir"]), str(OUTPUT_CONFIG["filename"])
+        )
+        output_file_latest = os.path.join(
+            str(OUTPUT_CONFIG["output_dir"]), str(OUTPUT_CONFIG["filename_latest"])
+        )
+
+        # Write to current version
+        with open(output_file, "w") as f:
+            json.dump(documentation, f, indent=int(OUTPUT_CONFIG["indent"]))
+        # Write to latest
+        with open(output_file_latest, "w") as f:
+            json.dump(documentation, f, indent=int(OUTPUT_CONFIG["indent"]))
+
+        print(f"✓ Generated {output_file}")
+
+        # Print summary
+        types_count = len(documentation["types"])
+        classes_count = len(documentation["classes"])
+
+        total_functions = sum(len(cls["functions"]) for cls in documentation["classes"])
+
+        print("📊 Documentation Summary:")
+        print(f"   • {types_count} types documented")
+        print(f"   • {classes_count} classes documented")
+        print(f"   • {total_functions} functions documented")
+
+    except Exception as e:
+        print(f"❌ Error generating documentation: {e}")
+        import traceback
+
+        traceback.print_exc()

bin/fmt

@@ -6,9 +6,7 @@ set_source_and_root_dir
 ensure_virtual_env
 
 if [[ "$1" == "--check" ]]; then
-  black --check .
-  isort --check-only .
+  ruff format --check .
 else
-  black .
-  isort .
+  ruff format .
 fi

example.py

@@ -1,171 +1,508 @@
 # PostHog Python library example
-import argparse
+#
+# This script demonstrates various PostHog Python SDK capabilities including:
+# - Basic event capture and user identification
+# - Feature flag local evaluation
+# - Feature flag payloads
+# - Context management and tagging
+#
+# Setup:
+# 1. Copy .env.example to .env and fill in your PostHog credentials
+# 2. Run this script and choose from the interactive menu
+
+import os
 
 import posthog
 
-# Add argument parsing
-parser = argparse.ArgumentParser(description="PostHog Python library example")
-parser.add_argument(
-    "--flag",
-    default="person-on-events-enabled",
-    help="Feature flag key to check (default: person-on-events-enabled)",
-)
-args = parser.parse_args()
 
-posthog.debug = True
+def load_env_file():
+    """Load environment variables from .env file if it exists."""
+    env_path = os.path.join(os.path.dirname(__file__), ".env")
+    if os.path.exists(env_path):
+        with open(env_path, "r") as f:
+            for line in f:
+                line = line.strip()
+                if line and not line.startswith("#") and "=" in line:
+                    key, value = line.split("=", 1)
+                    os.environ.setdefault(key.strip(), value.strip())
 
-# You can find this key on the /setup page in PostHog
-posthog.project_api_key = "phc_gtWmTq3Pgl06u4sZY3TRcoQfp42yfuXHKoe8ZVSR6Kh"
-posthog.personal_api_key = "phx_fiRCOQkTA3o2ePSdLrFDAILLHjMu2Mv52vUi8MNruIm"
 
-# Where you host PostHog, with no trailing /.
-# You can remove this line if you're using posthog.com
-posthog.host = "http://localhost:8000"
+# Load .env file if it exists
+load_env_file()
+
+# Get configuration
+project_key = os.getenv("POSTHOG_PROJECT_API_KEY", "")
+personal_api_key = os.getenv("POSTHOG_PERSONAL_API_KEY", "")
+host = os.getenv("POSTHOG_HOST", "http://localhost:8000")
+
+# Check if project key is provided (required)
+if not project_key:
+    print("❌ Missing PostHog project API key!")
+    print("   Please set POSTHOG_PROJECT_API_KEY environment variable")
+    print("   or copy .env.example to .env and fill in your values")
+    exit(1)
+
+# Configure PostHog with credentials
+posthog.debug = False
+posthog.api_key = project_key
+posthog.project_api_key = project_key
+posthog.host = host
 posthog.poll_interval = 10
 
-print(
-    posthog.feature_enabled(
-        args.flag,  # Use the flag from command line arguments
-        "12345",
-        groups={"organization": str("0182ee91-8ef7-0000-4cb9-fedc5f00926a")},
-        group_properties={
-            "organization": {
-                "id": "0182ee91-8ef7-0000-4cb9-fedc5f00926a",
-                "created_at": "2022-06-30 11:44:52.984121+00:00",
-            }
-        },
+# Check if personal API key is available for local evaluation
+local_eval_available = bool(personal_api_key)
+if personal_api_key:
+    posthog.personal_api_key = personal_api_key
+
+print("🔑 PostHog Configuration:")
+print(f"   Project API Key: {project_key[:9]}...")
+if local_eval_available:
+    print("   Personal API Key: [SET]")
+else:
+    print("   Personal API Key: [NOT SET] - Local evaluation examples will be skipped")
+print(f"   Host: {host}\n")
+
+# Display menu and get user choice
+print("🚀 PostHog Python SDK Demo - Choose an example to run:\n")
+print("1. Identify and capture examples")
+local_eval_note = "" if local_eval_available else " [requires personal API key]"
+print(f"2. Feature flag local evaluation examples{local_eval_note}")
+print("3. Feature flag payload examples")
+print(f"4. Flag dependencies examples{local_eval_note}")
+print("5. Context management and tagging examples")
+print("6. Run all examples")
+print("7. Exit")
+choice = input("\nEnter your choice (1-7): ").strip()
+
+if choice == "1":
+    print("\n" + "=" * 60)
+    print("IDENTIFY AND CAPTURE EXAMPLES")
+    print("=" * 60)
+
+    posthog.debug = True
+
+    # Capture an event
+    print("📊 Capturing events...")
+    posthog.capture(
+        "event",
+        distinct_id="distinct_id",
+        properties={"property1": "value", "property2": "value"},
+        send_feature_flags=True,
+    )
+
+    # Alias a previous distinct id with a new one
+    print("🔗 Creating alias...")
+    posthog.alias("distinct_id", "new_distinct_id")
+
+    posthog.capture(
+        "event2",
+        distinct_id="new_distinct_id",
+        properties={"property1": "value", "property2": "value"},
+    )
+    posthog.capture(
+        "event-with-groups",
+        distinct_id="new_distinct_id",
+        properties={"property1": "value", "property2": "value"},
+        groups={"company": "id:5"},
+    )
+
+    # Add properties to the person
+    print("👤 Identifying user...")
+    posthog.set(
+        distinct_id="new_distinct_id", properties={"email": "something@something.com"}
+    )
+
+    # Add properties to a group
+    print("🏢 Identifying group...")
+    posthog.group_identify("company", "id:5", {"employees": 11})
+
+    # Properties set only once to the person
+    print("🔒 Setting properties once...")
+    posthog.set_once(
+        distinct_id="new_distinct_id", properties={"self_serve_signup": True}
+    )
+
+    # This will not change the property (because it was already set)
+    posthog.set_once(
+        distinct_id="new_distinct_id", properties={"self_serve_signup": False}
+    )
+
+    print("🔄 Updating properties...")
+    posthog.set(distinct_id="new_distinct_id", properties={"current_browser": "Chrome"})
+    posthog.set(
+        distinct_id="new_distinct_id", properties={"current_browser": "Firefox"}
+    )
+
+elif choice == "2":
+    if not local_eval_available:
+        print("\n❌ This example requires a personal API key for local evaluation.")
+        print(
+            "   Set POSTHOG_PERSONAL_API_KEY environment variable to run this example."
+        )
+        posthog.shutdown()
+        exit(1)
+
+    print("\n" + "=" * 60)
+    print("FEATURE FLAG LOCAL EVALUATION EXAMPLES")
+    print("=" * 60)
+
+    posthog.debug = True
+
+    print("🏁 Testing basic feature flags...")
+    print(
+        f"beta-feature for 'distinct_id': {posthog.feature_enabled('beta-feature', 'distinct_id')}"
+    )
+    print(
+        f"beta-feature for 'new_distinct_id': {posthog.feature_enabled('beta-feature', 'new_distinct_id')}"
+    )
+    print(
+        f"beta-feature with groups: {posthog.feature_enabled('beta-feature-groups', 'distinct_id', groups={'company': 'id:5'})}"
+    )
+
+    print("\n🌍 Testing location-based flags...")
+    # Assume test-flag has `City Name = Sydney` as a person property set
+    print(
+        f"Sydney user: {posthog.feature_enabled('test-flag', 'random_id_12345', person_properties={'$geoip_city_name': 'Sydney'})}"
+    )
+
+    print(
+        f"Sydney user (local only): {posthog.feature_enabled('test-flag', 'distinct_id_random_22', person_properties={'$geoip_city_name': 'Sydney'}, only_evaluate_locally=True)}"
+    )
+
+    print("\n📋 Getting all flags...")
+    print(f"All flags: {posthog.get_all_flags('distinct_id_random_22')}")
+    print(
+        f"All flags (local): {posthog.get_all_flags('distinct_id_random_22', only_evaluate_locally=True)}"
+    )
+    print(
+        f"All flags with properties: {posthog.get_all_flags('distinct_id_random_22', person_properties={'$geoip_city_name': 'Sydney'}, only_evaluate_locally=True)}"
+    )
+
+elif choice == "3":
+    print("\n" + "=" * 60)
+    print("FEATURE FLAG PAYLOAD EXAMPLES")
+    print("=" * 60)
+
+    posthog.debug = True
+
+    print("📦 Testing feature flag payloads...")
+    print(
+        f"beta-feature payload: {posthog.get_feature_flag_payload('beta-feature', 'distinct_id')}"
+    )
+    print(
+        f"All flags and payloads: {posthog.get_all_flags_and_payloads('distinct_id')}"
+    )
+    print(
+        f"Remote config payload: {posthog.get_remote_config_payload('encrypted_payload_flag_key')}"
+    )
+
+    # Get feature flag result with all details (enabled, variant, payload, key, reason)
+    print("\n🔍 Getting detailed flag result...")
+    result = posthog.get_feature_flag_result("beta-feature", "distinct_id")
+    if result:
+        print(f"Flag key: {result.key}")
+        print(f"Flag enabled: {result.enabled}")
+        print(f"Variant: {result.variant}")
+        print(f"Payload: {result.payload}")
+        print(f"Reason: {result.reason}")
+        # get_value() returns the variant if it exists, otherwise the enabled value
+        print(f"Value (variant or enabled): {result.get_value()}")
+
+elif choice == "4":
+    if not local_eval_available:
+        print("\n❌ This example requires a personal API key for local evaluation.")
+        print(
+            "   Set POSTHOG_PERSONAL_API_KEY environment variable to run this example."
+        )
+        posthog.shutdown()
+        exit(1)
+
+    print("\n" + "=" * 60)
+    print("FLAG DEPENDENCIES EXAMPLES")
+    print("=" * 60)
+    print("🔗 Testing flag dependencies with local evaluation...")
+    print(
+        "   Flag structure: 'test-flag-dependency' depends on 'beta-feature' being enabled"
+    )
+    print("")
+    print("📋 Required setup (if 'test-flag-dependency' doesn't exist):")
+    print("   1. Create feature flag 'beta-feature':")
+    print("      - Condition: email contains '@example.com'")
+    print("      - Rollout: 100%")
+    print("   2. Create feature flag 'test-flag-dependency':")
+    print("      - Condition: flag 'beta-feature' is enabled")
+    print("      - Rollout: 100%")
+    print("")
+
+    posthog.debug = True
+
+    # Test @example.com user (should satisfy dependency if flags exist)
+    result1 = posthog.feature_enabled(
+        "test-flag-dependency",
+        "example_user",
+        person_properties={"email": "user@example.com"},
         only_evaluate_locally=True,
     )
-)
+    print(f"✅ @example.com user (test-flag-dependency): {result1}")
 
-
-# Capture an event
-posthog.capture(
-    "distinct_id",
-    "event",
-    {"property1": "value", "property2": "value"},
-    send_feature_flags=True,
-)
-
-print(posthog.feature_enabled("beta-feature", "distinct_id"))
-print(
-    posthog.feature_enabled(
-        "beta-feature-groups", "distinct_id", groups={"company": "id:5"}
-    )
-)
-
-print(posthog.feature_enabled("beta-feature", "distinct_id"))
-
-# get payload
-print(posthog.get_feature_flag_payload("beta-feature", "distinct_id"))
-print(posthog.get_all_flags_and_payloads("distinct_id"))
-exit()
-# # Alias a previous distinct id with a new one
-
-posthog.alias("distinct_id", "new_distinct_id")
-
-posthog.capture(
-    "new_distinct_id", "event2", {"property1": "value", "property2": "value"}
-)
-posthog.capture(
-    "new_distinct_id",
-    "event-with-groups",
-    {"property1": "value", "property2": "value"},
-    groups={"company": "id:5"},
-)
-
-# # Add properties to the person
-posthog.identify("new_distinct_id", {"email": "something@something.com"})
-
-# Add properties to a group
-posthog.group_identify("company", "id:5", {"employees": 11})
-
-# properties set only once to the person
-posthog.set_once("new_distinct_id", {"self_serve_signup": True})
-
-
-posthog.set_once(
-    "new_distinct_id", {"self_serve_signup": False}
-)  # this will not change the property (because it was already set)
-
-posthog.set("new_distinct_id", {"current_browser": "Chrome"})
-posthog.set("new_distinct_id", {"current_browser": "Firefox"})
-
-
-# #############################################################################
-# Make sure you have a personal API key for the examples below
-
-# Local Evaluation
-
-# If flag has City=Sydney, this call doesn't go to `/decide`
-print(
-    posthog.feature_enabled(
-        "test-flag",
-        "distinct_id_random_22",
-        person_properties={"$geoip_city_name": "Sydney"},
-    )
-)
-
-print(
-    posthog.feature_enabled(
-        "test-flag",
-        "distinct_id_random_22",
-        person_properties={"$geoip_city_name": "Sydney"},
+    # Test non-example.com user (dependency should not be satisfied)
+    result2 = posthog.feature_enabled(
+        "test-flag-dependency",
+        "regular_user",
+        person_properties={"email": "user@other.com"},
         only_evaluate_locally=True,
     )
-)
+    print(f"❌ Regular user (test-flag-dependency): {result2}")
 
-
-print(posthog.get_all_flags("distinct_id_random_22"))
-print(posthog.get_all_flags("distinct_id_random_22", only_evaluate_locally=True))
-print(
-    posthog.get_all_flags(
-        "distinct_id_random_22",
-        person_properties={"$geoip_city_name": "Sydney"},
+    # Test beta-feature directly for comparison
+    beta1 = posthog.feature_enabled(
+        "beta-feature",
+        "example_user",
+        person_properties={"email": "user@example.com"},
         only_evaluate_locally=True,
     )
-)
-print(posthog.get_remote_config_payload("encrypted_payload_flag_key"))
+    beta2 = posthog.feature_enabled(
+        "beta-feature",
+        "regular_user",
+        person_properties={"email": "user@other.com"},
+        only_evaluate_locally=True,
+    )
+    print(f"📊 Beta feature comparison - @example.com: {beta1}, regular: {beta2}")
 
+    print("\n🎯 Results Summary:")
+    print(
+        f"   - Flag dependencies evaluated locally: {'✅ YES' if result1 != result2 else '❌ NO'}"
+    )
+    print("   - Zero API calls needed: ✅ YES (all evaluated locally)")
+    print("   - Python SDK supports flag dependencies: ✅ YES")
 
-# You can add tags to a context, and these are automatically added to any events (including exceptions) captured
-# within that context.
+    print("\n" + "-" * 60)
+    print("PRODUCTION-STYLE MULTIVARIATE DEPENDENCY CHAIN")
+    print("-" * 60)
+    print("🔗 Testing complex multivariate flag dependencies...")
+    print(
+        "   Structure: multivariate-root-flag -> multivariate-intermediate-flag -> multivariate-leaf-flag"
+    )
+    print("")
+    print("📋 Required setup (if flags don't exist):")
+    print(
+        "   1. Create 'multivariate-leaf-flag' with fruit variants (pineapple, mango, papaya, kiwi)"
+    )
+    print("      - pineapple: email = 'pineapple@example.com'")
+    print("      - mango: email = 'mango@example.com'")
+    print(
+        "   2. Create 'multivariate-intermediate-flag' with color variants (blue, red)"
+    )
+    print("      - blue: depends on multivariate-leaf-flag = 'pineapple'")
+    print("      - red: depends on multivariate-leaf-flag = 'mango'")
+    print(
+        "   3. Create 'multivariate-root-flag' with show variants (breaking-bad, the-wire)"
+    )
+    print("      - breaking-bad: depends on multivariate-intermediate-flag = 'blue'")
+    print("      - the-wire: depends on multivariate-intermediate-flag = 'red'")
+    print("")
 
-# You can enter a new context using a with statement. Any exceptions thrown in the context will be captured,
-# and tagged with the context tags. Other events captured will also be tagged with the context tags. By default,
-# the new context inherits tags from the parent context.
-with posthog.new_context():
-    posthog.tag("transaction_id", "abc123")
-    posthog.tag("some_arbitrary_value", {"tags": "can be dicts"})
+    # Test pineapple -> blue -> breaking-bad chain
+    dependent_result3 = posthog.get_feature_flag(
+        "multivariate-root-flag",
+        "regular_user",
+        person_properties={"email": "pineapple@example.com"},
+        only_evaluate_locally=True,
+    )
+    if str(dependent_result3) != "breaking-bad":
+        print(
+            f"     ❌ Something went wrong evaluating 'multivariate-root-flag' with pineapple@example.com. Expected 'breaking-bad', got '{dependent_result3}'"
+        )
+    else:
+        print("✅ 'multivariate-root-flag' with email pineapple@example.com succeeded")
 
-    # This event will be captured with the tags set above
-    posthog.capture("order_processed")
-    # This exception will be captured with the tags set above
-    raise Exception("Order processing failed")
+    # Test mango -> red -> the-wire chain
+    dependent_result4 = posthog.get_feature_flag(
+        "multivariate-root-flag",
+        "regular_user",
+        person_properties={"email": "mango@example.com"},
+        only_evaluate_locally=True,
+    )
+    if str(dependent_result4) != "the-wire":
+        print(
+            f"     ❌ Something went wrong evaluating multivariate-root-flag with mango@example.com. Expected 'the-wire', got '{dependent_result4}'"
+        )
+    else:
+        print("✅ 'multivariate-root-flag' with email mango@example.com succeeded")
 
+    # Show the complete chain evaluation
+    print("\n🔍 Complete dependency chain evaluation:")
+    for email, expected_chain in [
+        ("pineapple@example.com", ["pineapple", "blue", "breaking-bad"]),
+        ("mango@example.com", ["mango", "red", "the-wire"]),
+    ]:
+        leaf = posthog.get_feature_flag(
+            "multivariate-leaf-flag",
+            "regular_user",
+            person_properties={"email": email},
+            only_evaluate_locally=True,
+        )
+        intermediate = posthog.get_feature_flag(
+            "multivariate-intermediate-flag",
+            "regular_user",
+            person_properties={"email": email},
+            only_evaluate_locally=True,
+        )
+        root = posthog.get_feature_flag(
+            "multivariate-root-flag",
+            "regular_user",
+            person_properties={"email": email},
+            only_evaluate_locally=True,
+        )
 
-# Use fresh=True to start with a clean context (no inherited tags)
-with posthog.new_context(fresh=True):
-    posthog.tag("session_id", "xyz789")
-    # Only session_id tag will be present, no inherited tags
-    raise Exception("Session handling failed")
+        actual_chain = [str(leaf), str(intermediate), str(root)]
+        chain_success = actual_chain == expected_chain
 
+        print(f"   📧 {email}:")
+        print(f"      Expected: {' -> '.join(map(str, expected_chain))}")
+        print(f"      Actual:   {' -> '.join(map(str, actual_chain))}")
+        print(f"      Status:   {'✅ SUCCESS' if chain_success else '❌ FAILED'}")
 
-# You can also use the `@posthog.scoped()` decorator to enter a new context.
-# By default, it inherits tags from the parent context
-@posthog.scoped()
-def process_order(order_id):
-    posthog.tag("order_id", order_id)
-    # Exception will be captured and tagged automatically
-    raise Exception("Order processing failed")
+    print("\n🎯 Multivariate Chain Summary:")
+    print("   - Complex dependency chains: ✅ SUPPORTED")
+    print("   - Multivariate flag dependencies: ✅ SUPPORTED")
+    print("   - Local evaluation of chains: ✅ WORKING")
 
+elif choice == "5":
+    print("\n" + "=" * 60)
+    print("CONTEXT MANAGEMENT AND TAGGING EXAMPLES")
+    print("=" * 60)
 
-# Use fresh=True to start with a clean context (no inherited tags)
-@posthog.scoped(fresh=True)
-def process_payment(payment_id):
-    posthog.tag("payment_id", payment_id)
-    # Only payment_id tag will be present, no inherited tags
-    raise Exception("Payment processing failed")
+    posthog.debug = True
 
+    print("🏷️ Testing context management...")
+    print(
+        "You can add tags to a context, and these are automatically added to any events captured within that context."
+    )
+
+    # You can enter a new context using a with statement. Any exceptions thrown in the context will be captured,
+    # and tagged with the context tags. Other events captured will also be tagged with the context tags. By default,
+    # the new context inherits tags from the parent context.
+    try:
+        with posthog.new_context():
+            posthog.tag("transaction_id", "abc123")
+            posthog.tag("some_arbitrary_value", {"tags": "can be dicts"})
+
+            # This event will be captured with the tags set above
+            posthog.capture("order_processed")
+            print("✅ Event captured with inherited context tags")
+            # This exception will be captured with the tags set above
+            # raise Exception("Order processing failed")
+    except Exception as e:
+        print(f"Exception captured: {e}")
+
+    # Use fresh=True to start with a clean context (no inherited tags)
+    try:
+        with posthog.new_context(fresh=True):
+            posthog.tag("session_id", "xyz789")
+            # Only session_id tag will be present, no inherited tags
+            posthog.capture("session_event")
+            print("✅ Event captured with fresh context tags")
+            # raise Exception("Session handling failed")
+    except Exception as e:
+        print(f"Exception captured: {e}")
+
+    # You can also use the `@posthog.scoped()` decorator to enter a new context.
+    # By default, it inherits tags from the parent context
+    @posthog.scoped()
+    def process_order(order_id):
+        posthog.tag("order_id", order_id)
+        posthog.capture("order_step_completed")
+        print(f"✅ Order {order_id} processed with scoped context")
+        # Exception will be captured and tagged automatically
+        # raise Exception("Order processing failed")
+
+    # Use fresh=True to start with a clean context (no inherited tags)
+    @posthog.scoped(fresh=True)
+    def process_payment(payment_id):
+        posthog.tag("payment_id", payment_id)
+        posthog.capture("payment_processed")
+        print(f"✅ Payment {payment_id} processed with fresh scoped context")
+        # Only payment_id tag will be present, no inherited tags
+        # raise Exception("Payment processing failed")
+
+    process_order("12345")
+    process_payment("67890")
+
+elif choice == "6":
+    print("\n🔄 Running all examples...")
+    if not local_eval_available:
+        print("   (Skipping local evaluation examples - no personal API key set)\n")
+
+    # Run example 1
+    print(f"\n{'🔸' * 20} IDENTIFY AND CAPTURE {'🔸' * 20}")
+    posthog.debug = True
+    print("📊 Capturing events...")
+    posthog.capture(
+        "event",
+        distinct_id="distinct_id",
+        properties={"property1": "value", "property2": "value"},
+        send_feature_flags=True,
+    )
+    print("🔗 Creating alias...")
+    posthog.alias("distinct_id", "new_distinct_id")
+    print("👤 Identifying user...")
+    posthog.set(
+        distinct_id="new_distinct_id", properties={"email": "something@something.com"}
+    )
+
+    # Run example 2 (requires local evaluation)
+    if local_eval_available:
+        print(f"\n{'🔸' * 20} FEATURE FLAGS {'🔸' * 20}")
+        print("🏁 Testing basic feature flags...")
+        print(f"beta-feature: {posthog.feature_enabled('beta-feature', 'distinct_id')}")
+        print(
+            f"Sydney user: {posthog.feature_enabled('test-flag', 'random_id_12345', person_properties={'$geoip_city_name': 'Sydney'})}"
+        )
+
+    # Run example 3
+    print(f"\n{'🔸' * 20} PAYLOADS {'🔸' * 20}")
+    print("📦 Testing payloads...")
+    print(f"Payload: {posthog.get_feature_flag_payload('beta-feature', 'distinct_id')}")
+
+    # Run example 4 (requires local evaluation)
+    if local_eval_available:
+        print(f"\n{'🔸' * 20} FLAG DEPENDENCIES {'🔸' * 20}")
+        print("🔗 Testing flag dependencies...")
+        result1 = posthog.feature_enabled(
+            "test-flag-dependency",
+            "demo_user",
+            person_properties={"email": "user@example.com"},
+            only_evaluate_locally=True,
+        )
+        result2 = posthog.feature_enabled(
+            "test-flag-dependency",
+            "demo_user2",
+            person_properties={"email": "user@other.com"},
+            only_evaluate_locally=True,
+        )
+        print(f"✅ @example.com user: {result1}, regular user: {result2}")
+
+    # Run example 5
+    print(f"\n{'🔸' * 20} CONTEXT MANAGEMENT {'🔸' * 20}")
+    print("🏷️ Testing context management...")
+    with posthog.new_context():
+        posthog.tag("demo_run", "all_examples")
+        posthog.capture("demo_completed")
+        print("✅ Demo completed with context tags")
+
+elif choice == "7":
+    print("👋 Goodbye!")
+    posthog.shutdown()
+    exit()
+
+else:
+    print("❌ Invalid choice. Please run again and select 1-7.")
+    posthog.shutdown()
+    exit()
+
+print("\n" + "=" * 60)
+print("✅ Example completed!")
+print("=" * 60)
 
 posthog.shutdown()

examples/redis_flag_cache.py

@@ -0,0 +1,144 @@
+"""
+Redis-based distributed cache for PostHog feature flag definitions.
+
+This example demonstrates how to implement a FlagDefinitionCacheProvider
+using Redis for multi-instance deployments (leader election pattern).
+
+Usage:
+    import redis
+    from posthog import Posthog
+
+    redis_client = redis.Redis(host='localhost', port=6379, decode_responses=True)
+    cache = RedisFlagCache(redis_client, service_key="my-service")
+
+    posthog = Posthog(
+        "<project_api_key>",
+        personal_api_key="<personal_api_key>",
+        flag_definition_cache_provider=cache,
+    )
+
+Requirements:
+    pip install redis
+"""
+
+import json
+import uuid
+
+from posthog import FlagDefinitionCacheData, FlagDefinitionCacheProvider
+from redis import Redis
+from typing import Optional
+
+
+class RedisFlagCache(FlagDefinitionCacheProvider):
+    """
+    A distributed cache for PostHog feature flag definitions using Redis.
+
+    In a multi-instance deployment (e.g., multiple serverless functions or containers),
+    we want only ONE instance to poll PostHog for flag updates, while all instances
+    share the cached results. This prevents N instances from making N redundant API calls.
+
+    The implementation uses leader election:
+    - One instance "wins" and becomes responsible for fetching
+    - Other instances read from the shared cache
+    - If the leader dies, the lock expires (TTL) and another instance takes over
+
+    Uses Lua scripts for atomic operations, following Redis distributed lock best practices:
+    https://redis.io/docs/latest/develop/clients/patterns/distributed-locks/
+    """
+
+    LOCK_TTL_MS = 60 * 1000  # 60 seconds, should be longer than the flags poll interval
+    CACHE_TTL_SECONDS = 60 * 60 * 24  # 24 hours
+
+    # Lua script: acquire lock if free, or extend if we own it
+    _LUA_TRY_LEAD = """
+        local current = redis.call('GET', KEYS[1])
+        if current == false then
+            redis.call('SET', KEYS[1], ARGV[1], 'PX', ARGV[2])
+            return 1
+        elseif current == ARGV[1] then
+            redis.call('PEXPIRE', KEYS[1], ARGV[2])
+            return 1
+        end
+        return 0
+    """
+
+    # Lua script: release lock only if we own it
+    _LUA_STOP_LEAD = """
+        if redis.call('GET', KEYS[1]) == ARGV[1] then
+            return redis.call('DEL', KEYS[1])
+        end
+        return 0
+    """
+
+    def __init__(self, redis: Redis[str], service_key: str):
+        """
+        Initialize the Redis flag cache.
+
+        Args:
+            redis: A redis-py client instance. Must be configured with
+                   decode_responses=True for correct string handling.
+            service_key: A unique identifier for this service/environment.
+                         Used to scope Redis keys, allowing multiple services
+                         or environments to share the same Redis instance.
+                         Examples: "my-api-prod", "checkout-service", "staging".
+
+        Redis Keys Created:
+            - posthog:flags:{service_key} - Cached flag definitions (JSON)
+            - posthog:flags:{service_key}:lock - Leader election lock
+
+        Example:
+            redis_client = redis.Redis(
+                host='localhost',
+                port=6379,
+                decode_responses=True
+            )
+            cache = RedisFlagCache(redis_client, service_key="my-api-prod")
+        """
+        self._redis = redis
+        self._cache_key = f"posthog:flags:{service_key}"
+        self._lock_key = f"posthog:flags:{service_key}:lock"
+        self._instance_id = str(uuid.uuid4())
+        self._try_lead = self._redis.register_script(self._LUA_TRY_LEAD)
+        self._stop_lead = self._redis.register_script(self._LUA_STOP_LEAD)
+
+    def get_flag_definitions(self) -> Optional[FlagDefinitionCacheData]:
+        """
+        Retrieve cached flag definitions from Redis.
+
+        Returns:
+            Cached flag definitions if available, None otherwise.
+        """
+        cached = self._redis.get(self._cache_key)
+        return json.loads(cached) if cached else None
+
+    def should_fetch_flag_definitions(self) -> bool:
+        """
+        Determines if this instance should fetch flag definitions from PostHog.
+
+        Atomically either:
+        - Acquires the lock if no one holds it, OR
+        - Extends the lock TTL if we already hold it
+
+        Returns:
+            True if this instance is the leader and should fetch, False otherwise.
+        """
+        result = self._try_lead(
+            keys=[self._lock_key],
+            args=[self._instance_id, self.LOCK_TTL_MS],
+        )
+        return result == 1
+
+    def on_flag_definitions_received(self, data: FlagDefinitionCacheData) -> None:
+        """
+        Store fetched flag definitions in Redis.
+
+        Args:
+            data: The flag definitions to cache.
+        """
+        self._redis.set(self._cache_key, json.dumps(data), ex=self.CACHE_TTL_SECONDS)
+
+    def shutdown(self) -> None:
+        """
+        Release leadership if we hold it. Safe to call even if not the leader.
+        """
+        self._stop_lead(keys=[self._lock_key], args=[self._instance_id])

examples/remote_config.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python3
+"""
+Simple test script for PostHog remote config endpoint.
+"""
+
+import posthog
+
+# Initialize PostHog client
+posthog.api_key = "phc_..."
+posthog.personal_api_key = "phs_..."  # or "phx_..."
+posthog.host = "http://localhost:8000"  # or "https://us.posthog.com"
+posthog.debug = True
+
+
+def test_remote_config():
+    """Test remote config payload retrieval."""
+    print("Testing remote config endpoint...")
+
+    # Test feature flag key - replace with an actual flag key from your project
+    flag_key = "unencrypted-remote-config-setting"
+
+    try:
+        # Get remote config payload
+        payload = posthog.get_remote_config_payload(flag_key)
+        print(f"✅ Success! Remote config payload for '{flag_key}': {payload}")
+
+    except Exception as e:
+        print(f"❌ Error getting remote config: {e}")
+
+
+if __name__ == "__main__":
+    test_remote_config()

integration_tests/django5/.gitignore

@@ -0,0 +1,4 @@
+db.sqlite3
+*.pyc
+__pycache__/
+.pytest_cache/

integration_tests/django5/manage.py

@@ -0,0 +1,23 @@
+#!/usr/bin/env python
+"""Django's command-line utility for administrative tasks."""
+
+import os
+import sys
+
+
+def main():
+    """Run administrative tasks."""
+    os.environ.setdefault("DJANGO_SETTINGS_MODULE", "testdjango.settings")
+    try:
+        from django.core.management import execute_from_command_line
+    except ImportError as exc:
+        raise ImportError(
+            "Couldn't import Django. Are you sure it's installed and "
+            "available on your PYTHONPATH environment variable? Did you "
+            "forget to activate a virtual environment?"
+        ) from exc
+    execute_from_command_line(sys.argv)
+
+
+if __name__ == "__main__":
+    main()

integration_tests/django5/pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "test-django5"
+version = "0.1.0"
+requires-python = ">=3.12"
+dependencies = [
+    "django~=5.2.7",
+    "uvicorn[standard]~=0.38.0",
+    "posthog",
+    "pytest~=8.4.2",
+    "pytest-asyncio~=1.2.0",
+    "pytest-django~=4.11.1",
+    "httpx~=0.28.1",
+]
+
+[tool.uv]
+required-version = ">=0.5"
+
+[tool.uv.sources]
+posthog = { path = "../..", editable = true }

integration_tests/django5/test_exception_capture.py

@@ -0,0 +1,111 @@
+"""
+Test that verifies exception capture functionality.
+
+These tests verify that exceptions are actually captured to PostHog, not just that
+500 responses are returned.
+
+Without process_exception(), view exceptions are NOT captured to PostHog (v6.7.11 and earlier).
+With process_exception(), Django calls this method to capture exceptions before
+converting them to 500 responses.
+"""
+
+import os
+import django
+
+# Setup Django before importing anything else
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "testdjango.settings")
+django.setup()
+
+import pytest  # noqa: E402
+from httpx import AsyncClient, ASGITransport  # noqa: E402
+from django.core.asgi import get_asgi_application  # noqa: E402
+
+
+@pytest.fixture(scope="session")
+def asgi_app():
+    """Shared ASGI application for all tests."""
+    return get_asgi_application()
+
+
+@pytest.mark.asyncio
+async def test_async_exception_is_captured(asgi_app):
+    """
+    Test that async view exceptions are captured to PostHog.
+
+    The middleware's process_exception() method ensures exceptions are captured.
+    Without it (v6.7.11 and earlier), exceptions are NOT captured even though 500 is returned.
+    """
+    from unittest.mock import patch
+
+    # Track captured exceptions
+    captured = []
+
+    def mock_capture(exception, **kwargs):
+        """Mock capture_exception to record calls."""
+        captured.append(
+            {
+                "exception": exception,
+                "type": type(exception).__name__,
+                "message": str(exception),
+            }
+        )
+
+    # Patch at the posthog module level where middleware imports from
+    with patch("posthog.capture_exception", side_effect=mock_capture):
+        async with AsyncClient(
+            transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+        ) as ac:
+            response = await ac.get("/test/async-exception")
+
+        # Django returns 500
+        assert response.status_code == 500
+
+        # CRITICAL: Verify PostHog captured the exception
+        assert len(captured) > 0, "Exception was NOT captured to PostHog!"
+
+        # Verify it's the right exception
+        exception_data = captured[0]
+        assert exception_data["type"] == "ValueError"
+        assert "Test exception from Django 5 async view" in exception_data["message"]
+
+
+@pytest.mark.asyncio
+async def test_sync_exception_is_captured(asgi_app):
+    """
+    Test that sync view exceptions are captured to PostHog.
+
+    The middleware's process_exception() method ensures exceptions are captured.
+    Without it (v6.7.11 and earlier), exceptions are NOT captured even though 500 is returned.
+    """
+    from unittest.mock import patch
+
+    # Track captured exceptions
+    captured = []
+
+    def mock_capture(exception, **kwargs):
+        """Mock capture_exception to record calls."""
+        captured.append(
+            {
+                "exception": exception,
+                "type": type(exception).__name__,
+                "message": str(exception),
+            }
+        )
+
+    # Patch at the posthog module level where middleware imports from
+    with patch("posthog.capture_exception", side_effect=mock_capture):
+        async with AsyncClient(
+            transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+        ) as ac:
+            response = await ac.get("/test/sync-exception")
+
+        # Django returns 500
+        assert response.status_code == 500
+
+        # CRITICAL: Verify PostHog captured the exception
+        assert len(captured) > 0, "Exception was NOT captured to PostHog!"
+
+        # Verify it's the right exception
+        exception_data = captured[0]
+        assert exception_data["type"] == "ValueError"
+        assert "Test exception from Django 5 sync view" in exception_data["message"]

integration_tests/django5/test_middleware.py

@@ -0,0 +1,170 @@
+"""
+Tests for PostHog Django middleware in async context.
+
+These tests verify that the middleware correctly handles:
+1. Async user access (request.auser() in Django 5)
+2. Exception capture in both sync and async views
+3. No SynchronousOnlyOperation errors in async context
+
+Tests run directly against the ASGI application without needing a server.
+"""
+
+import os
+import django
+
+# Setup Django before importing anything else
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "testdjango.settings")
+django.setup()
+
+import pytest  # noqa: E402
+from httpx import AsyncClient, ASGITransport  # noqa: E402
+from django.core.asgi import get_asgi_application  # noqa: E402
+
+
+@pytest.fixture(scope="session")
+def asgi_app():
+    """Shared ASGI application for all tests."""
+    return get_asgi_application()
+
+
+@pytest.mark.asyncio
+async def test_async_user_access(asgi_app):
+    """
+    Test that middleware can access request.user in async context.
+
+    In Django 5, this requires using await request.auser() instead of request.user
+    to avoid SynchronousOnlyOperation error.
+
+    Without authentication, request.user is AnonymousUser which doesn't
+    trigger the lazy loading bug. This test verifies the middleware works
+    in the common case.
+    """
+    async with AsyncClient(
+        transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+    ) as ac:
+        response = await ac.get("/test/async-user")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["status"] == "success"
+    assert "django_version" in data
+
+
+@pytest.mark.django_db(transaction=True)
+@pytest.mark.asyncio
+async def test_async_authenticated_user_access(asgi_app):
+    """
+    Test that middleware can access an authenticated user in async context.
+
+    This is the critical test that triggers the SynchronousOnlyOperation bug
+    in v6.7.11. When AuthenticationMiddleware sets request.user to a
+    SimpleLazyObject wrapping a database query, accessing user.pk or user.email
+    in async context causes the error.
+
+    In v6.7.11, extract_request_user() does getattr(user, "is_authenticated", False)
+    which triggers the lazy object evaluation synchronously.
+
+    The fix uses await request.auser() instead to avoid this.
+    """
+    from django.contrib.auth import get_user_model
+    from django.test import Client
+    from asgiref.sync import sync_to_async
+    from django.test import override_settings
+
+    # Create a test user (must use sync_to_async since we're in async test)
+    User = get_user_model()
+
+    @sync_to_async
+    def create_or_get_user():
+        user, created = User.objects.get_or_create(
+            username="testuser",
+            defaults={
+                "email": "test@example.com",
+            },
+        )
+        if created:
+            user.set_password("testpass123")
+            user.save()
+        return user
+
+    user = await create_or_get_user()
+
+    # Create a session with authenticated user (sync operation)
+    @sync_to_async
+    def create_session():
+        client = Client()
+        client.force_login(user)
+        return client.cookies.get("sessionid")
+
+    session_cookie = await create_session()
+
+    if not session_cookie:
+        pytest.skip("Could not create authenticated session")
+
+    # Make request with session cookie - this should trigger the bug in v6.7.11
+    # Disable exception capture to see the SynchronousOnlyOperation clearly
+    with override_settings(POSTHOG_MW_CAPTURE_EXCEPTIONS=False):
+        async with AsyncClient(
+            transport=ASGITransport(app=asgi_app),
+            base_url="http://testserver",
+            cookies={"sessionid": session_cookie.value},
+        ) as ac:
+            response = await ac.get("/test/async-user")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["status"] == "success"
+        assert data["user_authenticated"]
+
+
+@pytest.mark.asyncio
+async def test_sync_user_access(asgi_app):
+    """
+    Test that middleware works with sync views.
+
+    This should always work regardless of middleware version.
+    """
+    async with AsyncClient(
+        transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+    ) as ac:
+        response = await ac.get("/test/sync-user")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["status"] == "success"
+
+
+@pytest.mark.asyncio
+async def test_async_exception_capture(asgi_app):
+    """
+    Test that middleware handles exceptions from async views.
+
+    The middleware's process_exception() method captures view exceptions to PostHog
+    before Django converts them to 500 responses. This test verifies the exception
+    causes a 500 response. See test_exception_capture.py for tests that verify
+    actual exception capture to PostHog.
+    """
+    async with AsyncClient(
+        transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+    ) as ac:
+        response = await ac.get("/test/async-exception")
+
+    # Django returns 500 for unhandled exceptions
+    assert response.status_code == 500
+
+
+@pytest.mark.asyncio
+async def test_sync_exception_capture(asgi_app):
+    """
+    Test that middleware handles exceptions from sync views.
+
+    The middleware's process_exception() method captures view exceptions to PostHog.
+    This test verifies the exception causes a 500 response.
+    """
+    async with AsyncClient(
+        transport=ASGITransport(app=asgi_app), base_url="http://testserver"
+    ) as ac:
+        response = await ac.get("/test/sync-exception")
+
+    # Django returns 500 for unhandled exceptions
+    assert response.status_code == 500

integration_tests/django5/testdjango/asgi.py

@@ -0,0 +1,16 @@
+"""
+ASGI config for testdjango project.
+
+It exposes the ASGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.2/howto/deployment/asgi/
+"""
+
+import os
+
+from django.core.asgi import get_asgi_application
+
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "testdjango.settings")
+
+application = get_asgi_application()

integration_tests/django5/testdjango/settings.py

@@ -0,0 +1,129 @@
+"""
+Django settings for testdjango project.
+
+Generated by 'django-admin startproject' using Django 5.2.7.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.2/topics/settings/
+
+For the full list of settings and their values, see
+https://docs.djangoproject.com/en/5.2/ref/settings/
+"""
+
+from pathlib import Path
+
+# Build paths inside the project like this: BASE_DIR / 'subdir'.
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+
+# Quick-start development settings - unsuitable for production
+# See https://docs.djangoproject.com/en/5.2/howto/deployment/checklist/
+
+# SECURITY WARNING: keep the secret key used in production secret!
+SECRET_KEY = "django-insecure-q5(&wfw@_lb)noyowbfl$2ls8c82hl__0f9s5(mohlh2)aas#3"
+
+# SECURITY WARNING: don't run with debug turned on in production!
+DEBUG = True
+
+ALLOWED_HOSTS = ["*"]
+
+
+# Application definition
+
+INSTALLED_APPS = [
+    "django.contrib.admin",
+    "django.contrib.auth",
+    "django.contrib.contenttypes",
+    "django.contrib.sessions",
+    "django.contrib.messages",
+    "django.contrib.staticfiles",
+]
+
+MIDDLEWARE = [
+    "django.middleware.security.SecurityMiddleware",
+    "django.contrib.sessions.middleware.SessionMiddleware",
+    "django.middleware.common.CommonMiddleware",
+    "django.middleware.csrf.CsrfViewMiddleware",
+    "django.contrib.auth.middleware.AuthenticationMiddleware",
+    "django.contrib.messages.middleware.MessageMiddleware",
+    "django.middleware.clickjacking.XFrameOptionsMiddleware",
+    "posthog.integrations.django.PosthogContextMiddleware",  # Test PostHog middleware
+]
+
+ROOT_URLCONF = "testdjango.urls"
+
+TEMPLATES = [
+    {
+        "BACKEND": "django.template.backends.django.DjangoTemplates",
+        "DIRS": [],
+        "APP_DIRS": True,
+        "OPTIONS": {
+            "context_processors": [
+                "django.template.context_processors.request",
+                "django.contrib.auth.context_processors.auth",
+                "django.contrib.messages.context_processors.messages",
+            ],
+        },
+    },
+]
+
+WSGI_APPLICATION = "testdjango.wsgi.application"
+
+
+# Database
+# https://docs.djangoproject.com/en/5.2/ref/settings/#databases
+
+DATABASES = {
+    "default": {
+        "ENGINE": "django.db.backends.sqlite3",
+        "NAME": BASE_DIR / "db.sqlite3",
+    }
+}
+
+
+# Password validation
+# https://docs.djangoproject.com/en/5.2/ref/settings/#auth-password-validators
+
+AUTH_PASSWORD_VALIDATORS = [
+    {
+        "NAME": "django.contrib.auth.password_validation.UserAttributeSimilarityValidator",
+    },
+    {
+        "NAME": "django.contrib.auth.password_validation.MinimumLengthValidator",
+    },
+    {
+        "NAME": "django.contrib.auth.password_validation.CommonPasswordValidator",
+    },
+    {
+        "NAME": "django.contrib.auth.password_validation.NumericPasswordValidator",
+    },
+]
+
+
+# Internationalization
+# https://docs.djangoproject.com/en/5.2/topics/i18n/
+
+LANGUAGE_CODE = "en-us"
+
+TIME_ZONE = "UTC"
+
+USE_I18N = True
+
+USE_TZ = True
+
+
+# Static files (CSS, JavaScript, Images)
+# https://docs.djangoproject.com/en/5.2/howto/static-files/
+
+STATIC_URL = "static/"
+
+# Default primary key field type
+# https://docs.djangoproject.com/en/5.2/ref/settings/#default-auto-field
+
+DEFAULT_AUTO_FIELD = "django.db.models.BigAutoField"
+
+
+# PostHog settings for testing
+POSTHOG_API_KEY = "test-key"
+POSTHOG_HOST = "https://app.posthog.com"
+POSTHOG_MW_CAPTURE_EXCEPTIONS = True

integration_tests/django5/testdjango/urls.py

@@ -0,0 +1,28 @@
+"""
+URL configuration for testdjango project.
+
+The `urlpatterns` list routes URLs to views. For more information please see:
+    https://docs.djangoproject.com/en/5.2/topics/http/urls/
+Examples:
+Function views
+    1. Add an import:  from my_app import views
+    2. Add a URL to urlpatterns:  path('', views.home, name='home')
+Class-based views
+    1. Add an import:  from other_app.views import Home
+    2. Add a URL to urlpatterns:  path('', Home.as_view(), name='home')
+Including another URLconf
+    1. Import the include() function: from django.urls import include, path
+    2. Add a URL to urlpatterns:  path('blog/', include('blog.urls'))
+"""
+
+from django.contrib import admin
+from django.urls import path
+from testdjango import views
+
+urlpatterns = [
+    path("admin/", admin.site.urls),
+    path("test/async-user", views.test_async_user),
+    path("test/sync-user", views.test_sync_user),
+    path("test/async-exception", views.test_async_exception),
+    path("test/sync-exception", views.test_sync_exception),
+]

integration_tests/django5/testdjango/views.py

@@ -0,0 +1,50 @@
+"""
+Test views for validating PostHog middleware with Django 5 ASGI.
+"""
+
+from django.http import JsonResponse
+
+
+async def test_async_user(request):
+    """
+    Async view that tests middleware with request.user access.
+
+    The middleware will access request.user (SimpleLazyObject) via auser()
+    in async context. Without the fix, this causes SynchronousOnlyOperation.
+    """
+    # The middleware has already accessed request.user via auser()
+    # If we got here, the fix works!
+    user = await request.auser()
+
+    return JsonResponse(
+        {
+            "status": "success",
+            "message": "Django 5 async middleware test passed!",
+            "django_version": "5.x",
+            "user_authenticated": user.is_authenticated if user else False,
+            "note": "Middleware used await request.auser() successfully",
+        }
+    )
+
+
+def test_sync_user(request):
+    """Sync view for comparison."""
+    return JsonResponse(
+        {
+            "status": "success",
+            "message": "Sync view works",
+            "user_authenticated": request.user.is_authenticated
+            if hasattr(request, "user")
+            else False,
+        }
+    )
+
+
+async def test_async_exception(request):
+    """Async view that raises an exception for testing exception capture."""
+    raise ValueError("Test exception from Django 5 async view")
+
+
+def test_sync_exception(request):
+    """Sync view that raises an exception for testing exception capture."""
+    raise ValueError("Test exception from Django 5 sync view")

integration_tests/django5/testdjango/wsgi.py

@@ -0,0 +1,16 @@
+"""
+WSGI config for testdjango project.
+
+It exposes the WSGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.2/howto/deployment/wsgi/
+"""
+
+import os
+
+from django.core.wsgi import get_wsgi_application
+
+os.environ.setdefault("DJANGO_SETTINGS_MODULE", "testdjango.settings")
+
+application = get_wsgi_application()

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+    { url = "https://files.pythonhosted.org/packages/fa/a8/5b41e0da817d64113292ab1f8247140aac61cbf6cfd085d6a0fa77f4984f/websockets-15.0.1-py3-none-any.whl", hash = "sha256:f7a866fbc1e97b5c617ee4116daaa09b722101d4a3c170c787450ba409f9736f", size = 169743, upload-time = "2025-03-05T20:03:39.41Z" },
+]

mypy-baseline.txt

@@ -22,16 +22,14 @@ posthog/client.py:0: error: Library stubs not installed for "six"  [import-untyp
 posthog/client.py:0: note: Hint: "python3 -m pip install types-six"
 posthog/client.py:0: error: Name "queue" already defined (by an import)  [no-redef]
 posthog/client.py:0: error: Need type annotation for "queue"  [var-annotated]
-posthog/client.py:0: error: Item "None" of "Any | None" has no attribute "get"  [union-attr]
-simulator.py:0: error: Unexpected keyword argument "anonymous_id" for "capture"  [call-arg]
-posthog/__init__.py:0: note: "capture" defined here
-simulator.py:0: error: Unexpected keyword argument "anonymous_id" for "identify"  [call-arg]
-posthog/__init__.py:0: note: "identify" defined here
-simulator.py:0: error: Unexpected keyword argument "traits" for "identify"  [call-arg]
-posthog/__init__.py:0: note: "identify" defined here
-example.py:0: error: Statement is unreachable  [unreachable]
-posthog/ai/utils.py:0: error: Need type annotation for "output" (hint: "output: list[<type>] = ...")  [var-annotated]
-posthog/ai/utils.py:0: error: Function "builtins.any" is not valid as a type  [valid-type]
-posthog/ai/utils.py:0: note: Perhaps you meant "typing.Any" instead of "any"?
-posthog/ai/utils.py:0: error: Function "builtins.any" is not valid as a type  [valid-type]
-posthog/ai/utils.py:0: note: Perhaps you meant "typing.Any" instead of "any"?
+posthog/client.py:0: error: Incompatible types in assignment (expression has type "Any | list[Any]", variable has type "None")  [assignment]
+posthog/client.py:0: error: Incompatible types in assignment (expression has type "dict[Any, Any]", variable has type "None")  [assignment]
+posthog/client.py:0: error: "None" has no attribute "__iter__" (not iterable)  [attr-defined]
+posthog/client.py:0: error: Statement is unreachable  [unreachable]
+posthog/client.py:0: error: Right operand of "and" is never evaluated  [unreachable]
+posthog/client.py:0: error: Incompatible types in assignment (expression has type "Poller", variable has type "None")  [assignment]
+posthog/client.py:0: error: "None" has no attribute "start"  [attr-defined]
+posthog/client.py:0: error: Statement is unreachable  [unreachable]
+posthog/client.py:0: error: Statement is unreachable  [unreachable]
+posthog/client.py:0: error: Name "urlparse" already defined (possibly by an import)  [no-redef]
+posthog/client.py:0: error: Name "parse_qs" already defined (possibly by an import)  [no-redef]

posthog/ai/__init__.py

@@ -0,0 +1,3 @@
+from posthog.ai.prompts import Prompts
+
+__all__ = ["Prompts"]

posthog/ai/anthropic/__init__.py

@@ -6,6 +6,12 @@ from .anthropic_providers import (
     AsyncAnthropicBedrock,
     AsyncAnthropicVertex,
 )
+from .anthropic_converter import (
+    format_anthropic_response,
+    format_anthropic_input,
+    extract_anthropic_tools,
+    format_anthropic_streaming_content,
+)
 
 __all__ = [
     "Anthropic",
@@ -14,4 +20,8 @@ __all__ = [
     "AsyncAnthropicBedrock",
     "AnthropicVertex",
     "AsyncAnthropicVertex",
+    "format_anthropic_response",
+    "format_anthropic_input",
+    "extract_anthropic_tools",
+    "format_anthropic_streaming_content",
 ]

posthog/ai/anthropic/anthropic.py

@@ -8,15 +8,23 @@ except ImportError:
 
 import time
 import uuid
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
 
+from posthog.ai.types import StreamingContentBlock, TokenUsage, ToolInProgress
 from posthog.ai.utils import (
     call_llm_and_track_usage,
-    get_model_params,
-    merge_system_prompt,
-    with_privacy_mode,
+    merge_usage_stats,
 )
+from posthog.ai.anthropic.anthropic_converter import (
+    extract_anthropic_usage_from_event,
+    handle_anthropic_content_block_start,
+    handle_anthropic_text_delta,
+    handle_anthropic_tool_delta,
+    finalize_anthropic_tool_input,
+)
+from posthog.ai.sanitization import sanitize_anthropic
 from posthog.client import Client as PostHogClient
+from posthog import setup
 
 
 class Anthropic(anthropic.Anthropic):
@@ -26,14 +34,14 @@ class Anthropic(anthropic.Anthropic):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             posthog_client: PostHog client for tracking usage
             **kwargs: Additional arguments passed to the Anthropic client
         """
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = WrappedMessages(self)
 
 
@@ -60,6 +68,7 @@ class WrappedMessages(Messages):
             posthog_groups: Optional group analytics properties
             **kwargs: Arguments passed to Anthropic's messages.create
         """
+
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
@@ -117,35 +126,66 @@ class WrappedMessages(Messages):
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
-        accumulated_content = []
+        usage_stats: TokenUsage = TokenUsage(input_tokens=0, output_tokens=0)
+        accumulated_content = ""
+        content_blocks: List[StreamingContentBlock] = []
+        tools_in_progress: Dict[str, ToolInProgress] = {}
+        current_text_block: Optional[StreamingContentBlock] = None
         response = super().create(**kwargs)
 
         def generator():
             nonlocal usage_stats
-            nonlocal accumulated_content  # noqa: F824
+            nonlocal accumulated_content
+            nonlocal content_blocks
+            nonlocal tools_in_progress
+            nonlocal current_text_block
+
             try:
                 for event in response:
-                    if hasattr(event, "usage") and event.usage:
-                        usage_stats = {
-                            k: getattr(event.usage, k, 0)
-                            for k in [
-                                "input_tokens",
-                                "output_tokens",
-                                "cache_read_input_tokens",
-                                "cache_creation_input_tokens",
-                            ]
-                        }
+                    # Extract usage stats from event
+                    event_usage = extract_anthropic_usage_from_event(event)
+                    merge_usage_stats(usage_stats, event_usage)
 
-                    if hasattr(event, "content") and event.content:
-                        accumulated_content.append(event.content)
+                    # Handle content block start events
+                    if hasattr(event, "type") and event.type == "content_block_start":
+                        block, tool = handle_anthropic_content_block_start(event)
+
+                        if block:
+                            content_blocks.append(block)
+
+                            if block.get("type") == "text":
+                                current_text_block = block
+                            else:
+                                current_text_block = None
+
+                        if tool:
+                            tool_id = tool["block"].get("id")
+                            if tool_id:
+                                tools_in_progress[tool_id] = tool
+
+                    # Handle text delta events
+                    delta_text = handle_anthropic_text_delta(event, current_text_block)
+
+                    if delta_text:
+                        accumulated_content += delta_text
+
+                    # Handle tool input delta events
+                    handle_anthropic_tool_delta(
+                        event, content_blocks, tools_in_progress
+                    )
+
+                    # Handle content block stop events
+                    if hasattr(event, "type") and event.type == "content_block_stop":
+                        current_text_block = None
+                        finalize_anthropic_tool_input(
+                            event, content_blocks, tools_in_progress
+                        )
 
                     yield event
 
             finally:
                 end_time = time.time()
                 latency = end_time - start_time
-                output = "".join(accumulated_content)
 
                 self._capture_streaming_event(
                     posthog_distinct_id,
@@ -156,7 +196,8 @@ class WrappedMessages(Messages):
                     kwargs,
                     usage_stats,
                     latency,
-                    output,
+                    content_blocks,
+                    accumulated_content,
                 )
 
         return generator()
@@ -169,49 +210,39 @@ class WrappedMessages(Messages):
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
-        output: str,
+        content_blocks: List[StreamingContentBlock],
+        accumulated_content: str,
     ):
-        if posthog_trace_id is None:
-            posthog_trace_id = str(uuid.uuid4())
+        from posthog.ai.types import StreamingEventData
+        from posthog.ai.anthropic.anthropic_converter import (
+            format_anthropic_streaming_input,
+            format_anthropic_streaming_output_complete,
+        )
+        from posthog.ai.utils import capture_streaming_event
 
-        event_properties = {
-            "$ai_provider": "anthropic",
-            "$ai_model": kwargs.get("model"),
-            "$ai_model_parameters": get_model_params(kwargs),
-            "$ai_input": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                merge_system_prompt(kwargs, "anthropic"),
-            ),
-            "$ai_output_choices": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                [{"content": output, "role": "assistant"}],
-            ),
-            "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("output_tokens", 0),
-            "$ai_cache_read_input_tokens": usage_stats.get(
-                "cache_read_input_tokens", 0
-            ),
-            "$ai_cache_creation_input_tokens": usage_stats.get(
-                "cache_creation_input_tokens", 0
-            ),
-            "$ai_latency": latency,
-            "$ai_trace_id": posthog_trace_id,
-            "$ai_base_url": str(self._client.base_url),
-            **(posthog_properties or {}),
-        }
+        # Prepare standardized event data
+        formatted_input = format_anthropic_streaming_input(kwargs)
+        sanitized_input = sanitize_anthropic(formatted_input)
 
-        if posthog_distinct_id is None:
-            event_properties["$process_person_profile"] = False
+        event_data = StreamingEventData(
+            provider="anthropic",
+            model=kwargs.get("model", "unknown"),
+            base_url=str(self._client.base_url),
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_anthropic_streaming_output_complete(
+                content_blocks, accumulated_content
+            ),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=posthog_distinct_id,
+            trace_id=posthog_trace_id,
+            properties=posthog_properties,
+            privacy_mode=posthog_privacy_mode,
+            groups=posthog_groups,
+        )
 
-        if hasattr(self._client._ph_client, "capture"):
-            self._client._ph_client.capture(
-                distinct_id=posthog_distinct_id or posthog_trace_id,
-                event="$ai_generation",
-                properties=event_properties,
-                groups=posthog_groups,
-            )
+        # Use the common capture function
+        capture_streaming_event(self._client._ph_client, event_data)

posthog/ai/anthropic/anthropic_async.py

@@ -8,14 +8,22 @@ except ImportError:
 
 import time
 import uuid
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
 
+from posthog import setup
+from posthog.ai.types import StreamingContentBlock, TokenUsage, ToolInProgress
 from posthog.ai.utils import (
     call_llm_and_track_usage_async,
-    get_model_params,
-    merge_system_prompt,
-    with_privacy_mode,
+    merge_usage_stats,
 )
+from posthog.ai.anthropic.anthropic_converter import (
+    extract_anthropic_usage_from_event,
+    handle_anthropic_content_block_start,
+    handle_anthropic_text_delta,
+    handle_anthropic_tool_delta,
+    finalize_anthropic_tool_input,
+)
+from posthog.ai.sanitization import sanitize_anthropic
 from posthog.client import Client as PostHogClient
 
 
@@ -26,14 +34,14 @@ class AsyncAnthropic(anthropic.AsyncAnthropic):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             posthog_client: PostHog client for tracking usage
             **kwargs: Additional arguments passed to the Anthropic client
         """
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = AsyncWrappedMessages(self)
 
 
@@ -60,6 +68,7 @@ class AsyncWrappedMessages(AsyncMessages):
             posthog_groups: Optional group analytics properties
             **kwargs: Arguments passed to Anthropic's messages.create
         """
+
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
@@ -117,35 +126,66 @@ class AsyncWrappedMessages(AsyncMessages):
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
-        accumulated_content = []
+        usage_stats: TokenUsage = TokenUsage(input_tokens=0, output_tokens=0)
+        accumulated_content = ""
+        content_blocks: List[StreamingContentBlock] = []
+        tools_in_progress: Dict[str, ToolInProgress] = {}
+        current_text_block: Optional[StreamingContentBlock] = None
         response = await super().create(**kwargs)
 
         async def generator():
             nonlocal usage_stats
-            nonlocal accumulated_content  # noqa: F824
+            nonlocal accumulated_content
+            nonlocal content_blocks
+            nonlocal tools_in_progress
+            nonlocal current_text_block
+
             try:
                 async for event in response:
-                    if hasattr(event, "usage") and event.usage:
-                        usage_stats = {
-                            k: getattr(event.usage, k, 0)
-                            for k in [
-                                "input_tokens",
-                                "output_tokens",
-                                "cache_read_input_tokens",
-                                "cache_creation_input_tokens",
-                            ]
-                        }
+                    # Extract usage stats from event
+                    event_usage = extract_anthropic_usage_from_event(event)
+                    merge_usage_stats(usage_stats, event_usage)
 
-                    if hasattr(event, "content") and event.content:
-                        accumulated_content.append(event.content)
+                    # Handle content block start events
+                    if hasattr(event, "type") and event.type == "content_block_start":
+                        block, tool = handle_anthropic_content_block_start(event)
+
+                        if block:
+                            content_blocks.append(block)
+
+                            if block.get("type") == "text":
+                                current_text_block = block
+                            else:
+                                current_text_block = None
+
+                        if tool:
+                            tool_id = tool["block"].get("id")
+                            if tool_id:
+                                tools_in_progress[tool_id] = tool
+
+                    # Handle text delta events
+                    delta_text = handle_anthropic_text_delta(event, current_text_block)
+
+                    if delta_text:
+                        accumulated_content += delta_text
+
+                    # Handle tool input delta events
+                    handle_anthropic_tool_delta(
+                        event, content_blocks, tools_in_progress
+                    )
+
+                    # Handle content block stop events
+                    if hasattr(event, "type") and event.type == "content_block_stop":
+                        current_text_block = None
+                        finalize_anthropic_tool_input(
+                            event, content_blocks, tools_in_progress
+                        )
 
                     yield event
 
             finally:
                 end_time = time.time()
                 latency = end_time - start_time
-                output = "".join(accumulated_content)
 
                 await self._capture_streaming_event(
                     posthog_distinct_id,
@@ -156,7 +196,8 @@ class AsyncWrappedMessages(AsyncMessages):
                     kwargs,
                     usage_stats,
                     latency,
-                    output,
+                    content_blocks,
+                    accumulated_content,
                 )
 
         return generator()
@@ -169,49 +210,39 @@ class AsyncWrappedMessages(AsyncMessages):
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
-        output: str,
+        content_blocks: List[StreamingContentBlock],
+        accumulated_content: str,
     ):
-        if posthog_trace_id is None:
-            posthog_trace_id = str(uuid.uuid4())
+        from posthog.ai.types import StreamingEventData
+        from posthog.ai.anthropic.anthropic_converter import (
+            format_anthropic_streaming_input,
+            format_anthropic_streaming_output_complete,
+        )
+        from posthog.ai.utils import capture_streaming_event
 
-        event_properties = {
-            "$ai_provider": "anthropic",
-            "$ai_model": kwargs.get("model"),
-            "$ai_model_parameters": get_model_params(kwargs),
-            "$ai_input": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                merge_system_prompt(kwargs, "anthropic"),
-            ),
-            "$ai_output_choices": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                [{"content": output, "role": "assistant"}],
-            ),
-            "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("output_tokens", 0),
-            "$ai_cache_read_input_tokens": usage_stats.get(
-                "cache_read_input_tokens", 0
-            ),
-            "$ai_cache_creation_input_tokens": usage_stats.get(
-                "cache_creation_input_tokens", 0
-            ),
-            "$ai_latency": latency,
-            "$ai_trace_id": posthog_trace_id,
-            "$ai_base_url": str(self._client.base_url),
-            **(posthog_properties or {}),
-        }
+        # Prepare standardized event data
+        formatted_input = format_anthropic_streaming_input(kwargs)
+        sanitized_input = sanitize_anthropic(formatted_input)
 
-        if posthog_distinct_id is None:
-            event_properties["$process_person_profile"] = False
+        event_data = StreamingEventData(
+            provider="anthropic",
+            model=kwargs.get("model", "unknown"),
+            base_url=str(self._client.base_url),
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_anthropic_streaming_output_complete(
+                content_blocks, accumulated_content
+            ),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=posthog_distinct_id,
+            trace_id=posthog_trace_id,
+            properties=posthog_properties,
+            privacy_mode=posthog_privacy_mode,
+            groups=posthog_groups,
+        )
 
-        if hasattr(self._client._ph_client, "capture"):
-            self._client._ph_client.capture(
-                distinct_id=posthog_distinct_id or posthog_trace_id,
-                event="$ai_generation",
-                properties=event_properties,
-                groups=posthog_groups,
-            )
+        # Use the common capture function
+        capture_streaming_event(self._client._ph_client, event_data)

posthog/ai/anthropic/anthropic_converter.py

@@ -0,0 +1,461 @@
+"""
+Anthropic-specific conversion utilities.
+
+This module handles the conversion of Anthropic API responses and inputs
+into standardized formats for PostHog tracking.
+"""
+
+import json
+from typing import Any, Dict, List, Optional, Tuple
+
+from posthog.ai.types import (
+    FormattedContentItem,
+    FormattedFunctionCall,
+    FormattedMessage,
+    FormattedTextContent,
+    StreamingContentBlock,
+    TokenUsage,
+    ToolInProgress,
+)
+from posthog.ai.utils import serialize_raw_usage
+
+
+def format_anthropic_response(response: Any) -> List[FormattedMessage]:
+    """
+    Format an Anthropic response into standardized message format.
+
+    Args:
+        response: The response object from Anthropic API
+
+    Returns:
+        List of formatted messages with role and content
+    """
+
+    output: List[FormattedMessage] = []
+
+    if response is None:
+        return output
+
+    content: List[FormattedContentItem] = []
+
+    # Process content blocks from the response
+    if hasattr(response, "content"):
+        for choice in response.content:
+            if (
+                hasattr(choice, "type")
+                and choice.type == "text"
+                and hasattr(choice, "text")
+                and choice.text
+            ):
+                text_content: FormattedTextContent = {
+                    "type": "text",
+                    "text": choice.text,
+                }
+                content.append(text_content)
+
+            elif (
+                hasattr(choice, "type")
+                and choice.type == "tool_use"
+                and hasattr(choice, "name")
+                and hasattr(choice, "id")
+            ):
+                function_call: FormattedFunctionCall = {
+                    "type": "function",
+                    "id": choice.id,
+                    "function": {
+                        "name": choice.name,
+                        "arguments": getattr(choice, "input", {}),
+                    },
+                }
+                content.append(function_call)
+
+    if content:
+        message: FormattedMessage = {
+            "role": "assistant",
+            "content": content,
+        }
+        output.append(message)
+
+    return output
+
+
+def format_anthropic_input(
+    messages: List[Dict[str, Any]], system: Optional[str] = None
+) -> List[FormattedMessage]:
+    """
+    Format Anthropic input messages with optional system prompt.
+
+    Args:
+        messages: List of message dictionaries
+        system: Optional system prompt to prepend
+
+    Returns:
+        List of formatted messages
+    """
+
+    formatted_messages: List[FormattedMessage] = []
+
+    # Add system message if provided
+    if system is not None:
+        formatted_messages.append({"role": "system", "content": system})
+
+    # Add user messages
+    if messages:
+        for msg in messages:
+            # Messages are already in the correct format, just ensure type safety
+            formatted_msg: FormattedMessage = {
+                "role": msg.get("role", "user"),
+                "content": msg.get("content", ""),
+            }
+            formatted_messages.append(formatted_msg)
+
+    return formatted_messages
+
+
+def extract_anthropic_tools(kwargs: Dict[str, Any]) -> Optional[Any]:
+    """
+    Extract tool definitions from Anthropic API kwargs.
+
+    Args:
+        kwargs: Keyword arguments passed to Anthropic API
+
+    Returns:
+        Tool definitions if present, None otherwise
+    """
+
+    return kwargs.get("tools", None)
+
+
+def format_anthropic_streaming_content(
+    content_blocks: List[StreamingContentBlock],
+) -> List[FormattedContentItem]:
+    """
+    Format content blocks from Anthropic streaming response.
+
+    Used by streaming handlers to format accumulated content blocks.
+
+    Args:
+        content_blocks: List of content block dictionaries from streaming
+
+    Returns:
+        List of formatted content items
+    """
+
+    formatted: List[FormattedContentItem] = []
+
+    for block in content_blocks:
+        if block.get("type") == "text":
+            formatted.append(
+                {
+                    "type": "text",
+                    "text": block.get("text") or "",
+                }
+            )
+
+        elif block.get("type") == "function":
+            formatted.append(
+                {
+                    "type": "function",
+                    "id": block.get("id"),
+                    "function": block.get("function") or {},
+                }
+            )
+
+    return formatted
+
+
+def extract_anthropic_web_search_count(response: Any) -> int:
+    """
+    Extract web search count from Anthropic response.
+
+    Anthropic provides exact web search counts via usage.server_tool_use.web_search_requests.
+
+    Args:
+        response: The response from Anthropic API
+
+    Returns:
+        Number of web search requests (0 if none)
+    """
+    if not hasattr(response, "usage"):
+        return 0
+
+    if not hasattr(response.usage, "server_tool_use"):
+        return 0
+
+    server_tool_use = response.usage.server_tool_use
+
+    if hasattr(server_tool_use, "web_search_requests"):
+        return max(0, int(getattr(server_tool_use, "web_search_requests", 0)))
+
+    return 0
+
+
+def extract_anthropic_usage_from_response(response: Any) -> TokenUsage:
+    """
+    Extract usage from a full Anthropic response (non-streaming).
+
+    Args:
+        response: The complete response from Anthropic API
+
+    Returns:
+        TokenUsage with standardized usage
+    """
+    if not hasattr(response, "usage"):
+        return TokenUsage(input_tokens=0, output_tokens=0)
+
+    result = TokenUsage(
+        input_tokens=getattr(response.usage, "input_tokens", 0),
+        output_tokens=getattr(response.usage, "output_tokens", 0),
+    )
+
+    if hasattr(response.usage, "cache_read_input_tokens"):
+        cache_read = response.usage.cache_read_input_tokens
+        if cache_read and cache_read > 0:
+            result["cache_read_input_tokens"] = cache_read
+
+    if hasattr(response.usage, "cache_creation_input_tokens"):
+        cache_creation = response.usage.cache_creation_input_tokens
+        if cache_creation and cache_creation > 0:
+            result["cache_creation_input_tokens"] = cache_creation
+
+    web_search_count = extract_anthropic_web_search_count(response)
+    if web_search_count > 0:
+        result["web_search_count"] = web_search_count
+
+    # Capture raw usage metadata for backend processing
+    # Serialize to dict here in the converter (not in utils)
+    serialized = serialize_raw_usage(response.usage)
+    if serialized:
+        result["raw_usage"] = serialized
+
+    return result
+
+
+def extract_anthropic_usage_from_event(event: Any) -> TokenUsage:
+    """
+    Extract usage statistics from an Anthropic streaming event.
+
+    Args:
+        event: Streaming event from Anthropic API
+
+    Returns:
+        Dictionary of usage statistics
+    """
+
+    usage: TokenUsage = TokenUsage()
+
+    # Handle usage stats from message_start event
+    if hasattr(event, "type") and event.type == "message_start":
+        if hasattr(event, "message") and hasattr(event.message, "usage"):
+            usage["input_tokens"] = getattr(event.message.usage, "input_tokens", 0)
+            usage["cache_creation_input_tokens"] = getattr(
+                event.message.usage, "cache_creation_input_tokens", 0
+            )
+            usage["cache_read_input_tokens"] = getattr(
+                event.message.usage, "cache_read_input_tokens", 0
+            )
+            # Capture raw usage metadata for backend processing
+            # Serialize to dict here in the converter (not in utils)
+            serialized = serialize_raw_usage(event.message.usage)
+            if serialized:
+                usage["raw_usage"] = serialized
+
+    # Handle usage stats from message_delta event
+    if hasattr(event, "usage") and event.usage:
+        usage["output_tokens"] = getattr(event.usage, "output_tokens", 0)
+
+        # Extract web search count from usage
+        if hasattr(event.usage, "server_tool_use"):
+            server_tool_use = event.usage.server_tool_use
+            if hasattr(server_tool_use, "web_search_requests"):
+                web_search_count = int(
+                    getattr(server_tool_use, "web_search_requests", 0)
+                )
+                if web_search_count > 0:
+                    usage["web_search_count"] = web_search_count
+
+        # Capture raw usage metadata for backend processing
+        # Serialize to dict here in the converter (not in utils)
+        serialized = serialize_raw_usage(event.usage)
+        if serialized:
+            usage["raw_usage"] = serialized
+
+    return usage
+
+
+def handle_anthropic_content_block_start(
+    event: Any,
+) -> Tuple[Optional[StreamingContentBlock], Optional[ToolInProgress]]:
+    """
+    Handle content block start event from Anthropic streaming.
+
+    Args:
+        event: Content block start event
+
+    Returns:
+        Tuple of (content_block, tool_in_progress)
+    """
+
+    if not (hasattr(event, "type") and event.type == "content_block_start"):
+        return None, None
+
+    if not hasattr(event, "content_block"):
+        return None, None
+
+    block = event.content_block
+
+    if not hasattr(block, "type"):
+        return None, None
+
+    if block.type == "text":
+        content_block: StreamingContentBlock = {"type": "text", "text": ""}
+        return content_block, None
+
+    elif block.type == "tool_use":
+        tool_block: StreamingContentBlock = {
+            "type": "function",
+            "id": getattr(block, "id", ""),
+            "function": {"name": getattr(block, "name", ""), "arguments": {}},
+        }
+        tool_in_progress: ToolInProgress = {"block": tool_block, "input_string": ""}
+        return tool_block, tool_in_progress
+
+    return None, None
+
+
+def handle_anthropic_text_delta(
+    event: Any, current_block: Optional[StreamingContentBlock]
+) -> Optional[str]:
+    """
+    Handle text delta event from Anthropic streaming.
+
+    Args:
+        event: Delta event
+        current_block: Current text block being accumulated
+
+    Returns:
+        Text delta if present
+    """
+
+    if hasattr(event, "delta") and hasattr(event.delta, "text"):
+        delta_text = event.delta.text or ""
+
+        if current_block is not None and current_block.get("type") == "text":
+            text_val = current_block.get("text")
+            if text_val is not None:
+                current_block["text"] = text_val + delta_text
+            else:
+                current_block["text"] = delta_text
+
+        return delta_text
+
+    return None
+
+
+def handle_anthropic_tool_delta(
+    event: Any,
+    content_blocks: List[StreamingContentBlock],
+    tools_in_progress: Dict[str, ToolInProgress],
+) -> None:
+    """
+    Handle tool input delta event from Anthropic streaming.
+
+    Args:
+        event: Tool delta event
+        content_blocks: List of content blocks
+        tools_in_progress: Dictionary tracking tools being accumulated
+    """
+
+    if not (hasattr(event, "type") and event.type == "content_block_delta"):
+        return
+
+    if not (
+        hasattr(event, "delta")
+        and hasattr(event.delta, "type")
+        and event.delta.type == "input_json_delta"
+    ):
+        return
+
+    if hasattr(event, "index") and event.index < len(content_blocks):
+        block = content_blocks[event.index]
+
+        if block.get("type") == "function" and block.get("id") in tools_in_progress:
+            tool = tools_in_progress[block["id"]]
+            partial_json = getattr(event.delta, "partial_json", "")
+            tool["input_string"] += partial_json
+
+
+def finalize_anthropic_tool_input(
+    event: Any,
+    content_blocks: List[StreamingContentBlock],
+    tools_in_progress: Dict[str, ToolInProgress],
+) -> None:
+    """
+    Finalize tool input when content block stops.
+
+    Args:
+        event: Content block stop event
+        content_blocks: List of content blocks
+        tools_in_progress: Dictionary tracking tools being accumulated
+    """
+
+    if not (hasattr(event, "type") and event.type == "content_block_stop"):
+        return
+
+    if hasattr(event, "index") and event.index < len(content_blocks):
+        block = content_blocks[event.index]
+
+        if block.get("type") == "function" and block.get("id") in tools_in_progress:
+            tool = tools_in_progress[block["id"]]
+
+            try:
+                block["function"]["arguments"] = json.loads(tool["input_string"])
+            except (json.JSONDecodeError, Exception):
+                # Keep empty dict if parsing fails
+                pass
+
+            del tools_in_progress[block["id"]]
+
+
+def format_anthropic_streaming_input(kwargs: Dict[str, Any]) -> Any:
+    """
+    Format Anthropic streaming input using system prompt merging.
+
+    Args:
+        kwargs: Keyword arguments passed to Anthropic API
+
+    Returns:
+        Formatted input ready for PostHog tracking
+    """
+    from posthog.ai.utils import merge_system_prompt
+
+    return merge_system_prompt(kwargs, "anthropic")
+
+
+def format_anthropic_streaming_output_complete(
+    content_blocks: List[StreamingContentBlock], accumulated_content: str
+) -> List[FormattedMessage]:
+    """
+    Format complete Anthropic streaming output.
+
+    Combines existing logic for formatting content blocks with fallback to accumulated content.
+
+    Args:
+        content_blocks: List of content blocks accumulated during streaming
+        accumulated_content: Raw accumulated text content as fallback
+
+    Returns:
+        Formatted messages ready for PostHog tracking
+    """
+    formatted_content = format_anthropic_streaming_content(content_blocks)
+
+    if formatted_content:
+        return [{"role": "assistant", "content": formatted_content}]
+    else:
+        # Fallback to accumulated content if no blocks
+        return [
+            {
+                "role": "assistant",
+                "content": [{"type": "text", "text": accumulated_content}],
+            }
+        ]

posthog/ai/anthropic/anthropic_providers.py

@@ -5,9 +5,12 @@ except ImportError:
         "Please install the Anthropic SDK to use this feature: 'pip install anthropic'"
     )
 
+from typing import Optional
+
 from posthog.ai.anthropic.anthropic import WrappedMessages
 from posthog.ai.anthropic.anthropic_async import AsyncWrappedMessages
 from posthog.client import Client as PostHogClient
+from posthog import setup
 
 
 class AnthropicBedrock(anthropic.AnthropicBedrock):
@@ -17,9 +20,9 @@ class AnthropicBedrock(anthropic.AnthropicBedrock):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = WrappedMessages(self)
 
 
@@ -30,9 +33,9 @@ class AsyncAnthropicBedrock(anthropic.AsyncAnthropicBedrock):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = AsyncWrappedMessages(self)
 
 
@@ -43,9 +46,9 @@ class AnthropicVertex(anthropic.AnthropicVertex):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = WrappedMessages(self)
 
 
@@ -56,7 +59,7 @@ class AsyncAnthropicVertex(anthropic.AsyncAnthropicVertex):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
         self.messages = AsyncWrappedMessages(self)

posthog/ai/gemini/__init__.py

@@ -1,11 +1,25 @@
 from .gemini import Client
+from .gemini_async import AsyncClient
+from .gemini_converter import (
+    format_gemini_input,
+    format_gemini_response,
+    extract_gemini_tools,
+)
 
 
 # Create a genai-like module for perfect drop-in replacement
 class _GenAI:
     Client = Client
+    AsyncClient = AsyncClient
 
 
 genai = _GenAI()
 
-__all__ = ["Client", "genai"]
+__all__ = [
+    "Client",
+    "AsyncClient",
+    "genai",
+    "format_gemini_input",
+    "format_gemini_response",
+    "extract_gemini_tools",
+]

posthog/ai/gemini/gemini.py

@@ -3,6 +3,9 @@ import time
 import uuid
 from typing import Any, Dict, Optional
 
+from posthog.ai.types import TokenUsage, StreamingEventData
+from posthog.ai.utils import merge_system_prompt
+
 try:
     from google import genai
 except ImportError:
@@ -10,11 +13,18 @@ except ImportError:
         "Please install the Google Gemini SDK to use this feature: 'pip install google-genai'"
     )
 
+from posthog import setup
 from posthog.ai.utils import (
     call_llm_and_track_usage,
-    get_model_params,
-    with_privacy_mode,
+    capture_streaming_event,
+    merge_usage_stats,
 )
+from posthog.ai.gemini.gemini_converter import (
+    extract_gemini_usage_from_chunk,
+    extract_gemini_content_from_chunk,
+    format_gemini_streaming_output,
+)
+from posthog.ai.sanitization import sanitize_gemini
 from posthog.client import Client as PostHogClient
 
 
@@ -36,9 +46,17 @@ class Client:
         )
     """
 
+    _ph_client: PostHogClient
+
     def __init__(
         self,
         api_key: Optional[str] = None,
+        vertexai: Optional[bool] = None,
+        credentials: Optional[Any] = None,
+        project: Optional[str] = None,
+        location: Optional[str] = None,
+        debug_config: Optional[Any] = None,
+        http_options: Optional[Any] = None,
         posthog_client: Optional[PostHogClient] = None,
         posthog_distinct_id: Optional[str] = None,
         posthog_properties: Optional[Dict[str, Any]] = None,
@@ -48,7 +66,13 @@ class Client:
     ):
         """
         Args:
-            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable
+            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable (not required for Vertex AI)
+            vertexai: Whether to use Vertex AI authentication
+            credentials: Vertex AI credentials object
+            project: GCP project ID for Vertex AI
+            location: GCP location for Vertex AI
+            debug_config: Debug configuration for the client
+            http_options: HTTP options for the client
             posthog_client: PostHog client for tracking usage
             posthog_distinct_id: Default distinct ID for all calls (can be overridden per call)
             posthog_properties: Default properties for all calls (can be overridden per call)
@@ -56,12 +80,21 @@ class Client:
             posthog_groups: Default groups for all calls (can be overridden per call)
             **kwargs: Additional arguments (for future compatibility)
         """
-        if posthog_client is None:
+
+        self._ph_client = posthog_client or setup()
+
+        if self._ph_client is None:
             raise ValueError("posthog_client is required for PostHog tracking")
 
         self.models = Models(
             api_key=api_key,
-            posthog_client=posthog_client,
+            vertexai=vertexai,
+            credentials=credentials,
+            project=project,
+            location=location,
+            debug_config=debug_config,
+            http_options=http_options,
+            posthog_client=self._ph_client,
             posthog_distinct_id=posthog_distinct_id,
             posthog_properties=posthog_properties,
             posthog_privacy_mode=posthog_privacy_mode,
@@ -80,6 +113,12 @@ class Models:
     def __init__(
         self,
         api_key: Optional[str] = None,
+        vertexai: Optional[bool] = None,
+        credentials: Optional[Any] = None,
+        project: Optional[str] = None,
+        location: Optional[str] = None,
+        debug_config: Optional[Any] = None,
+        http_options: Optional[Any] = None,
         posthog_client: Optional[PostHogClient] = None,
         posthog_distinct_id: Optional[str] = None,
         posthog_properties: Optional[Dict[str, Any]] = None,
@@ -89,7 +128,13 @@ class Models:
     ):
         """
         Args:
-            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable
+            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable (not required for Vertex AI)
+            vertexai: Whether to use Vertex AI authentication
+            credentials: Vertex AI credentials object
+            project: GCP project ID for Vertex AI
+            location: GCP location for Vertex AI
+            debug_config: Debug configuration for the client
+            http_options: HTTP options for the client
             posthog_client: PostHog client for tracking usage
             posthog_distinct_id: Default distinct ID for all calls
             posthog_properties: Default properties for all calls
@@ -97,10 +142,11 @@ class Models:
             posthog_groups: Default groups for all calls
             **kwargs: Additional arguments (for future compatibility)
         """
-        if posthog_client is None:
-            raise ValueError("posthog_client is required for PostHog tracking")
 
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
+
+        if self._ph_client is None:
+            raise ValueError("posthog_client is required for PostHog tracking")
 
         # Store default PostHog settings
         self._default_distinct_id = posthog_distinct_id
@@ -108,16 +154,46 @@ class Models:
         self._default_privacy_mode = posthog_privacy_mode
         self._default_groups = posthog_groups
 
-        # Handle API key - try parameter first, then environment variables
-        if api_key is None:
-            api_key = os.environ.get("GOOGLE_API_KEY") or os.environ.get("API_KEY")
+        # Build genai.Client arguments
+        client_args: Dict[str, Any] = {}
 
-        if api_key is None:
-            raise ValueError(
-                "API key must be provided either as parameter or via GOOGLE_API_KEY/API_KEY environment variable"
-            )
+        # Add Vertex AI parameters if provided
+        if vertexai is not None:
+            client_args["vertexai"] = vertexai
 
-        self._client = genai.Client(api_key=api_key)
+        if credentials is not None:
+            client_args["credentials"] = credentials
+
+        if project is not None:
+            client_args["project"] = project
+
+        if location is not None:
+            client_args["location"] = location
+
+        if debug_config is not None:
+            client_args["debug_config"] = debug_config
+
+        if http_options is not None:
+            client_args["http_options"] = http_options
+
+        # Handle API key authentication
+        if vertexai:
+            # For Vertex AI, api_key is optional
+            if api_key is not None:
+                client_args["api_key"] = api_key
+        else:
+            # For non-Vertex AI mode, api_key is required (backwards compatibility)
+            if api_key is None:
+                api_key = os.environ.get("GOOGLE_API_KEY") or os.environ.get("API_KEY")
+
+            if api_key is None:
+                raise ValueError(
+                    "API key must be provided either as parameter or via GOOGLE_API_KEY/API_KEY environment variable"
+                )
+
+            client_args["api_key"] = api_key
+
+        self._client = genai.Client(**client_args)
         self._base_url = "https://generativelanguage.googleapis.com"
 
     def _merge_posthog_params(
@@ -129,6 +205,7 @@ class Models:
         call_groups: Optional[Dict[str, Any]],
     ):
         """Merge call-level PostHog parameters with client defaults."""
+
         # Use call-level values if provided, otherwise fall back to defaults
         distinct_id = (
             call_distinct_id
@@ -144,6 +221,7 @@ class Models:
 
         # Merge properties: default properties + call properties (call properties override)
         properties = dict(self._default_properties)
+
         if call_properties:
             properties.update(call_properties)
 
@@ -179,6 +257,7 @@ class Models:
             posthog_groups: Group analytics properties (overrides client default)
             **kwargs: Arguments passed to Gemini's generate_content
         """
+
         # Merge PostHog parameters
         distinct_id, trace_id, properties, privacy_mode, groups = (
             self._merge_posthog_params(
@@ -217,7 +296,7 @@ class Models:
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
+        usage_stats: TokenUsage = TokenUsage(input_tokens=0, output_tokens=0)
         accumulated_content = []
 
         kwargs_without_stream = {"model": model, "contents": contents, **kwargs}
@@ -225,28 +304,27 @@ class Models:
 
         def generator():
             nonlocal usage_stats
-            nonlocal accumulated_content  # noqa: F824
+            nonlocal accumulated_content
             try:
                 for chunk in response:
-                    if hasattr(chunk, "usage_metadata") and chunk.usage_metadata:
-                        usage_stats = {
-                            "input_tokens": getattr(
-                                chunk.usage_metadata, "prompt_token_count", 0
-                            ),
-                            "output_tokens": getattr(
-                                chunk.usage_metadata, "candidates_token_count", 0
-                            ),
-                        }
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_gemini_usage_from_chunk(chunk)
 
-                    if hasattr(chunk, "text") and chunk.text:
-                        accumulated_content.append(chunk.text)
+                    if chunk_usage:
+                        # Gemini reports cumulative totals, not incremental values
+                        merge_usage_stats(usage_stats, chunk_usage, mode="cumulative")
+
+                    # Extract content from chunk (now returns content blocks)
+                    content_block = extract_gemini_content_from_chunk(chunk)
+
+                    if content_block is not None:
+                        accumulated_content.append(content_block)
 
                     yield chunk
 
             finally:
                 end_time = time.time()
                 latency = end_time - start_time
-                output = "".join(accumulated_content)
 
                 self._capture_streaming_event(
                     model,
@@ -259,7 +337,7 @@ class Models:
                     kwargs,
                     usage_stats,
                     latency,
-                    output,
+                    accumulated_content,
                 )
 
         return generator()
@@ -274,63 +352,39 @@ class Models:
         privacy_mode: bool,
         groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
-        output: str,
+        output: Any,
     ):
-        if trace_id is None:
-            trace_id = str(uuid.uuid4())
+        # Prepare standardized event data
+        formatted_input = self._format_input(contents, **kwargs)
+        sanitized_input = sanitize_gemini(formatted_input)
 
-        event_properties = {
-            "$ai_provider": "gemini",
-            "$ai_model": model,
-            "$ai_model_parameters": get_model_params(kwargs),
-            "$ai_input": with_privacy_mode(
-                self._ph_client,
-                privacy_mode,
-                self._format_input(contents),
-            ),
-            "$ai_output_choices": with_privacy_mode(
-                self._ph_client,
-                privacy_mode,
-                [{"content": output, "role": "assistant"}],
-            ),
-            "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("output_tokens", 0),
-            "$ai_latency": latency,
-            "$ai_trace_id": trace_id,
-            "$ai_base_url": self._base_url,
-            **(properties or {}),
-        }
+        event_data = StreamingEventData(
+            provider="gemini",
+            model=model,
+            base_url=self._base_url,
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_gemini_streaming_output(output),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=distinct_id,
+            trace_id=trace_id,
+            properties=properties,
+            privacy_mode=privacy_mode,
+            groups=groups,
+        )
 
-        if distinct_id is None:
-            event_properties["$process_person_profile"] = False
+        # Use the common capture function
+        capture_streaming_event(self._ph_client, event_data)
 
-        if hasattr(self._ph_client, "capture"):
-            self._ph_client.capture(
-                distinct_id=distinct_id,
-                event="$ai_generation",
-                properties=event_properties,
-                groups=groups,
-            )
-
-    def _format_input(self, contents):
+    def _format_input(self, contents, **kwargs):
         """Format input contents for PostHog tracking"""
-        if isinstance(contents, str):
-            return [{"role": "user", "content": contents}]
-        elif isinstance(contents, list):
-            formatted = []
-            for item in contents:
-                if isinstance(item, str):
-                    formatted.append({"role": "user", "content": item})
-                elif hasattr(item, "text"):
-                    formatted.append({"role": "user", "content": item.text})
-                else:
-                    formatted.append({"role": "user", "content": str(item)})
-            return formatted
-        else:
-            return [{"role": "user", "content": str(contents)}]
+
+        # Create kwargs dict with contents for merge_system_prompt
+        input_kwargs = {"contents": contents, **kwargs}
+        return merge_system_prompt(input_kwargs, "gemini")
 
     def generate_content_stream(
         self,

posthog/ai/gemini/gemini_async.py

@@ -0,0 +1,423 @@
+import os
+import time
+import uuid
+from typing import Any, Dict, Optional
+
+from posthog.ai.types import TokenUsage, StreamingEventData
+from posthog.ai.utils import merge_system_prompt
+
+try:
+    from google import genai
+except ImportError:
+    raise ModuleNotFoundError(
+        "Please install the Google Gemini SDK to use this feature: 'pip install google-genai'"
+    )
+
+from posthog import setup
+from posthog.ai.utils import (
+    call_llm_and_track_usage_async,
+    capture_streaming_event,
+    merge_usage_stats,
+)
+from posthog.ai.gemini.gemini_converter import (
+    extract_gemini_usage_from_chunk,
+    extract_gemini_content_from_chunk,
+    format_gemini_streaming_output,
+)
+from posthog.ai.sanitization import sanitize_gemini
+from posthog.client import Client as PostHogClient
+
+
+class AsyncClient:
+    """
+    An async drop-in replacement for genai.Client that automatically sends LLM usage events to PostHog.
+
+    Usage:
+        client = AsyncClient(
+            api_key="your_api_key",
+            posthog_client=posthog_client,
+            posthog_distinct_id="default_user",  # Optional defaults
+            posthog_properties={"team": "ai"}    # Optional defaults
+        )
+        response = await client.models.generate_content(
+            model="gemini-2.0-flash",
+            contents=["Hello world"],
+            posthog_distinct_id="specific_user"  # Override default
+        )
+    """
+
+    _ph_client: PostHogClient
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        vertexai: Optional[bool] = None,
+        credentials: Optional[Any] = None,
+        project: Optional[str] = None,
+        location: Optional[str] = None,
+        debug_config: Optional[Any] = None,
+        http_options: Optional[Any] = None,
+        posthog_client: Optional[PostHogClient] = None,
+        posthog_distinct_id: Optional[str] = None,
+        posthog_properties: Optional[Dict[str, Any]] = None,
+        posthog_privacy_mode: bool = False,
+        posthog_groups: Optional[Dict[str, Any]] = None,
+        **kwargs,
+    ):
+        """
+        Args:
+            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable (not required for Vertex AI)
+            vertexai: Whether to use Vertex AI authentication
+            credentials: Vertex AI credentials object
+            project: GCP project ID for Vertex AI
+            location: GCP location for Vertex AI
+            debug_config: Debug configuration for the client
+            http_options: HTTP options for the client
+            posthog_client: PostHog client for tracking usage
+            posthog_distinct_id: Default distinct ID for all calls (can be overridden per call)
+            posthog_properties: Default properties for all calls (can be overridden per call)
+            posthog_privacy_mode: Default privacy mode for all calls (can be overridden per call)
+            posthog_groups: Default groups for all calls (can be overridden per call)
+            **kwargs: Additional arguments (for future compatibility)
+        """
+
+        self._ph_client = posthog_client or setup()
+
+        if self._ph_client is None:
+            raise ValueError("posthog_client is required for PostHog tracking")
+
+        self.models = AsyncModels(
+            api_key=api_key,
+            vertexai=vertexai,
+            credentials=credentials,
+            project=project,
+            location=location,
+            debug_config=debug_config,
+            http_options=http_options,
+            posthog_client=self._ph_client,
+            posthog_distinct_id=posthog_distinct_id,
+            posthog_properties=posthog_properties,
+            posthog_privacy_mode=posthog_privacy_mode,
+            posthog_groups=posthog_groups,
+            **kwargs,
+        )
+
+
+class AsyncModels:
+    """
+    Async Models interface that mimics genai.Client().aio.models with PostHog tracking.
+    """
+
+    _ph_client: PostHogClient  # Not None after __init__ validation
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        vertexai: Optional[bool] = None,
+        credentials: Optional[Any] = None,
+        project: Optional[str] = None,
+        location: Optional[str] = None,
+        debug_config: Optional[Any] = None,
+        http_options: Optional[Any] = None,
+        posthog_client: Optional[PostHogClient] = None,
+        posthog_distinct_id: Optional[str] = None,
+        posthog_properties: Optional[Dict[str, Any]] = None,
+        posthog_privacy_mode: bool = False,
+        posthog_groups: Optional[Dict[str, Any]] = None,
+        **kwargs,
+    ):
+        """
+        Args:
+            api_key: Google AI API key. If not provided, will use GOOGLE_API_KEY or API_KEY environment variable (not required for Vertex AI)
+            vertexai: Whether to use Vertex AI authentication
+            credentials: Vertex AI credentials object
+            project: GCP project ID for Vertex AI
+            location: GCP location for Vertex AI
+            debug_config: Debug configuration for the client
+            http_options: HTTP options for the client
+            posthog_client: PostHog client for tracking usage
+            posthog_distinct_id: Default distinct ID for all calls
+            posthog_properties: Default properties for all calls
+            posthog_privacy_mode: Default privacy mode for all calls
+            posthog_groups: Default groups for all calls
+            **kwargs: Additional arguments (for future compatibility)
+        """
+
+        self._ph_client = posthog_client or setup()
+
+        if self._ph_client is None:
+            raise ValueError("posthog_client is required for PostHog tracking")
+
+        # Store default PostHog settings
+        self._default_distinct_id = posthog_distinct_id
+        self._default_properties = posthog_properties or {}
+        self._default_privacy_mode = posthog_privacy_mode
+        self._default_groups = posthog_groups
+
+        # Build genai.Client arguments
+        client_args: Dict[str, Any] = {}
+
+        # Add Vertex AI parameters if provided
+        if vertexai is not None:
+            client_args["vertexai"] = vertexai
+
+        if credentials is not None:
+            client_args["credentials"] = credentials
+
+        if project is not None:
+            client_args["project"] = project
+
+        if location is not None:
+            client_args["location"] = location
+
+        if debug_config is not None:
+            client_args["debug_config"] = debug_config
+
+        if http_options is not None:
+            client_args["http_options"] = http_options
+
+        # Handle API key authentication
+        if vertexai:
+            # For Vertex AI, api_key is optional
+            if api_key is not None:
+                client_args["api_key"] = api_key
+        else:
+            # For non-Vertex AI mode, api_key is required (backwards compatibility)
+            if api_key is None:
+                api_key = os.environ.get("GOOGLE_API_KEY") or os.environ.get("API_KEY")
+
+            if api_key is None:
+                raise ValueError(
+                    "API key must be provided either as parameter or via GOOGLE_API_KEY/API_KEY environment variable"
+                )
+
+            client_args["api_key"] = api_key
+
+        self._client = genai.Client(**client_args)
+        self._base_url = "https://generativelanguage.googleapis.com"
+
+    def _merge_posthog_params(
+        self,
+        call_distinct_id: Optional[str],
+        call_trace_id: Optional[str],
+        call_properties: Optional[Dict[str, Any]],
+        call_privacy_mode: Optional[bool],
+        call_groups: Optional[Dict[str, Any]],
+    ):
+        """Merge call-level PostHog parameters with client defaults."""
+
+        # Use call-level values if provided, otherwise fall back to defaults
+        distinct_id = (
+            call_distinct_id
+            if call_distinct_id is not None
+            else self._default_distinct_id
+        )
+        privacy_mode = (
+            call_privacy_mode
+            if call_privacy_mode is not None
+            else self._default_privacy_mode
+        )
+        groups = call_groups if call_groups is not None else self._default_groups
+
+        # Merge properties: default properties + call properties (call properties override)
+        properties = dict(self._default_properties)
+
+        if call_properties:
+            properties.update(call_properties)
+
+        if call_trace_id is None:
+            call_trace_id = str(uuid.uuid4())
+
+        return distinct_id, call_trace_id, properties, privacy_mode, groups
+
+    async def generate_content(
+        self,
+        model: str,
+        contents,
+        posthog_distinct_id: Optional[str] = None,
+        posthog_trace_id: Optional[str] = None,
+        posthog_properties: Optional[Dict[str, Any]] = None,
+        posthog_privacy_mode: Optional[bool] = None,
+        posthog_groups: Optional[Dict[str, Any]] = None,
+        **kwargs: Any,
+    ):
+        """
+        Generate content using Gemini's API while tracking usage in PostHog.
+
+        This method signature exactly matches genai.Client().aio.models.generate_content()
+        with additional PostHog tracking parameters.
+
+        Args:
+            model: The model to use (e.g., 'gemini-2.0-flash')
+            contents: The input content for generation
+            posthog_distinct_id: ID to associate with the usage event (overrides client default)
+            posthog_trace_id: Trace UUID for linking events (auto-generated if not provided)
+            posthog_properties: Extra properties to include in the event (merged with client defaults)
+            posthog_privacy_mode: Whether to redact sensitive information (overrides client default)
+            posthog_groups: Group analytics properties (overrides client default)
+            **kwargs: Arguments passed to Gemini's generate_content
+        """
+
+        # Merge PostHog parameters
+        distinct_id, trace_id, properties, privacy_mode, groups = (
+            self._merge_posthog_params(
+                posthog_distinct_id,
+                posthog_trace_id,
+                posthog_properties,
+                posthog_privacy_mode,
+                posthog_groups,
+            )
+        )
+
+        kwargs_with_contents = {"model": model, "contents": contents, **kwargs}
+
+        return await call_llm_and_track_usage_async(
+            distinct_id,
+            self._ph_client,
+            "gemini",
+            trace_id,
+            properties,
+            privacy_mode,
+            groups,
+            self._base_url,
+            self._client.aio.models.generate_content,
+            **kwargs_with_contents,
+        )
+
+    async def _generate_content_streaming(
+        self,
+        model: str,
+        contents,
+        distinct_id: Optional[str],
+        trace_id: Optional[str],
+        properties: Optional[Dict[str, Any]],
+        privacy_mode: bool,
+        groups: Optional[Dict[str, Any]],
+        **kwargs: Any,
+    ):
+        start_time = time.time()
+        usage_stats: TokenUsage = TokenUsage(input_tokens=0, output_tokens=0)
+        accumulated_content = []
+
+        kwargs_without_stream = {"model": model, "contents": contents, **kwargs}
+        response = await self._client.aio.models.generate_content_stream(
+            **kwargs_without_stream
+        )
+
+        async def async_generator():
+            nonlocal usage_stats
+            nonlocal accumulated_content
+
+            try:
+                async for chunk in response:
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_gemini_usage_from_chunk(chunk)
+
+                    if chunk_usage:
+                        # Gemini reports cumulative totals, not incremental values
+                        merge_usage_stats(usage_stats, chunk_usage, mode="cumulative")
+
+                    # Extract content from chunk (now returns content blocks)
+                    content_block = extract_gemini_content_from_chunk(chunk)
+
+                    if content_block is not None:
+                        accumulated_content.append(content_block)
+
+                    yield chunk
+
+            finally:
+                end_time = time.time()
+                latency = end_time - start_time
+
+                self._capture_streaming_event(
+                    model,
+                    contents,
+                    distinct_id,
+                    trace_id,
+                    properties,
+                    privacy_mode,
+                    groups,
+                    kwargs,
+                    usage_stats,
+                    latency,
+                    accumulated_content,
+                )
+
+        return async_generator()
+
+    def _capture_streaming_event(
+        self,
+        model: str,
+        contents,
+        distinct_id: Optional[str],
+        trace_id: Optional[str],
+        properties: Optional[Dict[str, Any]],
+        privacy_mode: bool,
+        groups: Optional[Dict[str, Any]],
+        kwargs: Dict[str, Any],
+        usage_stats: TokenUsage,
+        latency: float,
+        output: Any,
+    ):
+        # Prepare standardized event data
+        formatted_input = self._format_input(contents, **kwargs)
+        sanitized_input = sanitize_gemini(formatted_input)
+
+        event_data = StreamingEventData(
+            provider="gemini",
+            model=model,
+            base_url=self._base_url,
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_gemini_streaming_output(output),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=distinct_id,
+            trace_id=trace_id,
+            properties=properties,
+            privacy_mode=privacy_mode,
+            groups=groups,
+        )
+
+        # Use the common capture function
+        capture_streaming_event(self._ph_client, event_data)
+
+    def _format_input(self, contents, **kwargs):
+        """Format input contents for PostHog tracking"""
+
+        # Create kwargs dict with contents for merge_system_prompt
+        input_kwargs = {"contents": contents, **kwargs}
+        return merge_system_prompt(input_kwargs, "gemini")
+
+    async def generate_content_stream(
+        self,
+        model: str,
+        contents,
+        posthog_distinct_id: Optional[str] = None,
+        posthog_trace_id: Optional[str] = None,
+        posthog_properties: Optional[Dict[str, Any]] = None,
+        posthog_privacy_mode: Optional[bool] = None,
+        posthog_groups: Optional[Dict[str, Any]] = None,
+        **kwargs: Any,
+    ):
+        # Merge PostHog parameters
+        distinct_id, trace_id, properties, privacy_mode, groups = (
+            self._merge_posthog_params(
+                posthog_distinct_id,
+                posthog_trace_id,
+                posthog_properties,
+                posthog_privacy_mode,
+                posthog_groups,
+            )
+        )
+
+        return await self._generate_content_streaming(
+            model,
+            contents,
+            distinct_id,
+            trace_id,
+            properties,
+            privacy_mode,
+            groups,
+            **kwargs,
+        )

posthog/ai/gemini/gemini_converter.py

@@ -0,0 +1,659 @@
+"""
+Gemini-specific conversion utilities.
+
+This module handles the conversion of Gemini API responses and inputs
+into standardized formats for PostHog tracking.
+"""
+
+from typing import Any, Dict, List, Optional, TypedDict, Union
+
+from posthog.ai.types import (
+    FormattedContentItem,
+    FormattedMessage,
+    TokenUsage,
+)
+from posthog.ai.utils import serialize_raw_usage
+
+
+class GeminiPart(TypedDict, total=False):
+    """Represents a part in a Gemini message."""
+
+    text: str
+
+
+class GeminiMessage(TypedDict, total=False):
+    """Represents a Gemini message with various possible fields."""
+
+    role: str
+    parts: List[Union[GeminiPart, Dict[str, Any]]]
+    content: Union[str, List[Any]]
+    text: str
+
+
+def _format_parts_as_content_blocks(parts: List[Any]) -> List[FormattedContentItem]:
+    """
+    Format Gemini parts array into structured content blocks.
+
+    Preserves structure for multimodal content (text + images) instead of
+    concatenating everything into a string.
+
+    Args:
+        parts: List of parts that may contain text, inline_data, etc.
+
+    Returns:
+        List of formatted content blocks
+    """
+    content_blocks: List[FormattedContentItem] = []
+
+    for part in parts:
+        # Handle dict with text field
+        if isinstance(part, dict) and "text" in part:
+            content_blocks.append({"type": "text", "text": part["text"]})
+
+        # Handle string parts
+        elif isinstance(part, str):
+            content_blocks.append({"type": "text", "text": part})
+
+        # Handle dict with inline_data (images, documents, etc.)
+        elif isinstance(part, dict) and "inline_data" in part:
+            inline_data = part["inline_data"]
+            mime_type = inline_data.get("mime_type", "")
+            content_type = "image" if mime_type.startswith("image/") else "document"
+
+            content_blocks.append(
+                {
+                    "type": content_type,
+                    "inline_data": inline_data,
+                }
+            )
+
+        # Handle object with text attribute
+        elif hasattr(part, "text"):
+            text_value = getattr(part, "text", "")
+            if text_value:
+                content_blocks.append({"type": "text", "text": text_value})
+
+        # Handle object with inline_data attribute
+        elif hasattr(part, "inline_data"):
+            inline_data = part.inline_data
+            # Convert to dict if needed
+            if hasattr(inline_data, "mime_type") and hasattr(inline_data, "data"):
+                # Determine type based on mime_type
+                mime_type = inline_data.mime_type
+                content_type = "image" if mime_type.startswith("image/") else "document"
+
+                content_blocks.append(
+                    {
+                        "type": content_type,
+                        "inline_data": {
+                            "mime_type": mime_type,
+                            "data": inline_data.data,
+                        },
+                    }
+                )
+            else:
+                content_blocks.append(
+                    {
+                        "type": "image",
+                        "inline_data": inline_data,
+                    }
+                )
+
+    return content_blocks
+
+
+def _format_dict_message(item: Dict[str, Any]) -> FormattedMessage:
+    """
+    Format a dictionary message into standardized format.
+
+    Args:
+        item: Dictionary containing message data
+
+    Returns:
+        Formatted message with role and content
+    """
+
+    # Handle dict format with parts array (Gemini-specific format)
+    if "parts" in item and isinstance(item["parts"], list):
+        content_blocks = _format_parts_as_content_blocks(item["parts"])
+        return {"role": item.get("role", "user"), "content": content_blocks}
+
+    # Handle dict with content field
+    if "content" in item:
+        content = item["content"]
+
+        if isinstance(content, list):
+            # If content is a list, format it as content blocks
+            content_blocks = _format_parts_as_content_blocks(content)
+            return {"role": item.get("role", "user"), "content": content_blocks}
+
+        elif not isinstance(content, str):
+            content = str(content)
+
+        return {"role": item.get("role", "user"), "content": content}
+
+    # Handle dict with text field
+    if "text" in item:
+        return {"role": item.get("role", "user"), "content": item["text"]}
+
+    # Fallback to string representation
+    return {"role": "user", "content": str(item)}
+
+
+def _format_object_message(item: Any) -> FormattedMessage:
+    """
+    Format an object (with attributes) into standardized format.
+
+    Args:
+        item: Object that may have text or parts attributes
+
+    Returns:
+        Formatted message with role and content
+    """
+
+    # Handle object with parts attribute
+    if hasattr(item, "parts") and hasattr(item.parts, "__iter__"):
+        content_blocks = _format_parts_as_content_blocks(list(item.parts))
+        role = getattr(item, "role", "user") if hasattr(item, "role") else "user"
+
+        # Ensure role is a string
+        if not isinstance(role, str):
+            role = "user"
+
+        return {"role": role, "content": content_blocks}
+
+    # Handle object with text attribute
+    if hasattr(item, "text"):
+        role = getattr(item, "role", "user") if hasattr(item, "role") else "user"
+
+        # Ensure role is a string
+        if not isinstance(role, str):
+            role = "user"
+
+        return {"role": role, "content": item.text}
+
+    # Handle object with content attribute
+    if hasattr(item, "content"):
+        role = getattr(item, "role", "user") if hasattr(item, "role") else "user"
+
+        # Ensure role is a string
+        if not isinstance(role, str):
+            role = "user"
+
+        content = item.content
+
+        if isinstance(content, list):
+            content_blocks = _format_parts_as_content_blocks(content)
+            return {"role": role, "content": content_blocks}
+
+        elif not isinstance(content, str):
+            content = str(content)
+        return {"role": role, "content": content}
+
+    # Fallback to string representation
+    return {"role": "user", "content": str(item)}
+
+
+def format_gemini_response(response: Any) -> List[FormattedMessage]:
+    """
+    Format a Gemini response into standardized message format.
+
+    Args:
+        response: The response object from Gemini API
+
+    Returns:
+        List of formatted messages with role and content
+    """
+
+    output: List[FormattedMessage] = []
+
+    if response is None:
+        return output
+
+    if hasattr(response, "candidates") and response.candidates:
+        for candidate in response.candidates:
+            if hasattr(candidate, "content") and candidate.content:
+                content: List[FormattedContentItem] = []
+
+                if hasattr(candidate.content, "parts") and candidate.content.parts:
+                    for part in candidate.content.parts:
+                        if hasattr(part, "text") and part.text:
+                            content.append(
+                                {
+                                    "type": "text",
+                                    "text": part.text,
+                                }
+                            )
+
+                        elif hasattr(part, "function_call") and part.function_call:
+                            function_call = part.function_call
+                            content.append(
+                                {
+                                    "type": "function",
+                                    "function": {
+                                        "name": function_call.name,
+                                        "arguments": function_call.args,
+                                    },
+                                }
+                            )
+
+                        elif hasattr(part, "inline_data") and part.inline_data:
+                            # Handle audio/media inline data
+                            import base64
+
+                            inline_data = part.inline_data
+                            mime_type = getattr(inline_data, "mime_type", "audio/pcm")
+                            raw_data = getattr(inline_data, "data", b"")
+
+                            # Encode binary data as base64 string for JSON serialization
+                            if isinstance(raw_data, bytes):
+                                data = base64.b64encode(raw_data).decode("utf-8")
+                            else:
+                                # Already a string (base64)
+                                data = raw_data
+
+                            content.append(
+                                {
+                                    "type": "audio",
+                                    "mime_type": mime_type,
+                                    "data": data,
+                                }
+                            )
+
+                if content:
+                    output.append(
+                        {
+                            "role": "assistant",
+                            "content": content,
+                        }
+                    )
+
+            elif hasattr(candidate, "text") and candidate.text:
+                output.append(
+                    {
+                        "role": "assistant",
+                        "content": [{"type": "text", "text": candidate.text}],
+                    }
+                )
+
+    elif hasattr(response, "text") and response.text:
+        output.append(
+            {
+                "role": "assistant",
+                "content": [{"type": "text", "text": response.text}],
+            }
+        )
+
+    return output
+
+
+def extract_gemini_system_instruction(config: Any) -> Optional[str]:
+    """
+    Extract system instruction from Gemini config parameter.
+
+    Args:
+        config: Config object or dict that may contain system instruction
+
+    Returns:
+        System instruction string if present, None otherwise
+    """
+    if config is None:
+        return None
+
+    # Handle different config formats
+    if hasattr(config, "system_instruction"):
+        return config.system_instruction
+    elif isinstance(config, dict) and "system_instruction" in config:
+        return config["system_instruction"]
+    elif isinstance(config, dict) and "systemInstruction" in config:
+        return config["systemInstruction"]
+
+    return None
+
+
+def extract_gemini_tools(kwargs: Dict[str, Any]) -> Optional[Any]:
+    """
+    Extract tool definitions from Gemini API kwargs.
+
+    Args:
+        kwargs: Keyword arguments passed to Gemini API
+
+    Returns:
+        Tool definitions if present, None otherwise
+    """
+
+    if "config" in kwargs and hasattr(kwargs["config"], "tools"):
+        return kwargs["config"].tools
+
+    return None
+
+
+def format_gemini_input_with_system(
+    contents: Any, config: Any = None
+) -> List[FormattedMessage]:
+    """
+    Format Gemini input contents into standardized message format, including system instruction handling.
+
+    Args:
+        contents: Input contents in various possible formats
+        config: Config object or dict that may contain system instruction
+
+    Returns:
+        List of formatted messages with role and content fields, with system message prepended if needed
+    """
+    formatted_messages = format_gemini_input(contents)
+
+    # Check if system instruction is provided in config parameter
+    system_instruction = extract_gemini_system_instruction(config)
+
+    if system_instruction is not None:
+        has_system = any(msg.get("role") == "system" for msg in formatted_messages)
+        if not has_system:
+            from posthog.ai.types import FormattedMessage
+
+            system_message: FormattedMessage = {
+                "role": "system",
+                "content": system_instruction,
+            }
+            formatted_messages = [system_message] + list(formatted_messages)
+
+    return formatted_messages
+
+
+def format_gemini_input(contents: Any) -> List[FormattedMessage]:
+    """
+    Format Gemini input contents into standardized message format for PostHog tracking.
+
+    This function handles various input formats:
+    - String inputs
+    - List of strings, dicts, or objects
+    - Single dict or object
+    - Gemini-specific format with parts array
+
+    Args:
+        contents: Input contents in various possible formats
+
+    Returns:
+        List of formatted messages with role and content fields
+    """
+
+    # Handle string input
+    if isinstance(contents, str):
+        return [{"role": "user", "content": contents}]
+
+    # Handle list input
+    if isinstance(contents, list):
+        formatted: List[FormattedMessage] = []
+
+        for item in contents:
+            if isinstance(item, str):
+                formatted.append({"role": "user", "content": item})
+
+            elif isinstance(item, dict):
+                formatted.append(_format_dict_message(item))
+
+            else:
+                formatted.append(_format_object_message(item))
+
+        return formatted
+
+    # Handle single dict input
+    if isinstance(contents, dict):
+        return [_format_dict_message(contents)]
+
+    # Handle single object input
+    return [_format_object_message(contents)]
+
+
+def extract_gemini_web_search_count(response: Any) -> int:
+    """
+    Extract web search count from Gemini response.
+
+    Gemini bills per request that uses grounding, not per query.
+    Returns 1 if grounding_metadata is present with actual search data, 0 otherwise.
+
+    Args:
+        response: The response from Gemini API
+
+    Returns:
+        1 if web search/grounding was used, 0 otherwise
+    """
+
+    # Check for grounding_metadata in candidates
+    if hasattr(response, "candidates"):
+        for candidate in response.candidates:
+            if (
+                hasattr(candidate, "grounding_metadata")
+                and candidate.grounding_metadata
+            ):
+                grounding_metadata = candidate.grounding_metadata
+
+                # Check if web_search_queries exists and is non-empty
+                if hasattr(grounding_metadata, "web_search_queries"):
+                    queries = grounding_metadata.web_search_queries
+
+                    if queries is not None and len(queries) > 0:
+                        return 1
+
+                # Check if grounding_chunks exists and is non-empty
+                if hasattr(grounding_metadata, "grounding_chunks"):
+                    chunks = grounding_metadata.grounding_chunks
+
+                    if chunks is not None and len(chunks) > 0:
+                        return 1
+
+            # Also check for google_search or grounding in function call names
+            if hasattr(candidate, "content") and candidate.content:
+                if hasattr(candidate.content, "parts") and candidate.content.parts:
+                    for part in candidate.content.parts:
+                        if hasattr(part, "function_call") and part.function_call:
+                            function_name = getattr(
+                                part.function_call, "name", ""
+                            ).lower()
+
+                            if (
+                                "google_search" in function_name
+                                or "grounding" in function_name
+                            ):
+                                return 1
+
+    return 0
+
+
+def _extract_usage_from_metadata(metadata: Any) -> TokenUsage:
+    """
+    Common logic to extract usage from Gemini metadata.
+    Used by both streaming and non-streaming paths.
+
+    Args:
+        metadata: usage_metadata from Gemini response or chunk
+
+    Returns:
+        TokenUsage with standardized usage
+    """
+    usage = TokenUsage(
+        input_tokens=getattr(metadata, "prompt_token_count", 0),
+        output_tokens=getattr(metadata, "candidates_token_count", 0),
+    )
+
+    # Add cache tokens if present (don't add if 0)
+    if hasattr(metadata, "cached_content_token_count"):
+        cache_tokens = metadata.cached_content_token_count
+        if cache_tokens and cache_tokens > 0:
+            usage["cache_read_input_tokens"] = cache_tokens
+
+    # Add reasoning tokens if present (don't add if 0)
+    if hasattr(metadata, "thoughts_token_count"):
+        reasoning_tokens = metadata.thoughts_token_count
+        if reasoning_tokens and reasoning_tokens > 0:
+            usage["reasoning_tokens"] = reasoning_tokens
+
+    # Capture raw usage metadata for backend processing
+    # Serialize to dict here in the converter (not in utils)
+    serialized = serialize_raw_usage(metadata)
+    if serialized:
+        usage["raw_usage"] = serialized
+
+    return usage
+
+
+def extract_gemini_usage_from_response(response: Any) -> TokenUsage:
+    """
+    Extract usage statistics from a full Gemini response (non-streaming).
+
+    Args:
+        response: The complete response from Gemini API
+
+    Returns:
+        TokenUsage with standardized usage statistics
+    """
+    if not hasattr(response, "usage_metadata") or not response.usage_metadata:
+        return TokenUsage(input_tokens=0, output_tokens=0)
+
+    usage = _extract_usage_from_metadata(response.usage_metadata)
+
+    # Add web search count if present
+    web_search_count = extract_gemini_web_search_count(response)
+    if web_search_count > 0:
+        usage["web_search_count"] = web_search_count
+
+    return usage
+
+
+def extract_gemini_usage_from_chunk(chunk: Any) -> TokenUsage:
+    """
+    Extract usage statistics from a Gemini streaming chunk.
+
+    Args:
+        chunk: Streaming chunk from Gemini API
+
+    Returns:
+        TokenUsage with standardized usage statistics
+    """
+
+    usage: TokenUsage = TokenUsage()
+
+    # Extract web search count from the chunk before checking for usage_metadata
+    # Web search indicators can appear on any chunk, not just those with usage data
+    web_search_count = extract_gemini_web_search_count(chunk)
+    if web_search_count > 0:
+        usage["web_search_count"] = web_search_count
+
+    if not hasattr(chunk, "usage_metadata") or not chunk.usage_metadata:
+        return usage
+
+    usage_from_metadata = _extract_usage_from_metadata(chunk.usage_metadata)
+
+    # Merge the usage from metadata with any web search count we found
+    usage.update(usage_from_metadata)
+
+    return usage
+
+
+def extract_gemini_content_from_chunk(chunk: Any) -> Optional[Dict[str, Any]]:
+    """
+    Extract content (text or function call) from a Gemini streaming chunk.
+
+    Args:
+        chunk: Streaming chunk from Gemini API
+
+    Returns:
+        Content block dictionary if present, None otherwise
+    """
+
+    # Check for text content
+    if hasattr(chunk, "text") and chunk.text:
+        return {"type": "text", "text": chunk.text}
+
+    # Check for function calls in candidates
+    if hasattr(chunk, "candidates") and chunk.candidates:
+        for candidate in chunk.candidates:
+            if hasattr(candidate, "content") and candidate.content:
+                if hasattr(candidate.content, "parts") and candidate.content.parts:
+                    for part in candidate.content.parts:
+                        # Check for function_call part
+                        if hasattr(part, "function_call") and part.function_call:
+                            function_call = part.function_call
+                            return {
+                                "type": "function",
+                                "function": {
+                                    "name": function_call.name,
+                                    "arguments": function_call.args,
+                                },
+                            }
+                        # Also check for text in parts
+                        elif hasattr(part, "text") and part.text:
+                            return {"type": "text", "text": part.text}
+
+    return None
+
+
+def format_gemini_streaming_output(
+    accumulated_content: Union[str, List[Any]],
+) -> List[FormattedMessage]:
+    """
+    Format the final output from Gemini streaming.
+
+    Args:
+        accumulated_content: Accumulated content from streaming (string, list of strings, or list of content blocks)
+
+    Returns:
+        List of formatted messages
+    """
+
+    # Handle legacy string input (backward compatibility)
+    if isinstance(accumulated_content, str):
+        return [
+            {
+                "role": "assistant",
+                "content": [{"type": "text", "text": accumulated_content}],
+            }
+        ]
+
+    # Handle list input
+    if isinstance(accumulated_content, list):
+        content: List[FormattedContentItem] = []
+        text_parts = []
+
+        for item in accumulated_content:
+            if isinstance(item, str):
+                # Legacy support: accumulate strings
+                text_parts.append(item)
+            elif isinstance(item, dict):
+                # New format: content blocks
+                if item.get("type") == "text":
+                    text_parts.append(item.get("text", ""))
+                elif item.get("type") == "function":
+                    # If we have accumulated text, add it first
+                    if text_parts:
+                        content.append(
+                            {
+                                "type": "text",
+                                "text": "".join(text_parts),
+                            }
+                        )
+                        text_parts = []
+
+                    # Add the function call
+                    content.append(
+                        {
+                            "type": "function",
+                            "function": item.get("function", {}),
+                        }
+                    )
+
+        # Add any remaining text
+        if text_parts:
+            content.append(
+                {
+                    "type": "text",
+                    "text": "".join(text_parts),
+                }
+            )
+
+        # If we have content, return it
+        if content:
+            return [{"role": "assistant", "content": content}]
+
+    # Fallback for empty or unexpected input
+    return [{"role": "assistant", "content": [{"type": "text", "text": ""}]}]

posthog/ai/langchain/callbacks.py

@@ -1,10 +1,11 @@
 try:
-    import langchain  # noqa: F401
+    import langchain_core  # noqa: F401
 except ImportError:
     raise ModuleNotFoundError(
-        "Please install LangChain to use this feature: 'pip install langchain'"
+        "Please install LangChain to use this feature: 'pip install langchain-core'"
     )
 
+import json
 import logging
 import time
 from dataclasses import dataclass
@@ -19,8 +20,14 @@ from typing import (
 )
 from uuid import UUID
 
-from langchain.callbacks.base import BaseCallbackHandler
-from langchain.schema.agent import AgentAction, AgentFinish
+try:
+    # LangChain 1.0+ and modern 0.x with langchain-core
+    from langchain_core.agents import AgentAction, AgentFinish
+    from langchain_core.callbacks.base import BaseCallbackHandler
+except (ImportError, ModuleNotFoundError):
+    # Fallback for older LangChain versions
+    from langchain.callbacks.base import BaseCallbackHandler
+    from langchain.schema.agent import AgentAction, AgentFinish
 from langchain_core.documents import Document
 from langchain_core.messages import (
     AIMessage,
@@ -28,12 +35,14 @@ from langchain_core.messages import (
     FunctionMessage,
     HumanMessage,
     SystemMessage,
+    ToolCall,
     ToolMessage,
 )
 from langchain_core.outputs import ChatGeneration, LLMResult
 from pydantic import BaseModel
 
-from posthog import default_client
+from posthog import setup
+from posthog.ai.sanitization import sanitize_langchain
 from posthog.ai.utils import get_model_params, with_privacy_mode
 from posthog.client import Client
 
@@ -70,6 +79,8 @@ class GenerationMetadata(SpanMetadata):
     """Base URL of the provider's API used in the run."""
     tools: Optional[List[Dict[str, Any]]] = None
     """Tools provided to the model."""
+    posthog_properties: Optional[Dict[str, Any]] = None
+    """PostHog properties of the run."""
 
 
 RunMetadata = Union[SpanMetadata, GenerationMetadata]
@@ -81,10 +92,10 @@ class CallbackHandler(BaseCallbackHandler):
     The PostHog LLM observability callback handler for LangChain.
     """
 
-    _client: Client
+    _ph_client: Client
     """PostHog client instance."""
 
-    _distinct_id: Optional[Union[str, int, float, UUID]]
+    _distinct_id: Optional[Union[str, int, UUID]]
     """Distinct ID of the user to associate the trace with."""
 
     _trace_id: Optional[Union[str, int, float, UUID]]
@@ -112,7 +123,7 @@ class CallbackHandler(BaseCallbackHandler):
         self,
         client: Optional[Client] = None,
         *,
-        distinct_id: Optional[Union[str, int, float, UUID]] = None,
+        distinct_id: Optional[Union[str, int, UUID]] = None,
         trace_id: Optional[Union[str, int, float, UUID]] = None,
         properties: Optional[Dict[str, Any]] = None,
         privacy_mode: bool = False,
@@ -127,10 +138,7 @@ class CallbackHandler(BaseCallbackHandler):
             privacy_mode: Whether to redact the input and output of the trace.
             groups: Optional additional PostHog groups to use for the trace.
         """
-        posthog_client = client or default_client
-        if posthog_client is None:
-            raise ValueError("PostHog client is required")
-        self._client = posthog_client
+        self._ph_client = client or setup()
         self._distinct_id = distinct_id
         self._trace_id = trace_id
         self._properties = properties or {}
@@ -414,6 +422,8 @@ class CallbackHandler(BaseCallbackHandler):
                 generation.model = model
             if provider := metadata.get("ls_provider"):
                 generation.provider = provider
+
+            generation.posthog_properties = metadata.get("posthog_properties")
         try:
             base_url = serialized["kwargs"]["openai_api_base"]
             if base_url is not None:
@@ -481,11 +491,12 @@ class CallbackHandler(BaseCallbackHandler):
         event_properties = {
             "$ai_trace_id": trace_id,
             "$ai_input_state": with_privacy_mode(
-                self._client, self._privacy_mode, run.input
+                self._ph_client, self._privacy_mode, sanitize_langchain(run.input)
             ),
             "$ai_latency": run.latency,
             "$ai_span_name": run.name,
             "$ai_span_id": run_id,
+            "$ai_framework": "langchain",
         }
         if parent_run_id is not None:
             event_properties["$ai_parent_id"] = parent_run_id
@@ -495,15 +506,23 @@ class CallbackHandler(BaseCallbackHandler):
         if isinstance(outputs, BaseException):
             event_properties["$ai_error"] = _stringify_exception(outputs)
             event_properties["$ai_is_error"] = True
+            event_properties = _capture_exception_and_update_properties(
+                self._ph_client,
+                outputs,
+                self._distinct_id,
+                self._groups,
+                event_properties,
+            )
+
         elif outputs is not None:
             event_properties["$ai_output_state"] = with_privacy_mode(
-                self._client, self._privacy_mode, outputs
+                self._ph_client, self._privacy_mode, outputs
             )
 
         if self._distinct_id is None:
             event_properties["$process_person_profile"] = False
 
-        self._client.capture(
+        self._ph_client.capture(
             distinct_id=self._distinct_id or run_id,
             event=event_name,
             properties=event_properties,
@@ -550,25 +569,42 @@ class CallbackHandler(BaseCallbackHandler):
             "$ai_provider": run.provider,
             "$ai_model": run.model,
             "$ai_model_parameters": run.model_params,
-            "$ai_input": with_privacy_mode(self._client, self._privacy_mode, run.input),
+            "$ai_input": with_privacy_mode(
+                self._ph_client, self._privacy_mode, sanitize_langchain(run.input)
+            ),
             "$ai_http_status": 200,
             "$ai_latency": run.latency,
             "$ai_base_url": run.base_url,
+            "$ai_framework": "langchain",
         }
+
+        if isinstance(run.posthog_properties, dict):
+            event_properties.update(run.posthog_properties)
+
         if run.tools:
-            event_properties["$ai_tools"] = with_privacy_mode(
-                self._client,
-                self._privacy_mode,
-                run.tools,
-            )
+            event_properties["$ai_tools"] = run.tools
+
+        if self._properties:
+            event_properties.update(self._properties)
+
+        if self._distinct_id is None:
+            event_properties["$process_person_profile"] = False
 
         if isinstance(output, BaseException):
             event_properties["$ai_http_status"] = _get_http_status(output)
             event_properties["$ai_error"] = _stringify_exception(output)
             event_properties["$ai_is_error"] = True
+
+            event_properties = _capture_exception_and_update_properties(
+                self._ph_client,
+                output,
+                self._distinct_id,
+                self._groups,
+                event_properties,
+            )
         else:
             # Add usage
-            usage = _parse_usage(output)
+            usage = _parse_usage(output, run.provider, run.model)
             event_properties["$ai_input_tokens"] = usage.input_tokens
             event_properties["$ai_output_tokens"] = usage.output_tokens
             event_properties["$ai_cache_creation_input_tokens"] = (
@@ -586,19 +622,14 @@ class CallbackHandler(BaseCallbackHandler):
                 ]
             else:
                 completions = [
-                    _extract_raw_esponse(generation) for generation in generation_result
+                    _extract_raw_response(generation)
+                    for generation in generation_result
                 ]
             event_properties["$ai_output_choices"] = with_privacy_mode(
-                self._client, self._privacy_mode, completions
+                self._ph_client, self._privacy_mode, completions
             )
 
-        if self._properties:
-            event_properties.update(self._properties)
-
-        if self._distinct_id is None:
-            event_properties["$process_person_profile"] = False
-
-        self._client.capture(
+        self._ph_client.capture(
             distinct_id=self._distinct_id or trace_id,
             event="$ai_generation",
             properties=event_properties,
@@ -617,7 +648,7 @@ class CallbackHandler(BaseCallbackHandler):
         )
 
 
-def _extract_raw_esponse(last_response):
+def _extract_raw_response(last_response):
     """Extract the response from the last response of the LLM call."""
     # We return the text of the response if not empty
     if last_response.text is not None and last_response.text.strip() != "":
@@ -630,12 +661,35 @@ def _extract_raw_esponse(last_response):
         return ""
 
 
-def _convert_message_to_dict(message: BaseMessage) -> Dict[str, Any]:
+def _convert_lc_tool_calls_to_oai(
+    tool_calls: list[ToolCall],
+) -> list[dict[str, Any]]:
+    try:
+        return [
+            {
+                "type": "function",
+                "id": tool_call["id"],
+                "function": {
+                    "name": tool_call["name"],
+                    "arguments": json.dumps(tool_call["args"]),
+                },
+            }
+            for tool_call in tool_calls
+        ]
+    except KeyError:
+        return tool_calls
+
+
+def _convert_message_to_dict(message: BaseMessage) -> dict[str, Any]:
     # assistant message
     if isinstance(message, HumanMessage):
         message_dict = {"role": "user", "content": message.content}
     elif isinstance(message, AIMessage):
         message_dict = {"role": "assistant", "content": message.content}
+        if message.tool_calls:
+            message_dict["tool_calls"] = _convert_lc_tool_calls_to_oai(
+                message.tool_calls
+            )
     elif isinstance(message, SystemMessage):
         message_dict = {"role": "system", "content": message.content}
     elif isinstance(message, ToolMessage):
@@ -648,6 +702,9 @@ def _convert_message_to_dict(message: BaseMessage) -> Dict[str, Any]:
     if message.additional_kwargs:
         message_dict.update(message.additional_kwargs)
 
+    if "content" in message_dict and not message_dict["content"]:
+        message_dict["content"] = ""
+
     return message_dict
 
 
@@ -662,6 +719,8 @@ class ModelUsage:
 
 def _parse_usage_model(
     usage: Union[BaseModel, dict],
+    provider: Optional[str] = None,
+    model: Optional[str] = None,
 ) -> ModelUsage:
     if isinstance(usage, BaseModel):
         usage = usage.__dict__
@@ -724,15 +783,38 @@ def _parse_usage_model(
         "cache_read": "cache_read_tokens",
         "reasoning": "reasoning_tokens",
     }
-    return ModelUsage(
+    normalized_usage = ModelUsage(
         **{
             dataclass_key: parsed_usage.get(mapped_key) or 0
             for mapped_key, dataclass_key in field_mapping.items()
         },
     )
+    # For Anthropic providers, LangChain reports input_tokens as the sum of all input tokens.
+    # Our cost calculation expects them to be separate for Anthropic, so we subtract cache tokens.
+    # Both cache_read and cache_write tokens should be subtracted since Anthropic's raw API
+    # reports input_tokens as tokens NOT read from or used to create a cache.
+    # For other providers (OpenAI, etc.), input_tokens already excludes cache tokens as expected.
+    # Match logic consistent with plugin-server: exact match on provider OR substring match on model
+    is_anthropic = False
+    if provider and provider.lower() == "anthropic":
+        is_anthropic = True
+    elif model and "anthropic" in model.lower():
+        is_anthropic = True
+
+    if is_anthropic and normalized_usage.input_tokens:
+        cache_tokens = (normalized_usage.cache_read_tokens or 0) + (
+            normalized_usage.cache_write_tokens or 0
+        )
+        if cache_tokens > 0:
+            normalized_usage.input_tokens = max(
+                normalized_usage.input_tokens - cache_tokens, 0
+            )
+    return normalized_usage
 
 
-def _parse_usage(response: LLMResult) -> ModelUsage:
+def _parse_usage(
+    response: LLMResult, provider: Optional[str] = None, model: Optional[str] = None
+) -> ModelUsage:
     # langchain-anthropic uses the usage field
     llm_usage_keys = ["token_usage", "usage"]
     llm_usage: ModelUsage = ModelUsage(
@@ -746,13 +828,15 @@ def _parse_usage(response: LLMResult) -> ModelUsage:
     if response.llm_output is not None:
         for key in llm_usage_keys:
             if response.llm_output.get(key):
-                llm_usage = _parse_usage_model(response.llm_output[key])
+                llm_usage = _parse_usage_model(
+                    response.llm_output[key], provider, model
+                )
                 break
 
     if hasattr(response, "generations"):
         for generation in response.generations:
             if "usage" in generation:
-                llm_usage = _parse_usage_model(generation["usage"])
+                llm_usage = _parse_usage_model(generation["usage"], provider, model)
                 break
 
             for generation_chunk in generation:
@@ -760,7 +844,9 @@ def _parse_usage(response: LLMResult) -> ModelUsage:
                     "usage_metadata" in generation_chunk.generation_info
                 ):
                     llm_usage = _parse_usage_model(
-                        generation_chunk.generation_info["usage_metadata"]
+                        generation_chunk.generation_info["usage_metadata"],
+                        provider,
+                        model,
                     )
                     break
 
@@ -787,12 +873,33 @@ def _parse_usage(response: LLMResult) -> ModelUsage:
                     bedrock_anthropic_usage or bedrock_titan_usage or ollama_usage
                 )
                 if chunk_usage:
-                    llm_usage = _parse_usage_model(chunk_usage)
+                    llm_usage = _parse_usage_model(chunk_usage, provider, model)
                     break
 
     return llm_usage
 
 
+def _capture_exception_and_update_properties(
+    client: Client,
+    exception: BaseException,
+    distinct_id: Optional[Union[str, int, UUID]],
+    groups: Optional[Dict[str, Any]],
+    event_properties: Dict[str, Any],
+):
+    if client.enable_exception_autocapture:
+        exception_id = client.capture_exception(
+            exception,
+            distinct_id=distinct_id,
+            groups=groups,
+            properties=event_properties,
+        )
+
+        if exception_id:
+            event_properties["$exception_event_id"] = exception_id
+
+    return event_properties
+
+
 def _get_http_status(error: BaseException) -> int:
     # OpenAI: https://github.com/openai/openai-python/blob/main/src/openai/_exceptions.py
     # Anthropic: https://github.com/anthropics/anthropic-sdk-python/blob/main/src/anthropic/_exceptions.py

posthog/ai/openai/__init__.py

@@ -1,5 +1,20 @@
 from .openai import OpenAI
 from .openai_async import AsyncOpenAI
 from .openai_providers import AsyncAzureOpenAI, AzureOpenAI
+from .openai_converter import (
+    format_openai_response,
+    format_openai_input,
+    extract_openai_tools,
+    format_openai_streaming_content,
+)
 
-__all__ = ["OpenAI", "AsyncOpenAI", "AzureOpenAI", "AsyncAzureOpenAI"]
+__all__ = [
+    "OpenAI",
+    "AsyncOpenAI",
+    "AzureOpenAI",
+    "AsyncAzureOpenAI",
+    "format_openai_response",
+    "format_openai_input",
+    "extract_openai_tools",
+    "format_openai_streaming_content",
+]

posthog/ai/openai/openai.py

@@ -2,6 +2,8 @@ import time
 import uuid
 from typing import Any, Dict, List, Optional
 
+from posthog.ai.types import TokenUsage
+
 try:
     import openai
 except ImportError:
@@ -11,10 +13,19 @@ except ImportError:
 
 from posthog.ai.utils import (
     call_llm_and_track_usage,
-    get_model_params,
+    extract_available_tool_calls,
+    merge_usage_stats,
     with_privacy_mode,
 )
+from posthog.ai.openai.openai_converter import (
+    extract_openai_usage_from_chunk,
+    extract_openai_content_from_chunk,
+    extract_openai_tool_calls_from_chunk,
+    accumulate_openai_tool_calls,
+)
+from posthog.ai.sanitization import sanitize_openai, sanitize_openai_response
 from posthog.client import Client as PostHogClient
+from posthog import setup
 
 
 class OpenAI(openai.OpenAI):
@@ -24,16 +35,16 @@ class OpenAI(openai.OpenAI):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             api_key: OpenAI API key.
-            posthog_client: If provided, events will be captured via this client instead
-                            of the global posthog.
+            posthog_client: If provided, events will be captured via this client instead of the global `posthog`.
             **openai_config: Any additional keyword args to set on openai (e.g. organization="xxx").
         """
+
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
 
         # Store original objects after parent initialization (only if they exist)
         self._original_chat = getattr(self, "chat", None)
@@ -111,45 +122,36 @@ class WrappedResponses:
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {}
+        usage_stats: TokenUsage = TokenUsage()
         final_content = []
+        model_from_response: Optional[str] = None
         response = self._original.create(**kwargs)
 
         def generator():
             nonlocal usage_stats
             nonlocal final_content  # noqa: F824
+            nonlocal model_from_response
 
             try:
                 for chunk in response:
-                    if hasattr(chunk, "type") and chunk.type == "response.completed":
-                        res = chunk.response
-                        if res.output and len(res.output) > 0:
-                            final_content.append(res.output[0])
-
-                    if hasattr(chunk, "usage") and chunk.usage:
-                        usage_stats = {
-                            k: getattr(chunk.usage, k, 0)
-                            for k in [
-                                "input_tokens",
-                                "output_tokens",
-                                "total_tokens",
-                            ]
-                        }
-
-                        # Add support for cached tokens
-                        if hasattr(chunk.usage, "output_tokens_details") and hasattr(
-                            chunk.usage.output_tokens_details, "reasoning_tokens"
+                    # Extract model from response object in chunk (for stored prompts)
+                    if hasattr(chunk, "response") and chunk.response:
+                        if model_from_response is None and hasattr(
+                            chunk.response, "model"
                         ):
-                            usage_stats["reasoning_tokens"] = (
-                                chunk.usage.output_tokens_details.reasoning_tokens
-                            )
+                            model_from_response = chunk.response.model
 
-                        if hasattr(chunk.usage, "input_tokens_details") and hasattr(
-                            chunk.usage.input_tokens_details, "cached_tokens"
-                        ):
-                            usage_stats["cache_read_input_tokens"] = (
-                                chunk.usage.input_tokens_details.cached_tokens
-                            )
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_openai_usage_from_chunk(chunk, "responses")
+
+                    if chunk_usage:
+                        merge_usage_stats(usage_stats, chunk_usage)
+
+                    # Extract content from chunk
+                    content = extract_openai_content_from_chunk(chunk, "responses")
+
+                    if content is not None:
+                        final_content.append(content)
 
                     yield chunk
 
@@ -167,6 +169,8 @@ class WrappedResponses:
                     usage_stats,
                     latency,
                     output,
+                    None,  # Responses API doesn't have tools
+                    model_from_response,
                 )
 
         return generator()
@@ -179,56 +183,44 @@ class WrappedResponses:
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
         output: Any,
-        tool_calls: Optional[List[Dict[str, Any]]] = None,
+        available_tool_calls: Optional[List[Dict[str, Any]]] = None,
+        model_from_response: Optional[str] = None,
     ):
-        if posthog_trace_id is None:
-            posthog_trace_id = str(uuid.uuid4())
+        from posthog.ai.types import StreamingEventData
+        from posthog.ai.openai.openai_converter import (
+            format_openai_streaming_input,
+            format_openai_streaming_output,
+        )
+        from posthog.ai.utils import capture_streaming_event
 
-        event_properties = {
-            "$ai_provider": "openai",
-            "$ai_model": kwargs.get("model"),
-            "$ai_model_parameters": get_model_params(kwargs),
-            "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("input")
-            ),
-            "$ai_output_choices": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                output,
-            ),
-            "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("output_tokens", 0),
-            "$ai_cache_read_input_tokens": usage_stats.get(
-                "cache_read_input_tokens", 0
-            ),
-            "$ai_reasoning_tokens": usage_stats.get("reasoning_tokens", 0),
-            "$ai_latency": latency,
-            "$ai_trace_id": posthog_trace_id,
-            "$ai_base_url": str(self._client.base_url),
-            **(posthog_properties or {}),
-        }
+        # Prepare standardized event data
+        formatted_input = format_openai_streaming_input(kwargs, "responses")
+        sanitized_input = sanitize_openai_response(formatted_input)
 
-        if tool_calls:
-            event_properties["$ai_tools"] = with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                tool_calls,
-            )
+        # Use model from kwargs, fallback to model from response
+        model = kwargs.get("model") or model_from_response or "unknown"
 
-        if posthog_distinct_id is None:
-            event_properties["$process_person_profile"] = False
+        event_data = StreamingEventData(
+            provider="openai",
+            model=model,
+            base_url=str(self._client.base_url),
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_openai_streaming_output(output, "responses"),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=posthog_distinct_id,
+            trace_id=posthog_trace_id,
+            properties=posthog_properties,
+            privacy_mode=posthog_privacy_mode,
+            groups=posthog_groups,
+        )
 
-        if hasattr(self._client._ph_client, "capture"):
-            self._client._ph_client.capture(
-                distinct_id=posthog_distinct_id or posthog_trace_id,
-                event="$ai_generation",
-                properties=event_properties,
-                groups=posthog_groups,
-            )
+        # Use the common capture function
+        capture_streaming_event(self._client._ph_client, event_data)
 
     def parse(
         self,
@@ -339,9 +331,10 @@ class WrappedCompletions:
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {}
+        usage_stats: TokenUsage = TokenUsage()
         accumulated_content = []
-        accumulated_tools = {}
+        accumulated_tool_calls: Dict[int, Dict[str, Any]] = {}
+        model_from_response: Optional[str] = None
         if "stream_options" not in kwargs:
             kwargs["stream_options"] = {}
         kwargs["stream_options"]["include_usage"] = True
@@ -350,70 +343,47 @@ class WrappedCompletions:
         def generator():
             nonlocal usage_stats
             nonlocal accumulated_content  # noqa: F824
-            nonlocal accumulated_tools  # noqa: F824
+            nonlocal accumulated_tool_calls
+            nonlocal model_from_response
 
             try:
                 for chunk in response:
-                    if hasattr(chunk, "usage") and chunk.usage:
-                        usage_stats = {
-                            k: getattr(chunk.usage, k, 0)
-                            for k in [
-                                "prompt_tokens",
-                                "completion_tokens",
-                                "total_tokens",
-                            ]
-                        }
+                    # Extract model from chunk (Chat Completions chunks have model field)
+                    if model_from_response is None and hasattr(chunk, "model"):
+                        model_from_response = chunk.model
 
-                        # Add support for cached tokens
-                        if hasattr(chunk.usage, "prompt_tokens_details") and hasattr(
-                            chunk.usage.prompt_tokens_details, "cached_tokens"
-                        ):
-                            usage_stats["cache_read_input_tokens"] = (
-                                chunk.usage.prompt_tokens_details.cached_tokens
-                            )
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_openai_usage_from_chunk(chunk, "chat")
 
-                        if hasattr(chunk.usage, "output_tokens_details") and hasattr(
-                            chunk.usage.output_tokens_details, "reasoning_tokens"
-                        ):
-                            usage_stats["reasoning_tokens"] = (
-                                chunk.usage.output_tokens_details.reasoning_tokens
-                            )
+                    if chunk_usage:
+                        merge_usage_stats(usage_stats, chunk_usage)
 
-                    if (
-                        hasattr(chunk, "choices")
-                        and chunk.choices
-                        and len(chunk.choices) > 0
-                    ):
-                        if chunk.choices[0].delta and chunk.choices[0].delta.content:
-                            content = chunk.choices[0].delta.content
-                            if content:
-                                accumulated_content.append(content)
+                    # Extract content from chunk
+                    content = extract_openai_content_from_chunk(chunk, "chat")
 
-                        # Process tool calls
-                        tool_calls = getattr(chunk.choices[0].delta, "tool_calls", None)
-                        if tool_calls:
-                            for tool_call in tool_calls:
-                                index = tool_call.index
-                                if index not in accumulated_tools:
-                                    accumulated_tools[index] = tool_call
-                                else:
-                                    # Append arguments for existing tool calls
-                                    if hasattr(tool_call, "function") and hasattr(
-                                        tool_call.function, "arguments"
-                                    ):
-                                        accumulated_tools[
-                                            index
-                                        ].function.arguments += (
-                                            tool_call.function.arguments
-                                        )
+                    if content is not None:
+                        accumulated_content.append(content)
+
+                    # Extract and accumulate tool calls from chunk
+                    chunk_tool_calls = extract_openai_tool_calls_from_chunk(chunk)
+                    if chunk_tool_calls:
+                        accumulate_openai_tool_calls(
+                            accumulated_tool_calls, chunk_tool_calls
+                        )
 
                     yield chunk
 
             finally:
                 end_time = time.time()
                 latency = end_time - start_time
-                output = "".join(accumulated_content)
-                tools = list(accumulated_tools.values()) if accumulated_tools else None
+
+                # Convert accumulated tool calls dict to list
+                tool_calls_list = (
+                    list(accumulated_tool_calls.values())
+                    if accumulated_tool_calls
+                    else None
+                )
+
                 self._capture_streaming_event(
                     posthog_distinct_id,
                     posthog_trace_id,
@@ -423,8 +393,10 @@ class WrappedCompletions:
                     kwargs,
                     usage_stats,
                     latency,
-                    output,
-                    tools,
+                    accumulated_content,
+                    tool_calls_list,
+                    extract_available_tool_calls("openai", kwargs),
+                    model_from_response,
                 )
 
         return generator()
@@ -437,56 +409,45 @@ class WrappedCompletions:
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
         output: Any,
         tool_calls: Optional[List[Dict[str, Any]]] = None,
+        available_tool_calls: Optional[List[Dict[str, Any]]] = None,
+        model_from_response: Optional[str] = None,
     ):
-        if posthog_trace_id is None:
-            posthog_trace_id = str(uuid.uuid4())
+        from posthog.ai.types import StreamingEventData
+        from posthog.ai.openai.openai_converter import (
+            format_openai_streaming_input,
+            format_openai_streaming_output,
+        )
+        from posthog.ai.utils import capture_streaming_event
 
-        event_properties = {
-            "$ai_provider": "openai",
-            "$ai_model": kwargs.get("model"),
-            "$ai_model_parameters": get_model_params(kwargs),
-            "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("messages")
-            ),
-            "$ai_output_choices": with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                [{"content": output, "role": "assistant"}],
-            ),
-            "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("completion_tokens", 0),
-            "$ai_cache_read_input_tokens": usage_stats.get(
-                "cache_read_input_tokens", 0
-            ),
-            "$ai_reasoning_tokens": usage_stats.get("reasoning_tokens", 0),
-            "$ai_latency": latency,
-            "$ai_trace_id": posthog_trace_id,
-            "$ai_base_url": str(self._client.base_url),
-            **(posthog_properties or {}),
-        }
+        # Prepare standardized event data
+        formatted_input = format_openai_streaming_input(kwargs, "chat")
+        sanitized_input = sanitize_openai(formatted_input)
 
-        if tool_calls:
-            event_properties["$ai_tools"] = with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                tool_calls,
-            )
+        # Use model from kwargs, fallback to model from response
+        model = kwargs.get("model") or model_from_response or "unknown"
 
-        if posthog_distinct_id is None:
-            event_properties["$process_person_profile"] = False
+        event_data = StreamingEventData(
+            provider="openai",
+            model=model,
+            base_url=str(self._client.base_url),
+            kwargs=kwargs,
+            formatted_input=sanitized_input,
+            formatted_output=format_openai_streaming_output(output, "chat", tool_calls),
+            usage_stats=usage_stats,
+            latency=latency,
+            distinct_id=posthog_distinct_id,
+            trace_id=posthog_trace_id,
+            properties=posthog_properties,
+            privacy_mode=posthog_privacy_mode,
+            groups=posthog_groups,
+        )
 
-        if hasattr(self._client._ph_client, "capture"):
-            self._client._ph_client.capture(
-                distinct_id=posthog_distinct_id or posthog_trace_id,
-                event="$ai_generation",
-                properties=event_properties,
-                groups=posthog_groups,
-            )
+        # Use the common capture function
+        capture_streaming_event(self._client._ph_client, event_data)
 
 
 class WrappedEmbeddings:
@@ -523,6 +484,7 @@ class WrappedEmbeddings:
         Returns:
             The response from OpenAI's embeddings.create call.
         """
+
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
@@ -545,7 +507,9 @@ class WrappedEmbeddings:
             "$ai_provider": "openai",
             "$ai_model": kwargs.get("model"),
             "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("input")
+                self._client._ph_client,
+                posthog_privacy_mode,
+                sanitize_openai_response(kwargs.get("input")),
             ),
             "$ai_http_status": 200,
             "$ai_input_tokens": usage_stats.get("prompt_tokens", 0),

posthog/ai/openai/openai_async.py

@@ -2,6 +2,8 @@ import time
 import uuid
 from typing import Any, Dict, List, Optional
 
+from posthog.ai.types import TokenUsage
+
 try:
     import openai
 except ImportError:
@@ -9,11 +11,22 @@ except ImportError:
         "Please install the OpenAI SDK to use this feature: 'pip install openai'"
     )
 
+from posthog import setup
 from posthog.ai.utils import (
     call_llm_and_track_usage_async,
+    extract_available_tool_calls,
     get_model_params,
+    merge_usage_stats,
     with_privacy_mode,
 )
+from posthog.ai.openai.openai_converter import (
+    extract_openai_usage_from_chunk,
+    extract_openai_content_from_chunk,
+    extract_openai_tool_calls_from_chunk,
+    accumulate_openai_tool_calls,
+    format_openai_streaming_output,
+)
+from posthog.ai.sanitization import sanitize_openai, sanitize_openai_response
 from posthog.client import Client as PostHogClient
 
 
@@ -24,7 +37,7 @@ class AsyncOpenAI(openai.AsyncOpenAI):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             api_key: OpenAI API key.
@@ -32,8 +45,9 @@ class AsyncOpenAI(openai.AsyncOpenAI):
                             of the global posthog.
             **openai_config: Any additional keyword args to set on openai (e.g. organization="xxx").
         """
+
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
 
         # Store original objects after parent initialization (only if they exist)
         self._original_chat = getattr(self, "chat", None)
@@ -64,6 +78,7 @@ class WrappedResponses:
 
     def __getattr__(self, name):
         """Fallback to original responses object for any methods we don't explicitly handle."""
+
         return getattr(self._original, name)
 
     async def create(
@@ -111,45 +126,36 @@ class WrappedResponses:
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {}
+        usage_stats: TokenUsage = TokenUsage()
         final_content = []
+        model_from_response: Optional[str] = None
         response = await self._original.create(**kwargs)
 
         async def async_generator():
             nonlocal usage_stats
             nonlocal final_content  # noqa: F824
+            nonlocal model_from_response
 
             try:
                 async for chunk in response:
-                    if hasattr(chunk, "type") and chunk.type == "response.completed":
-                        res = chunk.response
-                        if res.output and len(res.output) > 0:
-                            final_content.append(res.output[0])
-
-                    if hasattr(chunk, "usage") and chunk.usage:
-                        usage_stats = {
-                            k: getattr(chunk.usage, k, 0)
-                            for k in [
-                                "input_tokens",
-                                "output_tokens",
-                                "total_tokens",
-                            ]
-                        }
-
-                        # Add support for cached tokens
-                        if hasattr(chunk.usage, "output_tokens_details") and hasattr(
-                            chunk.usage.output_tokens_details, "reasoning_tokens"
+                    # Extract model from response object in chunk (for stored prompts)
+                    if hasattr(chunk, "response") and chunk.response:
+                        if model_from_response is None and hasattr(
+                            chunk.response, "model"
                         ):
-                            usage_stats["reasoning_tokens"] = (
-                                chunk.usage.output_tokens_details.reasoning_tokens
-                            )
+                            model_from_response = chunk.response.model
 
-                        if hasattr(chunk.usage, "input_tokens_details") and hasattr(
-                            chunk.usage.input_tokens_details, "cached_tokens"
-                        ):
-                            usage_stats["cache_read_input_tokens"] = (
-                                chunk.usage.input_tokens_details.cached_tokens
-                            )
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_openai_usage_from_chunk(chunk, "responses")
+
+                    if chunk_usage:
+                        merge_usage_stats(usage_stats, chunk_usage)
+
+                    # Extract content from chunk
+                    content = extract_openai_content_from_chunk(chunk, "responses")
+
+                    if content is not None:
+                        final_content.append(content)
 
                     yield chunk
 
@@ -157,6 +163,7 @@ class WrappedResponses:
                 end_time = time.time()
                 latency = end_time - start_time
                 output = final_content
+
                 await self._capture_streaming_event(
                     posthog_distinct_id,
                     posthog_trace_id,
@@ -167,6 +174,8 @@ class WrappedResponses:
                     usage_stats,
                     latency,
                     output,
+                    extract_available_tool_calls("openai", kwargs),
+                    model_from_response,
                 )
 
         return async_generator()
@@ -179,25 +188,31 @@ class WrappedResponses:
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
         output: Any,
-        tool_calls: Optional[List[Dict[str, Any]]] = None,
+        available_tool_calls: Optional[List[Dict[str, Any]]] = None,
+        model_from_response: Optional[str] = None,
     ):
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
+        # Use model from kwargs, fallback to model from response
+        model = kwargs.get("model") or model_from_response or "unknown"
+
         event_properties = {
             "$ai_provider": "openai",
-            "$ai_model": kwargs.get("model"),
+            "$ai_model": model,
             "$ai_model_parameters": get_model_params(kwargs),
             "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("input")
+                self._client._ph_client,
+                posthog_privacy_mode,
+                sanitize_openai_response(kwargs.get("input")),
             ),
             "$ai_output_choices": with_privacy_mode(
                 self._client._ph_client,
                 posthog_privacy_mode,
-                output,
+                format_openai_streaming_output(output, "responses"),
             ),
             "$ai_http_status": 200,
             "$ai_input_tokens": usage_stats.get("input_tokens", 0),
@@ -212,12 +227,17 @@ class WrappedResponses:
             **(posthog_properties or {}),
         }
 
-        if tool_calls:
-            event_properties["$ai_tools"] = with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                tool_calls,
-            )
+        # Add web search count if present
+        web_search_count = usage_stats.get("web_search_count")
+        if (
+            web_search_count is not None
+            and isinstance(web_search_count, int)
+            and web_search_count > 0
+        ):
+            event_properties["$ai_web_search_count"] = web_search_count
+
+        if available_tool_calls:
+            event_properties["$ai_tools"] = available_tool_calls
 
         if posthog_distinct_id is None:
             event_properties["$process_person_profile"] = False
@@ -341,9 +361,10 @@ class WrappedCompletions:
         **kwargs: Any,
     ):
         start_time = time.time()
-        usage_stats: Dict[str, int] = {}
+        usage_stats: TokenUsage = TokenUsage()
         accumulated_content = []
-        accumulated_tools = {}
+        accumulated_tool_calls: Dict[int, Dict[str, Any]] = {}
+        model_from_response: Optional[str] = None
 
         if "stream_options" not in kwargs:
             kwargs["stream_options"] = {}
@@ -353,70 +374,45 @@ class WrappedCompletions:
         async def async_generator():
             nonlocal usage_stats
             nonlocal accumulated_content  # noqa: F824
-            nonlocal accumulated_tools  # noqa: F824
+            nonlocal accumulated_tool_calls
+            nonlocal model_from_response
 
             try:
                 async for chunk in response:
-                    if hasattr(chunk, "usage") and chunk.usage:
-                        usage_stats = {
-                            k: getattr(chunk.usage, k, 0)
-                            for k in [
-                                "prompt_tokens",
-                                "completion_tokens",
-                                "total_tokens",
-                            ]
-                        }
+                    # Extract model from chunk (Chat Completions chunks have model field)
+                    if model_from_response is None and hasattr(chunk, "model"):
+                        model_from_response = chunk.model
 
-                        # Add support for cached tokens
-                        if hasattr(chunk.usage, "prompt_tokens_details") and hasattr(
-                            chunk.usage.prompt_tokens_details, "cached_tokens"
-                        ):
-                            usage_stats["cache_read_input_tokens"] = (
-                                chunk.usage.prompt_tokens_details.cached_tokens
-                            )
+                    # Extract usage stats from chunk
+                    chunk_usage = extract_openai_usage_from_chunk(chunk, "chat")
+                    if chunk_usage:
+                        merge_usage_stats(usage_stats, chunk_usage)
 
-                        if hasattr(chunk.usage, "output_tokens_details") and hasattr(
-                            chunk.usage.output_tokens_details, "reasoning_tokens"
-                        ):
-                            usage_stats["reasoning_tokens"] = (
-                                chunk.usage.output_tokens_details.reasoning_tokens
-                            )
+                    # Extract content from chunk
+                    content = extract_openai_content_from_chunk(chunk, "chat")
+                    if content is not None:
+                        accumulated_content.append(content)
 
-                    if (
-                        hasattr(chunk, "choices")
-                        and chunk.choices
-                        and len(chunk.choices) > 0
-                    ):
-                        if chunk.choices[0].delta and chunk.choices[0].delta.content:
-                            content = chunk.choices[0].delta.content
-                            if content:
-                                accumulated_content.append(content)
-
-                        # Process tool calls
-                        tool_calls = getattr(chunk.choices[0].delta, "tool_calls", None)
-                        if tool_calls:
-                            for tool_call in tool_calls:
-                                index = tool_call.index
-                                if index not in accumulated_tools:
-                                    accumulated_tools[index] = tool_call
-                                else:
-                                    # Append arguments for existing tool calls
-                                    if hasattr(tool_call, "function") and hasattr(
-                                        tool_call.function, "arguments"
-                                    ):
-                                        accumulated_tools[
-                                            index
-                                        ].function.arguments += (
-                                            tool_call.function.arguments
-                                        )
+                    # Extract and accumulate tool calls from chunk
+                    chunk_tool_calls = extract_openai_tool_calls_from_chunk(chunk)
+                    if chunk_tool_calls:
+                        accumulate_openai_tool_calls(
+                            accumulated_tool_calls, chunk_tool_calls
+                        )
 
                     yield chunk
 
             finally:
                 end_time = time.time()
                 latency = end_time - start_time
-                output = "".join(accumulated_content)
-                tools = list(accumulated_tools.values()) if accumulated_tools else None
+
+                # Convert accumulated tool calls dict to list
+                tool_calls_list = (
+                    list(accumulated_tool_calls.values())
+                    if accumulated_tool_calls
+                    else None
+                )
+
                 await self._capture_streaming_event(
                     posthog_distinct_id,
                     posthog_trace_id,
@@ -426,8 +422,10 @@ class WrappedCompletions:
                     kwargs,
                     usage_stats,
                     latency,
-                    output,
-                    tools,
+                    accumulated_content,
+                    tool_calls_list,
+                    extract_available_tool_calls("openai", kwargs),
+                    model_from_response,
                 )
 
         return async_generator()
@@ -440,29 +438,36 @@ class WrappedCompletions:
         posthog_privacy_mode: bool,
         posthog_groups: Optional[Dict[str, Any]],
         kwargs: Dict[str, Any],
-        usage_stats: Dict[str, int],
+        usage_stats: TokenUsage,
         latency: float,
         output: Any,
         tool_calls: Optional[List[Dict[str, Any]]] = None,
+        available_tool_calls: Optional[List[Dict[str, Any]]] = None,
+        model_from_response: Optional[str] = None,
     ):
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
+        # Use model from kwargs, fallback to model from response
+        model = kwargs.get("model") or model_from_response or "unknown"
+
         event_properties = {
             "$ai_provider": "openai",
-            "$ai_model": kwargs.get("model"),
+            "$ai_model": model,
             "$ai_model_parameters": get_model_params(kwargs),
             "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("messages")
+                self._client._ph_client,
+                posthog_privacy_mode,
+                sanitize_openai(kwargs.get("messages")),
             ),
             "$ai_output_choices": with_privacy_mode(
                 self._client._ph_client,
                 posthog_privacy_mode,
-                [{"content": output, "role": "assistant"}],
+                format_openai_streaming_output(output, "chat", tool_calls),
             ),
             "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
-            "$ai_output_tokens": usage_stats.get("completion_tokens", 0),
+            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
+            "$ai_output_tokens": usage_stats.get("output_tokens", 0),
             "$ai_cache_read_input_tokens": usage_stats.get(
                 "cache_read_input_tokens", 0
             ),
@@ -473,12 +478,18 @@ class WrappedCompletions:
             **(posthog_properties or {}),
         }
 
-        if tool_calls:
-            event_properties["$ai_tools"] = with_privacy_mode(
-                self._client._ph_client,
-                posthog_privacy_mode,
-                tool_calls,
-            )
+        # Add web search count if present
+        web_search_count = usage_stats.get("web_search_count")
+
+        if (
+            web_search_count is not None
+            and isinstance(web_search_count, int)
+            and web_search_count > 0
+        ):
+            event_properties["$ai_web_search_count"] = web_search_count
+
+        if available_tool_calls:
+            event_properties["$ai_tools"] = available_tool_calls
 
         if posthog_distinct_id is None:
             event_properties["$process_person_profile"] = False
@@ -501,6 +512,7 @@ class WrappedEmbeddings:
 
     def __getattr__(self, name):
         """Fallback to original embeddings object for any methods we don't explicitly handle."""
+
         return getattr(self._original, name)
 
     async def create(
@@ -526,6 +538,7 @@ class WrappedEmbeddings:
         Returns:
             The response from OpenAI's embeddings.create call.
         """
+
         if posthog_trace_id is None:
             posthog_trace_id = str(uuid.uuid4())
 
@@ -534,12 +547,13 @@ class WrappedEmbeddings:
         end_time = time.time()
 
         # Extract usage statistics if available
-        usage_stats = {}
+        usage_stats: TokenUsage = TokenUsage()
+
         if hasattr(response, "usage") and response.usage:
-            usage_stats = {
-                "prompt_tokens": getattr(response.usage, "prompt_tokens", 0),
-                "total_tokens": getattr(response.usage, "total_tokens", 0),
-            }
+            usage_stats = TokenUsage(
+                input_tokens=getattr(response.usage, "prompt_tokens", 0),
+                output_tokens=getattr(response.usage, "completion_tokens", 0),
+            )
 
         latency = end_time - start_time
 
@@ -548,10 +562,12 @@ class WrappedEmbeddings:
             "$ai_provider": "openai",
             "$ai_model": kwargs.get("model"),
             "$ai_input": with_privacy_mode(
-                self._client._ph_client, posthog_privacy_mode, kwargs.get("input")
+                self._client._ph_client,
+                posthog_privacy_mode,
+                sanitize_openai_response(kwargs.get("input")),
             ),
             "$ai_http_status": 200,
-            "$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
+            "$ai_input_tokens": usage_stats.get("input_tokens", 0),
             "$ai_latency": latency,
             "$ai_trace_id": posthog_trace_id,
             "$ai_base_url": str(self._client.base_url),
@@ -582,6 +598,7 @@ class WrappedBeta:
 
     def __getattr__(self, name):
         """Fallback to original beta object for any methods we don't explicitly handle."""
+
         return getattr(self._original, name)
 
     @property
@@ -598,6 +615,7 @@ class WrappedBetaChat:
 
     def __getattr__(self, name):
         """Fallback to original beta chat object for any methods we don't explicitly handle."""
+
         return getattr(self._original, name)
 
     @property
@@ -614,6 +632,7 @@ class WrappedBetaCompletions:
 
     def __getattr__(self, name):
         """Fallback to original beta completions object for any methods we don't explicitly handle."""
+
         return getattr(self._original, name)
 
     async def parse(

posthog/ai/openai/openai_converter.py

@@ -0,0 +1,760 @@
+"""
+OpenAI-specific conversion utilities.
+
+This module handles the conversion of OpenAI API responses and inputs
+into standardized formats for PostHog tracking. It supports both
+Chat Completions API and Responses API formats.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from posthog.ai.types import (
+    FormattedContentItem,
+    FormattedFunctionCall,
+    FormattedImageContent,
+    FormattedMessage,
+    FormattedTextContent,
+    TokenUsage,
+)
+from posthog.ai.utils import serialize_raw_usage
+
+
+def format_openai_response(response: Any) -> List[FormattedMessage]:
+    """
+    Format an OpenAI response into standardized message format.
+
+    Handles both Chat Completions API and Responses API formats.
+
+    Args:
+        response: The response object from OpenAI API
+
+    Returns:
+        List of formatted messages with role and content
+    """
+
+    output: List[FormattedMessage] = []
+
+    if response is None:
+        return output
+
+    # Handle Chat Completions response format
+    if hasattr(response, "choices"):
+        content: List[FormattedContentItem] = []
+        role = "assistant"
+
+        for choice in response.choices:
+            if hasattr(choice, "message") and choice.message:
+                if choice.message.role:
+                    role = choice.message.role
+
+                if choice.message.content:
+                    content.append(
+                        {
+                            "type": "text",
+                            "text": choice.message.content,
+                        }
+                    )
+
+                if hasattr(choice.message, "tool_calls") and choice.message.tool_calls:
+                    for tool_call in choice.message.tool_calls:
+                        content.append(
+                            {
+                                "type": "function",
+                                "id": tool_call.id,
+                                "function": {
+                                    "name": tool_call.function.name,
+                                    "arguments": tool_call.function.arguments,
+                                },
+                            }
+                        )
+
+                # Handle audio output (gpt-4o-audio-preview)
+                if hasattr(choice.message, "audio") and choice.message.audio:
+                    # Convert Pydantic model to dict to capture all fields from OpenAI
+                    audio_dict = choice.message.audio.model_dump()
+                    content.append({"type": "audio", **audio_dict})
+
+        if content:
+            output.append(
+                {
+                    "role": role,
+                    "content": content,
+                }
+            )
+
+    # Handle Responses API format
+    if hasattr(response, "output"):
+        content = []
+        role = "assistant"
+
+        for item in response.output:
+            if item.type == "message":
+                role = item.role
+
+                if hasattr(item, "content") and isinstance(item.content, list):
+                    for content_item in item.content:
+                        if (
+                            hasattr(content_item, "type")
+                            and content_item.type == "output_text"
+                            and hasattr(content_item, "text")
+                        ):
+                            content.append(
+                                {
+                                    "type": "text",
+                                    "text": content_item.text,
+                                }
+                            )
+
+                        elif hasattr(content_item, "text"):
+                            content.append({"type": "text", "text": content_item.text})
+
+                        elif (
+                            hasattr(content_item, "type")
+                            and content_item.type == "input_image"
+                            and hasattr(content_item, "image_url")
+                        ):
+                            image_content: FormattedImageContent = {
+                                "type": "image",
+                                "image": content_item.image_url,
+                            }
+                            content.append(image_content)
+
+                elif hasattr(item, "content"):
+                    text_content = {"type": "text", "text": str(item.content)}
+                    content.append(text_content)
+
+            elif hasattr(item, "type") and item.type == "function_call":
+                content.append(
+                    {
+                        "type": "function",
+                        "id": getattr(item, "call_id", getattr(item, "id", "")),
+                        "function": {
+                            "name": item.name,
+                            "arguments": getattr(item, "arguments", {}),
+                        },
+                    }
+                )
+
+        if content:
+            output.append(
+                {
+                    "role": role,
+                    "content": content,
+                }
+            )
+
+    return output
+
+
+def format_openai_input(
+    messages: Optional[List[Dict[str, Any]]] = None, input_data: Optional[Any] = None
+) -> List[FormattedMessage]:
+    """
+    Format OpenAI input messages.
+
+    Handles both messages parameter (Chat Completions) and input parameter (Responses API).
+
+    Args:
+        messages: List of message dictionaries for Chat Completions API
+        input_data: Input data for Responses API
+
+    Returns:
+        List of formatted messages
+    """
+
+    formatted_messages: List[FormattedMessage] = []
+
+    # Handle Chat Completions API format
+    if messages is not None:
+        for msg in messages:
+            formatted_messages.append(
+                {
+                    "role": msg.get("role", "user"),
+                    "content": msg.get("content", ""),
+                }
+            )
+
+    # Handle Responses API format
+    if input_data is not None:
+        if isinstance(input_data, list):
+            for item in input_data:
+                role = "user"
+                content = ""
+
+                if isinstance(item, dict):
+                    role = item.get("role", "user")
+                    content = item.get("content", "")
+
+                elif isinstance(item, str):
+                    content = item
+
+                else:
+                    content = str(item)
+
+                formatted_messages.append({"role": role, "content": content})
+
+        elif isinstance(input_data, str):
+            formatted_messages.append({"role": "user", "content": input_data})
+
+        else:
+            formatted_messages.append({"role": "user", "content": str(input_data)})
+
+    return formatted_messages
+
+
+def extract_openai_tools(kwargs: Dict[str, Any]) -> Optional[Any]:
+    """
+    Extract tool definitions from OpenAI API kwargs.
+
+    Args:
+        kwargs: Keyword arguments passed to OpenAI API
+
+    Returns:
+        Tool definitions if present, None otherwise
+    """
+
+    # Check for tools parameter (newer API)
+    if "tools" in kwargs:
+        return kwargs["tools"]
+
+    # Check for functions parameter (older API)
+    if "functions" in kwargs:
+        return kwargs["functions"]
+
+    return None
+
+
+def format_openai_streaming_content(
+    accumulated_content: str, tool_calls: Optional[List[Dict[str, Any]]] = None
+) -> List[FormattedContentItem]:
+    """
+    Format content from OpenAI streaming response.
+
+    Used by streaming handlers to format accumulated content.
+
+    Args:
+        accumulated_content: Accumulated text content from streaming
+        tool_calls: Optional list of tool calls accumulated during streaming
+
+    Returns:
+        List of formatted content items
+    """
+    formatted: List[FormattedContentItem] = []
+
+    # Add text content if present
+    if accumulated_content:
+        text_content: FormattedTextContent = {
+            "type": "text",
+            "text": accumulated_content,
+        }
+        formatted.append(text_content)
+
+    # Add tool calls if present
+    if tool_calls:
+        for tool_call in tool_calls:
+            function_call: FormattedFunctionCall = {
+                "type": "function",
+                "id": tool_call.get("id"),
+                "function": tool_call.get("function", {}),
+            }
+            formatted.append(function_call)
+
+    return formatted
+
+
+def extract_openai_web_search_count(response: Any) -> int:
+    """
+    Extract web search count from OpenAI response.
+
+    Uses a two-tier detection strategy:
+    1. Priority 1 (exact count): Check for output[].type == "web_search_call" (Responses API)
+    2. Priority 2 (binary detection): Check for various web search indicators:
+       - Root-level citations, search_results, or usage.search_context_size (Perplexity)
+       - Annotations with type "url_citation" in choices/output (including delta for streaming)
+
+    Args:
+        response: The response from OpenAI API
+
+    Returns:
+        Number of web search requests (exact count or binary 1/0)
+    """
+
+    # Priority 1: Check for exact count in Responses API output
+    if hasattr(response, "output"):
+        web_search_count = 0
+
+        for item in response.output:
+            if hasattr(item, "type") and item.type == "web_search_call":
+                web_search_count += 1
+
+        web_search_count = max(0, web_search_count)
+
+        if web_search_count > 0:
+            return web_search_count
+
+    # Priority 2: Binary detection (returns 1 or 0)
+
+    # Check root-level indicators (Perplexity)
+    if hasattr(response, "citations"):
+        citations = getattr(response, "citations")
+
+        if citations and len(citations) > 0:
+            return 1
+
+    if hasattr(response, "search_results"):
+        search_results = getattr(response, "search_results")
+
+        if search_results and len(search_results) > 0:
+            return 1
+
+    if hasattr(response, "usage") and hasattr(response.usage, "search_context_size"):
+        if response.usage.search_context_size:
+            return 1
+
+    # Check for url_citation annotations in choices (Chat Completions)
+    if hasattr(response, "choices"):
+        for choice in response.choices:
+            # Check message.annotations (non-streaming or final chunk)
+            if hasattr(choice, "message") and hasattr(choice.message, "annotations"):
+                annotations = choice.message.annotations
+
+                if annotations:
+                    for annotation in annotations:
+                        # Support both dict and object formats
+                        annotation_type = (
+                            annotation.get("type")
+                            if isinstance(annotation, dict)
+                            else getattr(annotation, "type", None)
+                        )
+
+                        if annotation_type == "url_citation":
+                            return 1
+
+            # Check delta.annotations (streaming chunks)
+            if hasattr(choice, "delta") and hasattr(choice.delta, "annotations"):
+                annotations = choice.delta.annotations
+
+                if annotations:
+                    for annotation in annotations:
+                        # Support both dict and object formats
+                        annotation_type = (
+                            annotation.get("type")
+                            if isinstance(annotation, dict)
+                            else getattr(annotation, "type", None)
+                        )
+
+                        if annotation_type == "url_citation":
+                            return 1
+
+    # Check for url_citation annotations in output (Responses API)
+    if hasattr(response, "output"):
+        for item in response.output:
+            if hasattr(item, "content") and isinstance(item.content, list):
+                for content_item in item.content:
+                    if hasattr(content_item, "annotations"):
+                        annotations = content_item.annotations
+
+                        if annotations:
+                            for annotation in annotations:
+                                # Support both dict and object formats
+                                annotation_type = (
+                                    annotation.get("type")
+                                    if isinstance(annotation, dict)
+                                    else getattr(annotation, "type", None)
+                                )
+
+                                if annotation_type == "url_citation":
+                                    return 1
+
+    return 0
+
+
+def extract_openai_usage_from_response(response: Any) -> TokenUsage:
+    """
+    Extract usage statistics from a full OpenAI response (non-streaming).
+    Handles both Chat Completions and Responses API.
+
+    Args:
+        response: The complete response from OpenAI API
+
+    Returns:
+        TokenUsage with standardized usage statistics
+    """
+    if not hasattr(response, "usage"):
+        return TokenUsage(input_tokens=0, output_tokens=0)
+
+    cached_tokens = 0
+    input_tokens = 0
+    output_tokens = 0
+    reasoning_tokens = 0
+
+    # Responses API format
+    if hasattr(response.usage, "input_tokens"):
+        input_tokens = response.usage.input_tokens
+    if hasattr(response.usage, "output_tokens"):
+        output_tokens = response.usage.output_tokens
+    if hasattr(response.usage, "input_tokens_details") and hasattr(
+        response.usage.input_tokens_details, "cached_tokens"
+    ):
+        cached_tokens = response.usage.input_tokens_details.cached_tokens
+    if hasattr(response.usage, "output_tokens_details") and hasattr(
+        response.usage.output_tokens_details, "reasoning_tokens"
+    ):
+        reasoning_tokens = response.usage.output_tokens_details.reasoning_tokens
+
+    # Chat Completions format
+    if hasattr(response.usage, "prompt_tokens"):
+        input_tokens = response.usage.prompt_tokens
+    if hasattr(response.usage, "completion_tokens"):
+        output_tokens = response.usage.completion_tokens
+    if hasattr(response.usage, "prompt_tokens_details") and hasattr(
+        response.usage.prompt_tokens_details, "cached_tokens"
+    ):
+        cached_tokens = response.usage.prompt_tokens_details.cached_tokens
+    if hasattr(response.usage, "completion_tokens_details") and hasattr(
+        response.usage.completion_tokens_details, "reasoning_tokens"
+    ):
+        reasoning_tokens = response.usage.completion_tokens_details.reasoning_tokens
+
+    result = TokenUsage(
+        input_tokens=input_tokens,
+        output_tokens=output_tokens,
+    )
+
+    if cached_tokens > 0:
+        result["cache_read_input_tokens"] = cached_tokens
+    if reasoning_tokens > 0:
+        result["reasoning_tokens"] = reasoning_tokens
+
+    web_search_count = extract_openai_web_search_count(response)
+    if web_search_count > 0:
+        result["web_search_count"] = web_search_count
+
+    # Capture raw usage metadata for backend processing
+    # Serialize to dict here in the converter (not in utils)
+    serialized = serialize_raw_usage(response.usage)
+    if serialized:
+        result["raw_usage"] = serialized
+
+    return result
+
+
+def extract_openai_usage_from_chunk(
+    chunk: Any, provider_type: str = "chat"
+) -> TokenUsage:
+    """
+    Extract usage statistics from an OpenAI streaming chunk.
+
+    Handles both Chat Completions and Responses API formats.
+
+    Args:
+        chunk: Streaming chunk from OpenAI API
+        provider_type: Either "chat" or "responses" to handle different API formats
+
+    Returns:
+        Dictionary of usage statistics
+    """
+
+    usage: TokenUsage = TokenUsage()
+
+    if provider_type == "chat":
+        # Extract web search count from the chunk before checking for usage
+        # Web search indicators (citations, annotations) can appear on any chunk,
+        # not just those with usage data
+        web_search_count = extract_openai_web_search_count(chunk)
+        if web_search_count > 0:
+            usage["web_search_count"] = web_search_count
+
+        if not hasattr(chunk, "usage") or not chunk.usage:
+            return usage
+
+        # Chat Completions API uses prompt_tokens and completion_tokens
+        # Standardize to input_tokens and output_tokens
+        usage["input_tokens"] = getattr(chunk.usage, "prompt_tokens", 0)
+        usage["output_tokens"] = getattr(chunk.usage, "completion_tokens", 0)
+
+        # Handle cached tokens
+        if hasattr(chunk.usage, "prompt_tokens_details") and hasattr(
+            chunk.usage.prompt_tokens_details, "cached_tokens"
+        ):
+            usage["cache_read_input_tokens"] = (
+                chunk.usage.prompt_tokens_details.cached_tokens
+            )
+
+        # Handle reasoning tokens
+        if hasattr(chunk.usage, "completion_tokens_details") and hasattr(
+            chunk.usage.completion_tokens_details, "reasoning_tokens"
+        ):
+            usage["reasoning_tokens"] = (
+                chunk.usage.completion_tokens_details.reasoning_tokens
+            )
+
+        # Capture raw usage metadata for backend processing
+        # Serialize to dict here in the converter (not in utils)
+        serialized = serialize_raw_usage(chunk.usage)
+        if serialized:
+            usage["raw_usage"] = serialized
+
+    elif provider_type == "responses":
+        # For Responses API, usage is only in chunk.response.usage for completed events
+        if hasattr(chunk, "type") and chunk.type == "response.completed":
+            if (
+                hasattr(chunk, "response")
+                and hasattr(chunk.response, "usage")
+                and chunk.response.usage
+            ):
+                response_usage = chunk.response.usage
+                usage["input_tokens"] = getattr(response_usage, "input_tokens", 0)
+                usage["output_tokens"] = getattr(response_usage, "output_tokens", 0)
+
+                # Handle cached tokens
+                if hasattr(response_usage, "input_tokens_details") and hasattr(
+                    response_usage.input_tokens_details, "cached_tokens"
+                ):
+                    usage["cache_read_input_tokens"] = (
+                        response_usage.input_tokens_details.cached_tokens
+                    )
+
+                # Handle reasoning tokens
+                if hasattr(response_usage, "output_tokens_details") and hasattr(
+                    response_usage.output_tokens_details, "reasoning_tokens"
+                ):
+                    usage["reasoning_tokens"] = (
+                        response_usage.output_tokens_details.reasoning_tokens
+                    )
+
+                # Extract web search count from the complete response
+                if hasattr(chunk, "response"):
+                    web_search_count = extract_openai_web_search_count(chunk.response)
+                    if web_search_count > 0:
+                        usage["web_search_count"] = web_search_count
+
+                # Capture raw usage metadata for backend processing
+                # Serialize to dict here in the converter (not in utils)
+                serialized = serialize_raw_usage(response_usage)
+                if serialized:
+                    usage["raw_usage"] = serialized
+
+    return usage
+
+
+def extract_openai_content_from_chunk(
+    chunk: Any, provider_type: str = "chat"
+) -> Optional[str]:
+    """
+    Extract content from an OpenAI streaming chunk.
+
+    Handles both Chat Completions and Responses API formats.
+
+    Args:
+        chunk: Streaming chunk from OpenAI API
+        provider_type: Either "chat" or "responses" to handle different API formats
+
+    Returns:
+        Text content if present, None otherwise
+    """
+
+    if provider_type == "chat":
+        # Chat Completions API format
+        if (
+            hasattr(chunk, "choices")
+            and chunk.choices
+            and len(chunk.choices) > 0
+            and chunk.choices[0].delta
+            and chunk.choices[0].delta.content
+        ):
+            return chunk.choices[0].delta.content
+
+    elif provider_type == "responses":
+        # Responses API format
+        if hasattr(chunk, "type") and chunk.type == "response.completed":
+            if hasattr(chunk, "response") and chunk.response:
+                res = chunk.response
+                if res.output and len(res.output) > 0:
+                    # Return the full output for responses
+                    return res.output[0]
+
+    return None
+
+
+def extract_openai_tool_calls_from_chunk(chunk: Any) -> Optional[List[Dict[str, Any]]]:
+    """
+    Extract tool calls from an OpenAI streaming chunk.
+
+    Args:
+        chunk: Streaming chunk from OpenAI API
+
+    Returns:
+        List of tool call deltas if present, None otherwise
+    """
+    if (
+        hasattr(chunk, "choices")
+        and chunk.choices
+        and len(chunk.choices) > 0
+        and chunk.choices[0].delta
+        and hasattr(chunk.choices[0].delta, "tool_calls")
+        and chunk.choices[0].delta.tool_calls
+    ):
+        tool_calls = []
+        for tool_call in chunk.choices[0].delta.tool_calls:
+            tc_dict = {
+                "index": getattr(tool_call, "index", None),
+            }
+
+            if hasattr(tool_call, "id") and tool_call.id:
+                tc_dict["id"] = tool_call.id
+
+            if hasattr(tool_call, "type") and tool_call.type:
+                tc_dict["type"] = tool_call.type
+
+            if hasattr(tool_call, "function") and tool_call.function:
+                function_dict = {}
+                if hasattr(tool_call.function, "name") and tool_call.function.name:
+                    function_dict["name"] = tool_call.function.name
+                if (
+                    hasattr(tool_call.function, "arguments")
+                    and tool_call.function.arguments
+                ):
+                    function_dict["arguments"] = tool_call.function.arguments
+                tc_dict["function"] = function_dict
+
+            tool_calls.append(tc_dict)
+        return tool_calls
+
+    return None
+
+
+def accumulate_openai_tool_calls(
+    accumulated_tool_calls: Dict[int, Dict[str, Any]],
+    chunk_tool_calls: List[Dict[str, Any]],
+) -> None:
+    """
+    Accumulate tool calls from streaming chunks.
+
+    OpenAI sends tool calls incrementally:
+    - First chunk has id, type, function.name and partial function.arguments
+    - Subsequent chunks have more function.arguments
+
+    Args:
+        accumulated_tool_calls: Dictionary mapping index to accumulated tool call data
+        chunk_tool_calls: List of tool call deltas from current chunk
+    """
+    for tool_call_delta in chunk_tool_calls:
+        index = tool_call_delta.get("index")
+        if index is None:
+            continue
+
+        # Initialize tool call if first time seeing this index
+        if index not in accumulated_tool_calls:
+            accumulated_tool_calls[index] = {
+                "id": "",
+                "type": "function",
+                "function": {
+                    "name": "",
+                    "arguments": "",
+                },
+            }
+
+        # Update with new data from delta
+        tc = accumulated_tool_calls[index]
+
+        if "id" in tool_call_delta and tool_call_delta["id"]:
+            tc["id"] = tool_call_delta["id"]
+
+        if "type" in tool_call_delta and tool_call_delta["type"]:
+            tc["type"] = tool_call_delta["type"]
+
+        if "function" in tool_call_delta:
+            func_delta = tool_call_delta["function"]
+            if "name" in func_delta and func_delta["name"]:
+                tc["function"]["name"] = func_delta["name"]
+            if "arguments" in func_delta and func_delta["arguments"]:
+                # Arguments are sent incrementally, concatenate them
+                tc["function"]["arguments"] += func_delta["arguments"]
+
+
+def format_openai_streaming_output(
+    accumulated_content: Any,
+    provider_type: str = "chat",
+    tool_calls: Optional[List[Dict[str, Any]]] = None,
+) -> List[FormattedMessage]:
+    """
+    Format the final output from OpenAI streaming.
+
+    Args:
+        accumulated_content: Accumulated content from streaming (string for chat, list for responses)
+        provider_type: Either "chat" or "responses" to handle different API formats
+        tool_calls: Optional list of accumulated tool calls
+
+    Returns:
+        List of formatted messages
+    """
+
+    if provider_type == "chat":
+        content_items: List[FormattedContentItem] = []
+
+        # Add text content if present
+        if isinstance(accumulated_content, str) and accumulated_content:
+            content_items.append({"type": "text", "text": accumulated_content})
+        elif isinstance(accumulated_content, list):
+            # If it's a list of strings, join them
+            text = "".join(str(item) for item in accumulated_content if item)
+            if text:
+                content_items.append({"type": "text", "text": text})
+
+        # Add tool calls if present
+        if tool_calls:
+            for tool_call in tool_calls:
+                if "function" in tool_call:
+                    function_call: FormattedFunctionCall = {
+                        "type": "function",
+                        "id": tool_call.get("id", ""),
+                        "function": tool_call["function"],
+                    }
+                    content_items.append(function_call)
+
+        # Return formatted message with content
+        if content_items:
+            return [{"role": "assistant", "content": content_items}]
+        else:
+            # Empty response
+            return [{"role": "assistant", "content": []}]
+
+    elif provider_type == "responses":
+        # Responses API: accumulated_content is a list of output items
+        if isinstance(accumulated_content, list) and accumulated_content:
+            # The output is already formatted, just return it
+            return accumulated_content
+        elif isinstance(accumulated_content, str):
+            return [
+                {
+                    "role": "assistant",
+                    "content": [{"type": "text", "text": accumulated_content}],
+                }
+            ]
+
+    # Fallback for any other format
+    return [
+        {
+            "role": "assistant",
+            "content": [{"type": "text", "text": str(accumulated_content)}],
+        }
+    ]
+
+
+def format_openai_streaming_input(
+    kwargs: Dict[str, Any], api_type: str = "chat"
+) -> Any:
+    """
+    Format OpenAI streaming input based on API type.
+
+    Args:
+        kwargs: Keyword arguments passed to OpenAI API
+        api_type: Either "chat" or "responses"
+
+    Returns:
+        Formatted input ready for PostHog tracking
+    """
+    from posthog.ai.utils import merge_system_prompt
+
+    return merge_system_prompt(kwargs, "openai")

posthog/ai/openai/openai_providers.py

@@ -15,7 +15,10 @@ from posthog.ai.openai.openai_async import WrappedBeta as AsyncWrappedBeta
 from posthog.ai.openai.openai_async import WrappedChat as AsyncWrappedChat
 from posthog.ai.openai.openai_async import WrappedEmbeddings as AsyncWrappedEmbeddings
 from posthog.ai.openai.openai_async import WrappedResponses as AsyncWrappedResponses
+from typing import Optional
+
 from posthog.client import Client as PostHogClient
+from posthog import setup
 
 
 class AzureOpenAI(openai.AzureOpenAI):
@@ -25,7 +28,7 @@ class AzureOpenAI(openai.AzureOpenAI):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             api_key: Azure OpenAI API key.
@@ -34,7 +37,7 @@ class AzureOpenAI(openai.AzureOpenAI):
             **openai_config: Any additional keyword args to set on Azure OpenAI (e.g. azure_endpoint="xxx").
         """
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
 
         # Store original objects after parent initialization (only if they exist)
         self._original_chat = getattr(self, "chat", None)
@@ -63,7 +66,7 @@ class AsyncAzureOpenAI(openai.AsyncAzureOpenAI):
 
     _ph_client: PostHogClient
 
-    def __init__(self, posthog_client: PostHogClient, **kwargs):
+    def __init__(self, posthog_client: Optional[PostHogClient] = None, **kwargs):
         """
         Args:
             api_key: Azure OpenAI API key.
@@ -72,7 +75,7 @@ class AsyncAzureOpenAI(openai.AsyncAzureOpenAI):
             **openai_config: Any additional keyword args to set on Azure OpenAI (e.g. azure_endpoint="xxx").
         """
         super().__init__(**kwargs)
-        self._ph_client = posthog_client
+        self._ph_client = posthog_client or setup()
 
         # Store original objects after parent initialization (only if they exist)
         self._original_chat = getattr(self, "chat", None)

posthog/ai/openai_agents/__init__.py

@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Union
+
+if TYPE_CHECKING:
+    from agents.tracing import Trace
+
+    from posthog.client import Client
+
+try:
+    import agents  # noqa: F401
+except ImportError:
+    raise ModuleNotFoundError(
+        "Please install the OpenAI Agents SDK to use this feature: 'pip install openai-agents'"
+    )
+
+from posthog.ai.openai_agents.processor import PostHogTracingProcessor
+
+__all__ = ["PostHogTracingProcessor", "instrument"]
+
+
+def instrument(
+    client: Optional[Client] = None,
+    distinct_id: Optional[Union[str, Callable[[Trace], Optional[str]]]] = None,
+    privacy_mode: bool = False,
+    groups: Optional[Dict[str, Any]] = None,
+    properties: Optional[Dict[str, Any]] = None,
+) -> PostHogTracingProcessor:
+    """
+    One-liner to instrument OpenAI Agents SDK with PostHog tracing.
+
+    This registers a PostHogTracingProcessor with the OpenAI Agents SDK,
+    automatically capturing traces, spans, and LLM generations.
+
+    Args:
+        client: Optional PostHog client instance. If not provided, uses the default client.
+        distinct_id: Optional distinct ID to associate with all traces.
+            Can also be a callable that takes a trace and returns a distinct ID.
+        privacy_mode: If True, redacts input/output content from events.
+        groups: Optional PostHog groups to associate with events.
+        properties: Optional additional properties to include with all events.
+
+    Returns:
+        PostHogTracingProcessor: The registered processor instance.
+
+    Example:
+        ```python
+        from posthog.ai.openai_agents import instrument
+
+        # Simple setup
+        instrument(distinct_id="user@example.com")
+
+        # With custom properties
+        instrument(
+            distinct_id="user@example.com",
+            privacy_mode=True,
+            properties={"environment": "production"}
+        )
+
+        # Now run agents as normal - traces automatically sent to PostHog
+        from agents import Agent, Runner
+        agent = Agent(name="Assistant", instructions="You are helpful.")
+        result = Runner.run_sync(agent, "Hello!")
+        ```
+    """
+    from agents.tracing import add_trace_processor
+
+    processor = PostHogTracingProcessor(
+        client=client,
+        distinct_id=distinct_id,
+        privacy_mode=privacy_mode,
+        groups=groups,
+        properties=properties,
+    )
+    add_trace_processor(processor)
+    return processor

posthog/ai/openai_agents/processor.py

@@ -0,0 +1,863 @@
+import json
+import logging
+import time
+from datetime import datetime
+from typing import Any, Callable, Dict, Optional, Union
+
+from agents.tracing import Span, Trace
+from agents.tracing.processor_interface import TracingProcessor
+from agents.tracing.span_data import (
+    AgentSpanData,
+    CustomSpanData,
+    FunctionSpanData,
+    GenerationSpanData,
+    GuardrailSpanData,
+    HandoffSpanData,
+    MCPListToolsSpanData,
+    ResponseSpanData,
+    SpeechGroupSpanData,
+    SpeechSpanData,
+    TranscriptionSpanData,
+)
+
+from posthog import setup
+from posthog.client import Client
+
+log = logging.getLogger("posthog")
+
+
+def _ensure_serializable(obj: Any) -> Any:
+    """Ensure an object is JSON-serializable, converting to str as fallback.
+
+    Returns the original object if it's already serializable (dict, list, str,
+    int, etc.), or str(obj) for non-serializable types so that downstream
+    json.dumps() calls won't fail.
+    """
+    if obj is None:
+        return None
+    try:
+        json.dumps(obj)
+        return obj
+    except (TypeError, ValueError):
+        return str(obj)
+
+
+def _parse_iso_timestamp(iso_str: Optional[str]) -> Optional[float]:
+    """Parse ISO timestamp to Unix timestamp."""
+    if not iso_str:
+        return None
+    try:
+        dt = datetime.fromisoformat(iso_str.replace("Z", "+00:00"))
+        return dt.timestamp()
+    except (ValueError, AttributeError):
+        return None
+
+
+class PostHogTracingProcessor(TracingProcessor):
+    """
+    A tracing processor that sends OpenAI Agents SDK traces to PostHog.
+
+    This processor implements the TracingProcessor interface from the OpenAI Agents SDK
+    and maps agent traces, spans, and generations to PostHog's LLM analytics events.
+
+    Example:
+        ```python
+        from agents import Agent, Runner
+        from agents.tracing import add_trace_processor
+        from posthog.ai.openai_agents import PostHogTracingProcessor
+
+        # Create and register the processor
+        processor = PostHogTracingProcessor(
+            distinct_id="user@example.com",
+            privacy_mode=False,
+        )
+        add_trace_processor(processor)
+
+        # Run agents as normal - traces automatically sent to PostHog
+        agent = Agent(name="Assistant", instructions="You are helpful.")
+        result = Runner.run_sync(agent, "Hello!")
+        ```
+    """
+
+    def __init__(
+        self,
+        client: Optional[Client] = None,
+        distinct_id: Optional[Union[str, Callable[[Trace], Optional[str]]]] = None,
+        privacy_mode: bool = False,
+        groups: Optional[Dict[str, Any]] = None,
+        properties: Optional[Dict[str, Any]] = None,
+    ):
+        """
+        Initialize the PostHog tracing processor.
+
+        Args:
+            client: Optional PostHog client instance. If not provided, uses the default client.
+            distinct_id: Either a string distinct ID or a callable that takes a Trace
+                and returns a distinct ID. If not provided, uses the trace_id.
+            privacy_mode: If True, redacts input/output content from events.
+            groups: Optional PostHog groups to associate with all events.
+            properties: Optional additional properties to include with all events.
+        """
+        self._client = client or setup()
+        self._distinct_id = distinct_id
+        self._privacy_mode = privacy_mode
+        self._groups = groups or {}
+        self._properties = properties or {}
+
+        # Track span start times for latency calculation
+        self._span_start_times: Dict[str, float] = {}
+
+        # Track trace metadata for associating with spans
+        self._trace_metadata: Dict[str, Dict[str, Any]] = {}
+
+        # Max entries to prevent unbounded growth if on_span_end/on_trace_end
+        # is never called (e.g., due to an exception in the Agents SDK).
+        self._max_tracked_entries = 10000
+
+    def _get_distinct_id(self, trace: Optional[Trace]) -> Optional[str]:
+        """Resolve the distinct ID for a trace.
+
+        Returns the user-provided distinct ID (string or callable result),
+        or None if no user-provided ID is available. Callers should treat
+        None as a signal to use a fallback ID in personless mode.
+        """
+        if callable(self._distinct_id):
+            if trace:
+                result = self._distinct_id(trace)
+                if result:
+                    return str(result)
+            return None
+        elif self._distinct_id:
+            return str(self._distinct_id)
+        return None
+
+    def _with_privacy_mode(self, value: Any) -> Any:
+        """Apply privacy mode redaction if enabled."""
+        if self._privacy_mode or (
+            hasattr(self._client, "privacy_mode") and self._client.privacy_mode
+        ):
+            return None
+        return value
+
+    def _evict_stale_entries(self) -> None:
+        """Evict oldest entries if dicts exceed max size to prevent unbounded growth."""
+        if len(self._span_start_times) > self._max_tracked_entries:
+            # Remove oldest entries by start time
+            sorted_spans = sorted(self._span_start_times.items(), key=lambda x: x[1])
+            for span_id, _ in sorted_spans[: len(sorted_spans) // 2]:
+                del self._span_start_times[span_id]
+            log.debug(
+                "Evicted stale span start times (exceeded %d entries)",
+                self._max_tracked_entries,
+            )
+
+        if len(self._trace_metadata) > self._max_tracked_entries:
+            # Remove half the entries (oldest inserted via dict ordering in Python 3.7+)
+            keys = list(self._trace_metadata.keys())
+            for key in keys[: len(keys) // 2]:
+                del self._trace_metadata[key]
+            log.debug(
+                "Evicted stale trace metadata (exceeded %d entries)",
+                self._max_tracked_entries,
+            )
+
+    def _get_group_id(self, trace_id: str) -> Optional[str]:
+        """Get the group_id for a trace from stored metadata."""
+        if trace_id in self._trace_metadata:
+            return self._trace_metadata[trace_id].get("group_id")
+        return None
+
+    def _capture_event(
+        self,
+        event: str,
+        properties: Dict[str, Any],
+        distinct_id: Optional[str] = None,
+    ) -> None:
+        """Capture an event to PostHog with error handling.
+
+        Args:
+            distinct_id: The resolved distinct ID. When the user didn't provide
+                one, callers should pass ``user_distinct_id or fallback_id``
+                (matching the langchain/openai pattern) and separately set
+                ``$process_person_profile`` in properties.
+        """
+        try:
+            if not hasattr(self._client, "capture") or not callable(
+                self._client.capture
+            ):
+                return
+
+            final_properties = {
+                **properties,
+                **self._properties,
+            }
+
+            self._client.capture(
+                distinct_id=distinct_id or "unknown",
+                event=event,
+                properties=final_properties,
+                groups=self._groups,
+            )
+        except Exception as e:
+            log.debug(f"Failed to capture PostHog event: {e}")
+
+    def on_trace_start(self, trace: Trace) -> None:
+        """Called when a new trace begins. Stores metadata for spans; the $ai_trace event is emitted in on_trace_end."""
+        try:
+            self._evict_stale_entries()
+            trace_id = trace.trace_id
+            trace_name = trace.name
+            group_id = getattr(trace, "group_id", None)
+            metadata = getattr(trace, "metadata", None)
+
+            distinct_id = self._get_distinct_id(trace)
+
+            # Store trace metadata for later (used by spans and on_trace_end)
+            self._trace_metadata[trace_id] = {
+                "name": trace_name,
+                "group_id": group_id,
+                "metadata": metadata,
+                "distinct_id": distinct_id,
+                "start_time": time.time(),
+            }
+        except Exception as e:
+            log.debug(f"Error in on_trace_start: {e}")
+
+    def on_trace_end(self, trace: Trace) -> None:
+        """Called when a trace completes. Emits the $ai_trace event with full metadata."""
+        try:
+            trace_id = trace.trace_id
+
+            # Pop stored metadata (also cleans up)
+            trace_info = self._trace_metadata.pop(trace_id, {})
+            trace_name = trace_info.get("name") or trace.name
+            group_id = trace_info.get("group_id") or getattr(trace, "group_id", None)
+            metadata = trace_info.get("metadata") or getattr(trace, "metadata", None)
+            distinct_id = trace_info.get("distinct_id") or self._get_distinct_id(trace)
+
+            # Calculate trace-level latency
+            start_time = trace_info.get("start_time")
+            latency = (time.time() - start_time) if start_time else None
+
+            properties = {
+                "$ai_trace_id": trace_id,
+                "$ai_trace_name": trace_name,
+                "$ai_provider": "openai",
+                "$ai_framework": "openai-agents",
+            }
+
+            if latency is not None:
+                properties["$ai_latency"] = latency
+
+            # Include group_id for linking related traces (e.g., conversation threads)
+            if group_id:
+                properties["$ai_group_id"] = group_id
+
+            # Include trace metadata if present
+            if metadata:
+                properties["$ai_trace_metadata"] = _ensure_serializable(metadata)
+
+            if distinct_id is None:
+                properties["$process_person_profile"] = False
+
+            self._capture_event(
+                event="$ai_trace",
+                distinct_id=distinct_id or trace_id,
+                properties=properties,
+            )
+        except Exception as e:
+            log.debug(f"Error in on_trace_end: {e}")
+
+    def on_span_start(self, span: Span[Any]) -> None:
+        """Called when a new span begins."""
+        try:
+            self._evict_stale_entries()
+            span_id = span.span_id
+            self._span_start_times[span_id] = time.time()
+        except Exception as e:
+            log.debug(f"Error in on_span_start: {e}")
+
+    def on_span_end(self, span: Span[Any]) -> None:
+        """Called when a span completes."""
+        try:
+            span_id = span.span_id
+            trace_id = span.trace_id
+            parent_id = span.parent_id
+            span_data = span.span_data
+
+            # Calculate latency
+            start_time = self._span_start_times.pop(span_id, None)
+            if start_time:
+                latency = time.time() - start_time
+            else:
+                # Fall back to parsing timestamps
+                started = _parse_iso_timestamp(span.started_at)
+                ended = _parse_iso_timestamp(span.ended_at)
+                latency = (ended - started) if (started and ended) else 0
+
+            # Get user-provided distinct ID from trace metadata (resolved at trace start).
+            # None means no user-provided ID — use trace_id as fallback in personless mode,
+            # matching the langchain/openai pattern: `distinct_id or trace_id`.
+            trace_info = self._trace_metadata.get(trace_id, {})
+            distinct_id = trace_info.get("distinct_id") or self._get_distinct_id(None)
+
+            # Get group_id from trace metadata for linking
+            group_id = self._get_group_id(trace_id)
+
+            # Get error info if present
+            error_info = span.error
+            error_properties = {}
+            if error_info:
+                if isinstance(error_info, dict):
+                    error_message = error_info.get("message", str(error_info))
+                    error_type_raw = error_info.get("type", "")
+                else:
+                    error_message = str(error_info)
+                    error_type_raw = ""
+
+                # Categorize error type for cross-provider filtering/alerting
+                error_type = "unknown"
+                if (
+                    "ModelBehaviorError" in error_type_raw
+                    or "ModelBehaviorError" in error_message
+                ):
+                    error_type = "model_behavior_error"
+                elif "UserError" in error_type_raw or "UserError" in error_message:
+                    error_type = "user_error"
+                elif (
+                    "InputGuardrailTripwireTriggered" in error_type_raw
+                    or "InputGuardrailTripwireTriggered" in error_message
+                ):
+                    error_type = "input_guardrail_triggered"
+                elif (
+                    "OutputGuardrailTripwireTriggered" in error_type_raw
+                    or "OutputGuardrailTripwireTriggered" in error_message
+                ):
+                    error_type = "output_guardrail_triggered"
+                elif (
+                    "MaxTurnsExceeded" in error_type_raw
+                    or "MaxTurnsExceeded" in error_message
+                ):
+                    error_type = "max_turns_exceeded"
+
+                error_properties = {
+                    "$ai_is_error": True,
+                    "$ai_error": error_message,
+                    "$ai_error_type": error_type,
+                }
+
+            # Personless mode: no user-provided distinct_id, fallback to trace_id
+            if distinct_id is None:
+                error_properties["$process_person_profile"] = False
+                distinct_id = trace_id
+
+            # Dispatch based on span data type
+            if isinstance(span_data, GenerationSpanData):
+                self._handle_generation_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, FunctionSpanData):
+                self._handle_function_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, AgentSpanData):
+                self._handle_agent_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, HandoffSpanData):
+                self._handle_handoff_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, GuardrailSpanData):
+                self._handle_guardrail_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, ResponseSpanData):
+                self._handle_response_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, CustomSpanData):
+                self._handle_custom_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(
+                span_data, (TranscriptionSpanData, SpeechSpanData, SpeechGroupSpanData)
+            ):
+                self._handle_audio_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            elif isinstance(span_data, MCPListToolsSpanData):
+                self._handle_mcp_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+            else:
+                # Unknown span type - capture as generic span
+                self._handle_generic_span(
+                    span_data,
+                    trace_id,
+                    span_id,
+                    parent_id,
+                    latency,
+                    distinct_id,
+                    group_id,
+                    error_properties,
+                )
+
+        except Exception as e:
+            log.debug(f"Error in on_span_end: {e}")
+
+    def _base_properties(
+        self,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> Dict[str, Any]:
+        """Build the base properties dict shared by all span handlers."""
+        properties = {
+            "$ai_trace_id": trace_id,
+            "$ai_span_id": span_id,
+            "$ai_parent_id": parent_id,
+            "$ai_provider": "openai",
+            "$ai_framework": "openai-agents",
+            "$ai_latency": latency,
+            **error_properties,
+        }
+        if group_id:
+            properties["$ai_group_id"] = group_id
+        return properties
+
+    def _handle_generation_span(
+        self,
+        span_data: GenerationSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle LLM generation spans - maps to $ai_generation event."""
+        # Extract token usage
+        usage = span_data.usage or {}
+        input_tokens = usage.get("input_tokens") or usage.get("prompt_tokens") or 0
+        output_tokens = (
+            usage.get("output_tokens") or usage.get("completion_tokens") or 0
+        )
+
+        # Extract model config parameters
+        model_config = span_data.model_config or {}
+        model_params = {}
+        for param in [
+            "temperature",
+            "max_tokens",
+            "top_p",
+            "frequency_penalty",
+            "presence_penalty",
+        ]:
+            if param in model_config:
+                model_params[param] = model_config[param]
+
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_model": span_data.model,
+            "$ai_model_parameters": model_params if model_params else None,
+            "$ai_input": self._with_privacy_mode(_ensure_serializable(span_data.input)),
+            "$ai_output_choices": self._with_privacy_mode(
+                _ensure_serializable(span_data.output)
+            ),
+            "$ai_input_tokens": input_tokens,
+            "$ai_output_tokens": output_tokens,
+            "$ai_total_tokens": (input_tokens or 0) + (output_tokens or 0),
+        }
+
+        # Add optional token fields if present
+        if usage.get("reasoning_tokens"):
+            properties["$ai_reasoning_tokens"] = usage["reasoning_tokens"]
+        if usage.get("cache_read_input_tokens"):
+            properties["$ai_cache_read_input_tokens"] = usage["cache_read_input_tokens"]
+        if usage.get("cache_creation_input_tokens"):
+            properties["$ai_cache_creation_input_tokens"] = usage[
+                "cache_creation_input_tokens"
+            ]
+
+        self._capture_event("$ai_generation", properties, distinct_id)
+
+    def _handle_function_span(
+        self,
+        span_data: FunctionSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle function/tool call spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_data.name,
+            "$ai_span_type": "tool",
+            "$ai_input_state": self._with_privacy_mode(
+                _ensure_serializable(span_data.input)
+            ),
+            "$ai_output_state": self._with_privacy_mode(
+                _ensure_serializable(span_data.output)
+            ),
+        }
+
+        if span_data.mcp_data:
+            properties["$ai_mcp_data"] = _ensure_serializable(span_data.mcp_data)
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_agent_span(
+        self,
+        span_data: AgentSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle agent execution spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_data.name,
+            "$ai_span_type": "agent",
+        }
+
+        if span_data.handoffs:
+            properties["$ai_agent_handoffs"] = span_data.handoffs
+        if span_data.tools:
+            properties["$ai_agent_tools"] = span_data.tools
+        if span_data.output_type:
+            properties["$ai_agent_output_type"] = span_data.output_type
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_handoff_span(
+        self,
+        span_data: HandoffSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle agent handoff spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": f"{span_data.from_agent} -> {span_data.to_agent}",
+            "$ai_span_type": "handoff",
+            "$ai_handoff_from_agent": span_data.from_agent,
+            "$ai_handoff_to_agent": span_data.to_agent,
+        }
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_guardrail_span(
+        self,
+        span_data: GuardrailSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle guardrail execution spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_data.name,
+            "$ai_span_type": "guardrail",
+            "$ai_guardrail_triggered": span_data.triggered,
+        }
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_response_span(
+        self,
+        span_data: ResponseSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle OpenAI Response API spans - maps to $ai_generation event."""
+        response = span_data.response
+        response_id = response.id if response else None
+
+        # Try to extract usage from response
+        usage = getattr(response, "usage", None) if response else None
+        input_tokens = 0
+        output_tokens = 0
+        if usage:
+            input_tokens = getattr(usage, "input_tokens", 0) or 0
+            output_tokens = getattr(usage, "output_tokens", 0) or 0
+
+        # Try to extract model from response
+        model = getattr(response, "model", None) if response else None
+
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_model": model,
+            "$ai_response_id": response_id,
+            "$ai_input": self._with_privacy_mode(_ensure_serializable(span_data.input)),
+            "$ai_input_tokens": input_tokens,
+            "$ai_output_tokens": output_tokens,
+            "$ai_total_tokens": input_tokens + output_tokens,
+        }
+
+        # Extract output content from response
+        if response:
+            output_items = getattr(response, "output", None)
+            if output_items:
+                properties["$ai_output_choices"] = self._with_privacy_mode(
+                    _ensure_serializable(output_items)
+                )
+
+        self._capture_event("$ai_generation", properties, distinct_id)
+
+    def _handle_custom_span(
+        self,
+        span_data: CustomSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle custom user-defined spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_data.name,
+            "$ai_span_type": "custom",
+            "$ai_custom_data": self._with_privacy_mode(
+                _ensure_serializable(span_data.data)
+            ),
+        }
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_audio_span(
+        self,
+        span_data: Union[TranscriptionSpanData, SpeechSpanData, SpeechGroupSpanData],
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle audio-related spans (transcription, speech) - maps to $ai_span event."""
+        span_type = span_data.type  # "transcription", "speech", or "speech_group"
+
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_type,
+            "$ai_span_type": span_type,
+        }
+
+        # Add model info if available
+        if hasattr(span_data, "model") and span_data.model:
+            properties["$ai_model"] = span_data.model
+
+        # Add model config if available (pass-through property)
+        if hasattr(span_data, "model_config") and span_data.model_config:
+            properties["model_config"] = _ensure_serializable(span_data.model_config)
+
+        # Add time to first audio byte for speech spans (pass-through property)
+        if hasattr(span_data, "first_content_at") and span_data.first_content_at:
+            properties["first_content_at"] = span_data.first_content_at
+
+        # Add audio format info (pass-through properties)
+        if hasattr(span_data, "input_format"):
+            properties["audio_input_format"] = span_data.input_format
+        if hasattr(span_data, "output_format"):
+            properties["audio_output_format"] = span_data.output_format
+
+        # Add text input for TTS
+        if (
+            hasattr(span_data, "input")
+            and span_data.input
+            and isinstance(span_data.input, str)
+        ):
+            properties["$ai_input"] = self._with_privacy_mode(span_data.input)
+
+        # Don't include audio data (base64) - just metadata
+        if hasattr(span_data, "output") and isinstance(span_data.output, str):
+            # For transcription, output is the text
+            properties["$ai_output_state"] = self._with_privacy_mode(span_data.output)
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_mcp_span(
+        self,
+        span_data: MCPListToolsSpanData,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle MCP (Model Context Protocol) spans - maps to $ai_span event."""
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": f"mcp:{span_data.server}",
+            "$ai_span_type": "mcp_tools",
+            "$ai_mcp_server": span_data.server,
+            "$ai_mcp_tools": span_data.result,
+        }
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def _handle_generic_span(
+        self,
+        span_data: Any,
+        trace_id: str,
+        span_id: str,
+        parent_id: Optional[str],
+        latency: float,
+        distinct_id: str,
+        group_id: Optional[str],
+        error_properties: Dict[str, Any],
+    ) -> None:
+        """Handle unknown span types - maps to $ai_span event."""
+        span_type = getattr(span_data, "type", "unknown")
+
+        properties = {
+            **self._base_properties(
+                trace_id, span_id, parent_id, latency, group_id, error_properties
+            ),
+            "$ai_span_name": span_type,
+            "$ai_span_type": span_type,
+        }
+
+        # Try to export span data
+        if hasattr(span_data, "export"):
+            try:
+                exported = span_data.export()
+                properties["$ai_span_data"] = _ensure_serializable(exported)
+            except Exception:
+                pass
+
+        self._capture_event("$ai_span", properties, distinct_id)
+
+    def shutdown(self) -> None:
+        """Clean up resources when the application stops."""
+        try:
+            self._span_start_times.clear()
+            self._trace_metadata.clear()
+
+            # Flush the PostHog client if possible
+            if hasattr(self._client, "flush") and callable(self._client.flush):
+                self._client.flush()
+        except Exception as e:
+            log.debug(f"Error in shutdown: {e}")
+
+    def force_flush(self) -> None:
+        """Force immediate processing of any queued events."""
+        try:
+            if hasattr(self._client, "flush") and callable(self._client.flush):
+                self._client.flush()
+        except Exception as e:
+            log.debug(f"Error in force_flush: {e}")

posthog/ai/prompts.py

@@ -0,0 +1,286 @@
+"""
+Prompt management for PostHog AI SDK.
+
+Fetch and compile LLM prompts from PostHog with caching and fallback support.
+"""
+
+import logging
+import re
+import time
+import urllib.parse
+from typing import Any, Dict, Optional, Union
+
+from posthog.request import USER_AGENT, _get_session
+from posthog.utils import remove_trailing_slash
+
+log = logging.getLogger("posthog")
+
+APP_ENDPOINT = "https://us.posthog.com"
+DEFAULT_CACHE_TTL_SECONDS = 300  # 5 minutes
+
+PromptVariables = Dict[str, Union[str, int, float, bool]]
+
+
+class CachedPrompt:
+    """Cached prompt with metadata."""
+
+    def __init__(self, prompt: str, fetched_at: float):
+        self.prompt = prompt
+        self.fetched_at = fetched_at
+
+
+def _is_prompt_api_response(data: Any) -> bool:
+    """Check if the response is a valid prompt API response."""
+    return (
+        isinstance(data, dict)
+        and "prompt" in data
+        and isinstance(data.get("prompt"), str)
+    )
+
+
+class Prompts:
+    """
+    Fetch and compile LLM prompts from PostHog.
+
+    Can be initialized with a PostHog client or with direct options.
+
+    Examples:
+        ```python
+        from posthog import Posthog
+        from posthog.ai.prompts import Prompts
+
+        # With PostHog client
+        posthog = Posthog('phc_xxx', host='https://us.posthog.com', personal_api_key='phx_xxx')
+        prompts = Prompts(posthog)
+
+        # Or with direct options (no PostHog client needed)
+        prompts = Prompts(
+            personal_api_key='phx_xxx',
+            project_api_key='phc_xxx',
+            host='https://us.posthog.com',
+        )
+
+        # Fetch with caching and fallback
+        template = prompts.get('support-system-prompt', fallback='You are a helpful assistant.')
+
+        # Compile with variables
+        system_prompt = prompts.compile(template, {
+            'company': 'Acme Corp',
+            'tier': 'premium',
+        })
+        ```
+    """
+
+    def __init__(
+        self,
+        posthog: Optional[Any] = None,
+        *,
+        personal_api_key: Optional[str] = None,
+        project_api_key: Optional[str] = None,
+        host: Optional[str] = None,
+        default_cache_ttl_seconds: Optional[int] = None,
+    ):
+        """
+        Initialize Prompts.
+
+        Args:
+            posthog: PostHog client instance (optional if personal_api_key provided)
+            personal_api_key: Direct personal API key (optional if posthog provided)
+            project_api_key: Direct project API key (optional if posthog provided)
+            host: PostHog host (defaults to app endpoint)
+            default_cache_ttl_seconds: Default cache TTL (defaults to 300)
+        """
+        self._default_cache_ttl_seconds = (
+            default_cache_ttl_seconds or DEFAULT_CACHE_TTL_SECONDS
+        )
+        self._cache: Dict[str, CachedPrompt] = {}
+
+        if posthog is not None:
+            self._personal_api_key = getattr(posthog, "personal_api_key", None) or ""
+            self._project_api_key = getattr(posthog, "api_key", None) or ""
+            self._host = remove_trailing_slash(
+                getattr(posthog, "raw_host", None) or APP_ENDPOINT
+            )
+        else:
+            self._personal_api_key = personal_api_key or ""
+            self._project_api_key = project_api_key or ""
+            self._host = remove_trailing_slash(host or APP_ENDPOINT)
+
+    def get(
+        self,
+        name: str,
+        *,
+        cache_ttl_seconds: Optional[int] = None,
+        fallback: Optional[str] = None,
+    ) -> str:
+        """
+        Fetch a prompt by name from the PostHog API.
+
+        Caching behavior:
+        1. If cache is fresh, return cached value
+        2. If fetch fails and cache exists (stale), return stale cache with warning
+        3. If fetch fails and fallback provided, return fallback with warning
+        4. If fetch fails with no cache/fallback, raise exception
+
+        Args:
+            name: The name of the prompt to fetch
+            cache_ttl_seconds: Cache TTL in seconds (defaults to instance default)
+            fallback: Fallback prompt to use if fetch fails and no cache available
+
+        Returns:
+            The prompt string
+
+        Raises:
+            Exception: If the prompt cannot be fetched and no fallback is available
+        """
+        ttl = (
+            cache_ttl_seconds
+            if cache_ttl_seconds is not None
+            else self._default_cache_ttl_seconds
+        )
+
+        # Check cache first
+        cached = self._cache.get(name)
+        now = time.time()
+
+        if cached is not None:
+            is_fresh = (now - cached.fetched_at) < ttl
+
+            if is_fresh:
+                return cached.prompt
+
+        # Try to fetch from API
+        try:
+            prompt = self._fetch_prompt_from_api(name)
+            fetched_at = time.time()
+
+            # Update cache
+            self._cache[name] = CachedPrompt(prompt=prompt, fetched_at=fetched_at)
+
+            return prompt
+
+        except Exception as error:
+            # Fallback order:
+            # 1. Return stale cache (with warning)
+            if cached is not None:
+                log.warning(
+                    '[PostHog Prompts] Failed to fetch prompt "%s", using stale cache: %s',
+                    name,
+                    error,
+                )
+                return cached.prompt
+
+            # 2. Return fallback (with warning)
+            if fallback is not None:
+                log.warning(
+                    '[PostHog Prompts] Failed to fetch prompt "%s", using fallback: %s',
+                    name,
+                    error,
+                )
+                return fallback
+
+            # 3. Raise error
+            raise
+
+    def compile(self, prompt: str, variables: PromptVariables) -> str:
+        """
+        Replace {{variableName}} placeholders with values.
+
+        Unmatched variables are left unchanged.
+        Supports variable names with hyphens and dots (e.g., user-id, company.name).
+
+        Args:
+            prompt: The prompt template string
+            variables: Object containing variable values
+
+        Returns:
+            The compiled prompt string
+        """
+
+        def replace_variable(match: re.Match) -> str:
+            variable_name = match.group(1)
+
+            if variable_name in variables:
+                return str(variables[variable_name])
+
+            return match.group(0)
+
+        return re.sub(r"\{\{([\w.-]+)\}\}", replace_variable, prompt)
+
+    def clear_cache(self, name: Optional[str] = None) -> None:
+        """
+        Clear cached prompts.
+
+        Args:
+            name: Specific prompt to clear. If None, clears all cached prompts.
+        """
+        if name is not None:
+            self._cache.pop(name, None)
+        else:
+            self._cache.clear()
+
+    def _fetch_prompt_from_api(self, name: str) -> str:
+        """
+        Fetch prompt from PostHog API.
+
+        Endpoint: {host}/api/environments/@current/llm_prompts/name/{encoded_name}/?token={encoded_project_api_key}
+        Auth: Bearer {personal_api_key}
+
+        Args:
+            name: The name of the prompt to fetch
+
+        Returns:
+            The prompt string
+
+        Raises:
+            Exception: If the prompt cannot be fetched
+        """
+        if not self._personal_api_key:
+            raise Exception(
+                "[PostHog Prompts] personal_api_key is required to fetch prompts. "
+                "Please provide it when initializing the Prompts instance."
+            )
+        if not self._project_api_key:
+            raise Exception(
+                "[PostHog Prompts] project_api_key is required to fetch prompts. "
+                "Please provide it when initializing the Prompts instance."
+            )
+
+        encoded_name = urllib.parse.quote(name, safe="")
+        encoded_project_api_key = urllib.parse.quote(self._project_api_key, safe="")
+        url = f"{self._host}/api/environments/@current/llm_prompts/name/{encoded_name}/?token={encoded_project_api_key}"
+
+        headers = {
+            "Authorization": f"Bearer {self._personal_api_key}",
+            "User-Agent": USER_AGENT,
+        }
+
+        response = _get_session().get(url, headers=headers, timeout=10)
+
+        if not response.ok:
+            if response.status_code == 404:
+                raise Exception(f'[PostHog Prompts] Prompt "{name}" not found')
+
+            if response.status_code == 403:
+                raise Exception(
+                    f'[PostHog Prompts] Access denied for prompt "{name}". '
+                    "Check that your personal_api_key has the correct permissions and the LLM prompts feature is enabled."
+                )
+
+            raise Exception(
+                f'[PostHog Prompts] Failed to fetch prompt "{name}": HTTP {response.status_code}'
+            )
+
+        try:
+            data = response.json()
+        except Exception:
+            raise Exception(
+                f'[PostHog Prompts] Invalid response format for prompt "{name}"'
+            )
+
+        if not _is_prompt_api_response(data):
+            raise Exception(
+                f'[PostHog Prompts] Invalid response format for prompt "{name}"'
+            )
+
+        return data["prompt"]

posthog/ai/sanitization.py

@@ -0,0 +1,254 @@
+import os
+import re
+from typing import Any
+from urllib.parse import urlparse
+
+REDACTED_IMAGE_PLACEHOLDER = "[base64 image redacted]"
+
+
+def _is_multimodal_enabled() -> bool:
+    """Check if multimodal capture is enabled via environment variable."""
+    return os.environ.get("_INTERNAL_LLMA_MULTIMODAL", "").lower() in (
+        "true",
+        "1",
+        "yes",
+    )
+
+
+def is_base64_data_url(text: str) -> bool:
+    return re.match(r"^data:([^;]+);base64,", text) is not None
+
+
+def is_valid_url(text: str) -> bool:
+    try:
+        result = urlparse(text)
+        return bool(result.scheme and result.netloc)
+    except Exception:
+        pass
+
+    return text.startswith(("/", "./", "../"))
+
+
+def is_raw_base64(text: str) -> bool:
+    if is_valid_url(text):
+        return False
+
+    return len(text) > 20 and re.match(r"^[A-Za-z0-9+/]+=*$", text) is not None
+
+
+def redact_base64_data_url(value: Any) -> Any:
+    if _is_multimodal_enabled():
+        return value
+
+    if not isinstance(value, str):
+        return value
+
+    if is_base64_data_url(value):
+        return REDACTED_IMAGE_PLACEHOLDER
+
+    if is_raw_base64(value):
+        return REDACTED_IMAGE_PLACEHOLDER
+
+    return value
+
+
+def process_messages(messages: Any, transform_content_func) -> Any:
+    if not messages:
+        return messages
+
+    def process_content(content: Any) -> Any:
+        if isinstance(content, str):
+            return content
+
+        if not content:
+            return content
+
+        if isinstance(content, list):
+            return [transform_content_func(item) for item in content]
+
+        return transform_content_func(content)
+
+    def process_message(msg: Any) -> Any:
+        if not isinstance(msg, dict) or "content" not in msg:
+            return msg
+        return {**msg, "content": process_content(msg["content"])}
+
+    if isinstance(messages, list):
+        return [process_message(msg) for msg in messages]
+
+    return process_message(messages)
+
+
+def sanitize_openai_image(item: Any) -> Any:
+    if not isinstance(item, dict):
+        return item
+
+    if item.get("type") == "input_image" and isinstance(item.get("image_url"), str):
+        return {
+            **item,
+            "image_url": redact_base64_data_url(item["image_url"]),
+        }
+
+    if (
+        item.get("type") == "image_url"
+        and isinstance(item.get("image_url"), dict)
+        and "url" in item["image_url"]
+    ):
+        return {
+            **item,
+            "image_url": {
+                **item["image_url"],
+                "url": redact_base64_data_url(item["image_url"]["url"]),
+            },
+        }
+
+    if item.get("type") == "audio" and "data" in item:
+        if _is_multimodal_enabled():
+            return item
+        return {**item, "data": REDACTED_IMAGE_PLACEHOLDER}
+
+    return item
+
+
+def sanitize_openai_response_image(item: Any) -> Any:
+    if not isinstance(item, dict):
+        return item
+
+    if item.get("type") == "input_image" and "image_url" in item:
+        return {
+            **item,
+            "image_url": redact_base64_data_url(item["image_url"]),
+        }
+
+    return item
+
+
+def sanitize_anthropic_image(item: Any) -> Any:
+    if _is_multimodal_enabled():
+        return item
+
+    if not isinstance(item, dict):
+        return item
+
+    if (
+        item.get("type") == "image"
+        and isinstance(item.get("source"), dict)
+        and item["source"].get("type") == "base64"
+        and "data" in item["source"]
+    ):
+        return {
+            **item,
+            "source": {
+                **item["source"],
+                "data": REDACTED_IMAGE_PLACEHOLDER,
+            },
+        }
+
+    return item
+
+
+def sanitize_gemini_part(part: Any) -> Any:
+    if _is_multimodal_enabled():
+        return part
+
+    if not isinstance(part, dict):
+        return part
+
+    if (
+        "inline_data" in part
+        and isinstance(part["inline_data"], dict)
+        and "data" in part["inline_data"]
+    ):
+        return {
+            **part,
+            "inline_data": {
+                **part["inline_data"],
+                "data": REDACTED_IMAGE_PLACEHOLDER,
+            },
+        }
+
+    return part
+
+
+def process_gemini_item(item: Any) -> Any:
+    if not isinstance(item, dict):
+        return item
+
+    if "parts" in item and item["parts"]:
+        parts = item["parts"]
+        if isinstance(parts, list):
+            parts = [sanitize_gemini_part(part) for part in parts]
+        else:
+            parts = sanitize_gemini_part(parts)
+
+        return {**item, "parts": parts}
+
+    return item
+
+
+def sanitize_langchain_image(item: Any) -> Any:
+    if not isinstance(item, dict):
+        return item
+
+    if (
+        item.get("type") == "image_url"
+        and isinstance(item.get("image_url"), dict)
+        and "url" in item["image_url"]
+    ):
+        return {
+            **item,
+            "image_url": {
+                **item["image_url"],
+                "url": redact_base64_data_url(item["image_url"]["url"]),
+            },
+        }
+
+    if item.get("type") == "image" and "data" in item:
+        return {**item, "data": redact_base64_data_url(item["data"])}
+
+    if (
+        item.get("type") == "image"
+        and isinstance(item.get("source"), dict)
+        and "data" in item["source"]
+    ):
+        if _is_multimodal_enabled():
+            return item
+
+        return {
+            **item,
+            "source": {
+                **item["source"],
+                "data": REDACTED_IMAGE_PLACEHOLDER,
+            },
+        }
+
+    if item.get("type") == "media" and "data" in item:
+        return {**item, "data": redact_base64_data_url(item["data"])}
+
+    return item
+
+
+def sanitize_openai(data: Any) -> Any:
+    return process_messages(data, sanitize_openai_image)
+
+
+def sanitize_openai_response(data: Any) -> Any:
+    return process_messages(data, sanitize_openai_response_image)
+
+
+def sanitize_anthropic(data: Any) -> Any:
+    return process_messages(data, sanitize_anthropic_image)
+
+
+def sanitize_gemini(data: Any) -> Any:
+    if not data:
+        return data
+
+    if isinstance(data, list):
+        return [process_gemini_item(item) for item in data]
+
+    return process_gemini_item(data)
+
+
+def sanitize_langchain(data: Any) -> Any:
+    return process_messages(data, sanitize_langchain_image)

posthog/ai/types.py

@@ -0,0 +1,126 @@
+"""
+Common type definitions for PostHog AI SDK.
+
+These types are used for formatting messages and responses across different AI providers
+(Anthropic, OpenAI, Gemini, etc.) to ensure consistency in tracking and data structure.
+"""
+
+from typing import Any, Dict, List, Optional, TypedDict, Union
+
+
+class FormattedTextContent(TypedDict):
+    """Formatted text content item."""
+
+    type: str  # Literal["text"]
+    text: str
+
+
+class FormattedFunctionCall(TypedDict, total=False):
+    """Formatted function/tool call content item."""
+
+    type: str  # Literal["function"]
+    id: Optional[str]
+    function: Dict[str, Any]  # Contains 'name' and 'arguments'
+
+
+class FormattedImageContent(TypedDict):
+    """Formatted image content item."""
+
+    type: str  # Literal["image"]
+    image: str
+
+
+# Union type for all formatted content items
+FormattedContentItem = Union[
+    FormattedTextContent,
+    FormattedFunctionCall,
+    FormattedImageContent,
+    Dict[str, Any],  # Fallback for unknown content types
+]
+
+
+class FormattedMessage(TypedDict):
+    """
+    Standardized message format for PostHog tracking.
+
+    Used across all providers to ensure consistent message structure
+    when sending events to PostHog.
+    """
+
+    role: str
+    content: Union[str, List[FormattedContentItem], Any]
+
+
+class TokenUsage(TypedDict, total=False):
+    """
+    Token usage information for AI model responses.
+
+    Different providers may populate different fields.
+    """
+
+    input_tokens: int
+    output_tokens: int
+    cache_read_input_tokens: Optional[int]
+    cache_creation_input_tokens: Optional[int]
+    reasoning_tokens: Optional[int]
+    web_search_count: Optional[int]
+    raw_usage: Optional[Any]  # Raw provider usage metadata for backend processing
+
+
+class ProviderResponse(TypedDict, total=False):
+    """
+    Standardized provider response format.
+
+    Used for consistent response formatting across all providers.
+    """
+
+    messages: List[FormattedMessage]
+    usage: TokenUsage
+    error: Optional[str]
+
+
+class StreamingContentBlock(TypedDict, total=False):
+    """
+    Content block used during streaming to accumulate content.
+
+    Used for tracking text and function calls as they stream in.
+    """
+
+    type: str  # "text" or "function"
+    text: Optional[str]
+    id: Optional[str]
+    function: Optional[Dict[str, Any]]
+
+
+class ToolInProgress(TypedDict):
+    """
+    Tracks a tool/function call being accumulated during streaming.
+
+    Used by Anthropic to accumulate JSON input for tools.
+    """
+
+    block: StreamingContentBlock
+    input_string: str
+
+
+class StreamingEventData(TypedDict):
+    """
+    Standardized data for streaming events across all providers.
+
+    This type ensures consistent data structure when capturing streaming events,
+    with all provider-specific formatting already completed.
+    """
+
+    provider: str  # "openai", "anthropic", "gemini"
+    model: str
+    base_url: str
+    kwargs: Dict[str, Any]  # Original kwargs for tool extraction and special handling
+    formatted_input: Any  # Provider-formatted input ready for tracking
+    formatted_output: Any  # Provider-formatted output ready for tracking
+    usage_stats: TokenUsage
+    latency: float
+    distinct_id: Optional[str]
+    trace_id: Optional[str]
+    properties: Optional[Dict[str, Any]]
+    privacy_mode: bool
+    groups: Optional[Dict[str, Any]]

posthog/args.py

@@ -0,0 +1,71 @@
+from typing import TypedDict, Optional, Any, Dict, Union, Tuple, Type
+from types import TracebackType
+from typing_extensions import NotRequired  # For Python < 3.11 compatibility
+from datetime import datetime
+import numbers
+from uuid import UUID
+
+from posthog.types import SendFeatureFlagsOptions
+
+ID_TYPES = Union[numbers.Number, str, UUID, int]
+
+
+class OptionalCaptureArgs(TypedDict):
+    """Optional arguments for the capture method.
+
+    Args:
+        distinct_id: Unique identifier for the person associated with this event. If not set, the context
+            distinct_id is used, if available, otherwise a UUID is generated, and the event is marked
+            as personless. Setting context-level distinct_id's is recommended.
+        properties: Dictionary of properties to track with the event
+        timestamp: When the event occurred (defaults to current time)
+        uuid: Unique identifier for this specific event. If not provided, one is generated. The event
+            UUID is returned, so you can correlate it with actions in your app (like showing users an
+            error ID if you capture an exception).
+        groups: Group identifiers to associate with this event (format: {group_type: group_key})
+        send_feature_flags: Whether to include currently active feature flags in the event properties.
+            Can be a boolean (True/False) or a SendFeatureFlagsOptions object for advanced configuration.
+            Defaults to False.
+        disable_geoip: Whether to disable GeoIP lookup for this event. Defaults to False.
+    """
+
+    distinct_id: NotRequired[Optional[ID_TYPES]]
+    properties: NotRequired[Optional[Dict[str, Any]]]
+    timestamp: NotRequired[Optional[Union[datetime, str]]]
+    uuid: NotRequired[Optional[str]]
+    groups: NotRequired[Optional[Dict[str, str]]]
+    send_feature_flags: NotRequired[
+        Optional[Union[bool, SendFeatureFlagsOptions]]
+    ]  # Updated to support both boolean and options object
+    disable_geoip: NotRequired[
+        Optional[bool]
+    ]  # As above, optional so we can tell if the user is intentionally overriding a client setting or not
+
+
+class OptionalSetArgs(TypedDict):
+    """Optional arguments for the set method.
+
+    Args:
+        distinct_id: Unique identifier for the user to set properties on. If not set, the context
+            distinct_id is used, if available, otherwise this function does nothing. Setting
+            context-level distinct_id's is recommended.
+        properties: Dictionary of properties to set on the person
+        timestamp: When the properties were set (defaults to current time)
+        uuid: Unique identifier for this operation. If not provided, one is generated. This
+            UUID is returned, so you can correlate it with actions in your app.
+        disable_geoip: Whether to disable GeoIP lookup for this operation. Defaults to False.
+    """
+
+    distinct_id: NotRequired[Optional[ID_TYPES]]
+    properties: NotRequired[Optional[Dict[str, Any]]]
+    timestamp: NotRequired[Optional[Union[datetime, str]]]
+    uuid: NotRequired[Optional[str]]
+    disable_geoip: NotRequired[Optional[bool]]
+
+
+ExcInfo = Union[
+    Tuple[Type[BaseException], BaseException, Optional[TracebackType]],
+    Tuple[None, None, None],
+]
+
+ExceptionArg = Union[BaseException, ExcInfo]

posthog/consumer.py

@@ -3,8 +3,6 @@ import logging
 import time
 from threading import Thread
 
-import backoff
-
 from posthog.request import APIError, DatetimeSerializer, batch_post
 
 try:
@@ -84,12 +82,16 @@ class Consumer(Thread):
             self.log.error("error uploading: %s", e)
             success = False
             if self.on_error:
-                self.on_error(e, batch)
+                try:
+                    self.on_error(e, batch)
+                except Exception as e:
+                    self.log.error("on_error handler failed: %s", e)
         finally:
             # mark items as acknowledged from queue
             for item in batch:
                 self.queue.task_done()
-            return success
+
+        return success
 
     def next(self):
         """Return the next batch of items to upload."""
@@ -124,29 +126,41 @@ class Consumer(Thread):
     def request(self, batch):
         """Attempt to upload the batch and retry before raising an error"""
 
-        def fatal_exception(exc):
+        def is_retryable(exc):
             if isinstance(exc, APIError):
                 # retry on server errors and client errors
-                # with 429 status code (rate limited),
+                # with 408 (request timeout) or 429 (rate limited),
                 # don't retry on other client errors
                 if exc.status == "N/A":
                     return False
-                return (400 <= exc.status < 500) and exc.status != 429
+                return not ((400 <= exc.status < 500) and exc.status not in (408, 429))
             else:
                 # retry on all other errors (eg. network)
-                return False
+                return True
 
-        @backoff.on_exception(
-            backoff.expo, Exception, max_tries=self.retries + 1, giveup=fatal_exception
-        )
-        def send_request():
-            batch_post(
-                self.api_key,
-                self.host,
-                gzip=self.gzip,
-                timeout=self.timeout,
-                batch=batch,
-                historical_migration=self.historical_migration,
-            )
+        last_exc = None
+        for attempt in range(self.retries + 1):
+            try:
+                batch_post(
+                    self.api_key,
+                    self.host,
+                    gzip=self.gzip,
+                    timeout=self.timeout,
+                    batch=batch,
+                    historical_migration=self.historical_migration,
+                )
+                return
+            except Exception as e:
+                last_exc = e
+                if not is_retryable(e):
+                    raise
+                if attempt < self.retries:
+                    # Respect Retry-After header if present, otherwise use exponential backoff
+                    retry_after = getattr(e, "retry_after", None)
+                    if retry_after and retry_after > 0:
+                        time.sleep(retry_after)
+                    else:
+                        time.sleep(min(2**attempt, 30))
 
-        send_request()
+        if last_exc:
+            raise last_exc

posthog/contexts.py

@@ -1,6 +1,10 @@
 import contextvars
 from contextlib import contextmanager
-from typing import Optional, Any, Callable, Dict, TypeVar, cast
+from typing import Optional, Any, Callable, Dict, TypeVar, cast, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    # To avoid circular imports
+    from posthog.client import Client
 
 
 class ContextScope:
@@ -9,13 +13,19 @@ class ContextScope:
         parent=None,
         fresh: bool = False,
         capture_exceptions: bool = True,
+        client: Optional["Client"] = None,
     ):
+        self.client: Optional[Client] = client
         self.parent = parent
         self.fresh = fresh
         self.capture_exceptions = capture_exceptions
         self.session_id: Optional[str] = None
         self.distinct_id: Optional[str] = None
+        self.device_id: Optional[str] = None
         self.tags: Dict[str, Any] = {}
+        self.capture_exception_code_variables: Optional[bool] = None
+        self.code_variables_mask_patterns: Optional[list] = None
+        self.code_variables_ignore_patterns: Optional[list] = None
 
     def set_session_id(self, session_id: str):
         self.session_id = session_id
@@ -23,9 +33,21 @@ class ContextScope:
     def set_distinct_id(self, distinct_id: str):
         self.distinct_id = distinct_id
 
+    def set_device_id(self, device_id: str):
+        self.device_id = device_id
+
     def add_tag(self, key: str, value: Any):
         self.tags[key] = value
 
+    def set_capture_exception_code_variables(self, enabled: bool):
+        self.capture_exception_code_variables = enabled
+
+    def set_code_variables_mask_patterns(self, mask_patterns: list):
+        self.code_variables_mask_patterns = mask_patterns
+
+    def set_code_variables_ignore_patterns(self, ignore_patterns: list):
+        self.code_variables_ignore_patterns = ignore_patterns
+
     def get_parent(self):
         return self.parent
 
@@ -43,15 +65,42 @@ class ContextScope:
             return self.parent.get_distinct_id()
         return None
 
+    def get_device_id(self) -> Optional[str]:
+        if self.device_id is not None:
+            return self.device_id
+        if self.parent is not None and not self.fresh:
+            return self.parent.get_device_id()
+        return None
+
     def collect_tags(self) -> Dict[str, Any]:
-        tags = self.tags.copy()
         if self.parent and not self.fresh:
             # We want child tags to take precedence over parent tags,
-            # so we can't use a simple update here, instead collecting
-            # the parent tags and then updating with the child tags.
-            new_tags = self.parent.collect_tags()
-            tags.update(new_tags)
-        return tags
+            # so collect parent tags first, then update with child tags.
+            tags = self.parent.collect_tags()
+            tags.update(self.tags)
+            return tags
+        return self.tags.copy()
+
+    def get_capture_exception_code_variables(self) -> Optional[bool]:
+        if self.capture_exception_code_variables is not None:
+            return self.capture_exception_code_variables
+        if self.parent is not None and not self.fresh:
+            return self.parent.get_capture_exception_code_variables()
+        return None
+
+    def get_code_variables_mask_patterns(self) -> Optional[list]:
+        if self.code_variables_mask_patterns is not None:
+            return self.code_variables_mask_patterns
+        if self.parent is not None and not self.fresh:
+            return self.parent.get_code_variables_mask_patterns()
+        return None
+
+    def get_code_variables_ignore_patterns(self) -> Optional[list]:
+        if self.code_variables_ignore_patterns is not None:
+            return self.code_variables_ignore_patterns
+        if self.parent is not None and not self.fresh:
+            return self.parent.get_code_variables_ignore_patterns()
+        return None
 
 
 _context_stack: contextvars.ContextVar[Optional[ContextScope]] = contextvars.ContextVar(
@@ -64,7 +113,11 @@ def _get_current_context() -> Optional[ContextScope]:
 
 
 @contextmanager
-def new_context(fresh=False, capture_exceptions=True):
+def new_context(
+    fresh: bool = False,
+    capture_exceptions: bool = True,
+    client: Optional["Client"] = None,
+):
     """
     Create a new context scope that will be active for the duration of the with block.
     Any tags set within this scope will be isolated to this context. Any exceptions raised
@@ -77,34 +130,49 @@ def new_context(fresh=False, capture_exceptions=True):
         capture_exceptions: Whether to capture exceptions raised within the context (default: True).
                If True, captures exceptions and tags them with the context tags before propagating them.
                If False, exceptions will propagate without being tagged or captured.
+        client: Optional client instance to use for capturing exceptions (default: None).
+                If provided, the client will be used to capture exceptions within the context.
+                If not provided, the default (global) client will be used. Note that the passed
+                client is only used to capture exceptions within the context - other events captured
+                within the context via `Client.capture` or `posthog.capture` will still carry the context
+                state (tags, identity, session id), but will be captured by the client directly used (or
+                the global one, in the case of `posthog.capture`)
 
     Examples:
+        ```python
         # Inherit parent context tags
         with posthog.new_context():
             posthog.tag("request_id", "123")
             # Both this event and the exception will be tagged with the context tags
             posthog.capture("event_name", {"property": "value"})
             raise ValueError("Something went wrong")
-
+        ```
+        ```python
         # Start with fresh context (no inherited tags)
         with posthog.new_context(fresh=True):
             posthog.tag("request_id", "123")
             # Both this event and the exception will be tagged with the context tags
             posthog.capture("event_name", {"property": "value"})
             raise ValueError("Something went wrong")
+        ```
 
+    Category:
+        Contexts
     """
     from posthog import capture_exception
 
     current_context = _get_current_context()
-    new_context = ContextScope(current_context, fresh, capture_exceptions)
+    new_context = ContextScope(current_context, fresh, capture_exceptions, client)
     _context_stack.set(new_context)
 
     try:
         yield
     except Exception as e:
         if new_context.capture_exceptions:
-            capture_exception(e)
+            if new_context.client:
+                new_context.client.capture_exception(e)
+            else:
+                capture_exception(e)
         raise
     finally:
         _context_stack.set(new_context.get_parent())
@@ -112,22 +180,26 @@ def new_context(fresh=False, capture_exceptions=True):
 
 def tag(key: str, value: Any) -> None:
     """
-    Add a tag to the current context.
+    Add a tag to the current context. All tags are added as properties to any event, including exceptions, captured
+    within the context.
 
     Args:
         key: The tag key
         value: The tag value
 
     Example:
+        ```python
         posthog.tag("user_id", "123")
+        ```
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
         current_context.add_tag(key, value)
 
 
-# NOTE: we should probably also remove this - there's no reason for the user to ever
-# need to manually interact with the current tag set
 def get_tags() -> Dict[str, Any]:
     """
     Get all tags from the current context. Note, modifying
@@ -135,6 +207,9 @@ def get_tags() -> Dict[str, Any]:
 
     Returns:
         Dict of all tags in the current context
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
@@ -142,25 +217,20 @@ def get_tags() -> Dict[str, Any]:
     return {}
 
 
-# NOTE: We should probably remove this function - the way to clear scope context
-# is by entering a new, fresh context, rather than by clearing the tags or other
-# scope data directly.
-def clear_tags() -> None:
-    """Clear all tags in the current context. Does not clear parent tags"""
-    current_context = _get_current_context()
-    if current_context:
-        current_context.tags.clear()
-
-
 def identify_context(distinct_id: str) -> None:
     """
     Identify the current context with a distinct ID, associating all events captured in this or
     child contexts with the given distinct ID (unless identify_context is called again). This is overridden by
     distinct id's passed directly to posthog.capture and related methods (identify, set etc). Entering a
-    fresh context will clear the context-level distinct ID.
+    fresh context will clear the context-level distinct ID. The distinct-id passed should be uniquely associated
+    with one of your users. Events captured outside of a context, or in a context with no associated distinct
+    ID, will be assigned a random UUID, and captured as "personless".
 
     Args:
         distinct_id: The distinct ID to associate with the current context and its children.
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
@@ -175,6 +245,9 @@ def set_context_session(session_id: str) -> None:
 
     Args:
         session_id: The session ID to associate with the current context and its children. See https://posthog.com/docs/data/sessions
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
@@ -187,6 +260,9 @@ def get_context_session_id() -> Optional[str]:
 
     Returns:
         The session ID if set, None otherwise
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
@@ -200,6 +276,9 @@ def get_context_distinct_id() -> Optional[str]:
 
     Returns:
         The distinct ID if set, None otherwise
+
+    Category:
+        Contexts
     """
     current_context = _get_current_context()
     if current_context:
@@ -207,10 +286,91 @@ def get_context_distinct_id() -> Optional[str]:
     return None
 
 
+def set_context_device_id(device_id: str) -> None:
+    """
+    Set the device ID for the current context, associating all feature flag requests in this or
+    child contexts with the given device ID (unless set_context_device_id is called again).
+    Entering a fresh context will clear the context-level device ID.
+
+    Args:
+        device_id: The device ID to associate with the current context and its children.
+
+    Category:
+        Contexts
+    """
+    current_context = _get_current_context()
+    if current_context:
+        current_context.set_device_id(device_id)
+
+
+def get_context_device_id() -> Optional[str]:
+    """
+    Get the device ID for the current context.
+
+    Returns:
+        The device ID if set, None otherwise
+
+    Category:
+        Contexts
+    """
+    current_context = _get_current_context()
+    if current_context:
+        return current_context.get_device_id()
+    return None
+
+
+def set_capture_exception_code_variables_context(enabled: bool) -> None:
+    """
+    Set whether code variables are captured for the current context.
+    """
+    current_context = _get_current_context()
+    if current_context:
+        current_context.set_capture_exception_code_variables(enabled)
+
+
+def set_code_variables_mask_patterns_context(mask_patterns: list) -> None:
+    """
+    Variable names matching these patterns will be masked with *** when capturing code variables.
+    """
+    current_context = _get_current_context()
+    if current_context:
+        current_context.set_code_variables_mask_patterns(mask_patterns)
+
+
+def set_code_variables_ignore_patterns_context(ignore_patterns: list) -> None:
+    """
+    Variable names matching these patterns will be ignored completely when capturing code variables.
+    """
+    current_context = _get_current_context()
+    if current_context:
+        current_context.set_code_variables_ignore_patterns(ignore_patterns)
+
+
+def get_capture_exception_code_variables_context() -> Optional[bool]:
+    current_context = _get_current_context()
+    if current_context:
+        return current_context.get_capture_exception_code_variables()
+    return None
+
+
+def get_code_variables_mask_patterns_context() -> Optional[list]:
+    current_context = _get_current_context()
+    if current_context:
+        return current_context.get_code_variables_mask_patterns()
+    return None
+
+
+def get_code_variables_ignore_patterns_context() -> Optional[list]:
+    current_context = _get_current_context()
+    if current_context:
+        return current_context.get_code_variables_ignore_patterns()
+    return None
+
+
 F = TypeVar("F", bound=Callable[..., Any])
 
 
-def scoped(fresh=False, capture_exceptions=True):
+def scoped(fresh: bool = False, capture_exceptions: bool = True):
     """
     Decorator that creates a new context for the function. Simply wraps
     the function in a with posthog.new_context(): block.
@@ -230,6 +390,9 @@ def scoped(fresh=False, capture_exceptions=True):
             # If this raises an exception, it will be captured with tags
             # and then re-raised
             some_risky_function()
+
+    Category:
+        Contexts
     """
 
     def decorator(func: F) -> F:

posthog/exception_capture.py

@@ -6,47 +6,25 @@
 import logging
 import sys
 import threading
-from enum import Enum
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from posthog.client import Client
 
 
-class Integrations(str, Enum):
-    Django = "django"
-
-
 class ExceptionCapture:
     # TODO: Add client side rate limiting to prevent spamming the server with exceptions
 
     log = logging.getLogger("posthog")
 
-    def __init__(
-        self, client: "Client", integrations: Optional[List[Integrations]] = None
-    ):
+    def __init__(self, client: "Client"):
         self.client = client
         self.original_excepthook = sys.excepthook
         sys.excepthook = self.exception_handler
         threading.excepthook = self.thread_exception_handler
-        self.enabled_integrations = []
-
-        for integration in integrations or []:
-            # TODO: Maybe find a better way of enabling integrations
-            # This is very annoying currently if we had to add any configuration per integration
-            if integration == Integrations.Django:
-                try:
-                    from posthog.exception_integrations.django import DjangoIntegration
-
-                    enabled_integration = DjangoIntegration(self.exception_receiver)
-                    self.enabled_integrations.append(enabled_integration)
-                except Exception as e:
-                    self.log.exception(f"Failed to enable Django integration: {e}")
 
     def close(self):
         sys.excepthook = self.original_excepthook
-        for integration in self.enabled_integrations:
-            integration.uninstall()
 
     def exception_handler(self, exc_type, exc_value, exc_traceback):
         # don't affect default behaviour.
@@ -66,6 +44,6 @@ class ExceptionCapture:
     def capture_exception(self, exception, metadata=None):
         try:
             distinct_id = metadata.get("distinct_id") if metadata else None
-            self.client.capture_exception(exception, distinct_id)
+            self.client.capture_exception(exception, distinct_id=distinct_id)
         except Exception as e:
             self.log.exception(f"Failed to capture exception: {e}")

posthog/exception_integrations/__init__.py

@@ -1,5 +0,0 @@
-class IntegrationEnablingError(Exception):
-    """
-    The integration could not be enabled due to a user error like
-    `django` not being installed for the `DjangoIntegration`.
-    """

posthog/exception_integrations/django.py

@@ -1,117 +0,0 @@
-# Portions of this file are derived from getsentry/sentry-javascript by Software, Inc. dba Sentry
-# Licensed under the MIT License
-
-# 💖open source (under MIT License)
-
-import re
-import sys
-from typing import TYPE_CHECKING
-
-from posthog.exception_integrations import IntegrationEnablingError
-
-try:
-    from django import VERSION as DJANGO_VERSION
-    from django.core import signals
-
-except ImportError:
-    raise IntegrationEnablingError("Django not installed")
-
-
-if TYPE_CHECKING:
-    from typing import Any, Dict  # noqa: F401
-
-    from django.core.handlers.wsgi import WSGIRequest  # noqa: F401
-
-
-class DjangoIntegration:
-    # TODO: Abstract integrations one we have more and can see patterns
-    """
-    Autocapture errors from a Django application.
-    """
-
-    identifier = "django"
-
-    def __init__(self, capture_exception_fn=None):
-        if DJANGO_VERSION < (4, 2):
-            raise IntegrationEnablingError("Django 4.2 or newer is required.")
-
-        # TODO: Right now this seems too complicated / overkill for us, but seems like we can automatically plug in middlewares
-        # which is great for users (they don't need to do this) and everything should just work.
-        # We should consider this in the future, but for now we can just use the middleware and signals handlers.
-        # See: https://github.com/getsentry/sentry-python/blob/269d96d6e9821122fbff280e6a26956e5ed03c0b/sentry_sdk/integrations/django/__init__.py
-
-        self.capture_exception_fn = capture_exception_fn
-
-        def _got_request_exception(request=None, **kwargs):
-            # type: (WSGIRequest, **Any) -> None
-
-            extra_props = {}
-            if request is not None:
-                # get headers metadata
-                extra_props = DjangoRequestExtractor(request).extract_person_data()
-
-            self.capture_exception_fn(sys.exc_info(), extra_props)
-
-        signals.got_request_exception.connect(_got_request_exception)
-
-    def uninstall(self):
-        pass
-
-
-class DjangoRequestExtractor:
-    def __init__(self, request):
-        # type: (Any) -> None
-        self.request = request
-
-    def extract_person_data(self):
-        headers = self.headers()
-
-        # Extract traceparent and tracestate headers
-        traceparent = headers.get("Traceparent")
-        tracestate = headers.get("Tracestate")
-
-        # Extract the distinct_id from tracestate
-        distinct_id = None
-        if tracestate:
-            # TODO: Align on the format of the distinct_id in tracestate
-            # We can't have comma or equals in header values here, so maybe we should base64 encode it?
-            match = re.search(r"posthog-distinct-id=([^,]+)", tracestate)
-            if match:
-                distinct_id = match.group(1)
-
-        return {
-            **self.user(),
-            "distinct_id": distinct_id,
-            "ip": headers.get("X-Forwarded-For"),
-            "user_agent": headers.get("User-Agent"),
-            "traceparent": traceparent,
-            "$request_path": self.request.path,
-        }
-
-    def user(self):
-        user_data: dict[str, str] = {}
-
-        user = getattr(self.request, "user", None)
-
-        if user is None or not user.is_authenticated:
-            return user_data
-
-        try:
-            user_id = str(user.pk)
-            if user_id:
-                user_data.setdefault("$user_id", user_id)
-        except Exception:
-            pass
-
-        try:
-            email = str(user.email)
-            if email:
-                user_data.setdefault("email", email)
-        except Exception:
-            pass
-
-        return user_data
-
-    def headers(self):
-        # type: () -> Dict[str, str]
-        return dict(self.request.headers)

posthog/exception_utils.py

@@ -5,13 +5,32 @@
 # 💖open source (under MIT License)
 # We want to keep payloads as similar to Sentry as possible for easy interoperability
 
+import json
 import linecache
 import os
 import re
 import sys
 import types
 from datetime import datetime
-from typing import TYPE_CHECKING
+from types import FrameType, TracebackType  # noqa: F401
+from typing import (  # noqa: F401
+    TYPE_CHECKING,
+    Any,
+    Dict,
+    Iterator,
+    List,
+    Literal,
+    Optional,
+    Pattern,
+    Set,
+    Tuple,
+    TypedDict,
+    TypeVar,
+    Union,
+    cast,
+)
+
+from posthog.args import ExceptionArg, ExcInfo  # noqa: F401
 
 try:
     # Python 3.11
@@ -23,85 +42,106 @@ except ImportError:
 
 DEFAULT_MAX_VALUE_LENGTH = 1024
 
+DEFAULT_CODE_VARIABLES_MASK_PATTERNS = [
+    r"(?i)password",
+    r"(?i)secret",
+    r"(?i)passwd",
+    r"(?i)pwd",
+    r"(?i)api_key",
+    r"(?i)apikey",
+    r"(?i)auth",
+    r"(?i)credentials",
+    r"(?i)privatekey",
+    r"(?i)private_key",
+    r"(?i)token",
+    r"(?i)aws_access_key_id",
+    r"(?i)_pass",
+    r"(?i)sk_",
+    r"(?i)jwt",
+]
 
-if TYPE_CHECKING:
-    from types import FrameType, TracebackType
-    from typing import (  # noqa: F401
-        Any,
-        Callable,
-        Dict,
-        Iterator,
-        List,
-        Literal,
-        Optional,
-        Set,
-        Tuple,
-        Type,
-        TypedDict,
-        TypeVar,
-        Union,
-        cast,
-    )
+DEFAULT_CODE_VARIABLES_IGNORE_PATTERNS = [r"^__.*"]
 
-    ExcInfo = Union[
-        Tuple[Type[BaseException], BaseException, Optional[TracebackType]],
-        Tuple[None, None, None],
-    ]
-    LogLevelStr = Literal["fatal", "critical", "error", "warning", "info", "debug"]
+CODE_VARIABLES_REDACTED_VALUE = "$$_posthog_redacted_based_on_masking_rules_$$"
+CODE_VARIABLES_TOO_LONG_VALUE = "$$_posthog_value_too_long_$$"
 
-    Event = TypedDict(
-        "Event",
-        {
-            "breadcrumbs": Dict[
-                Literal["values"], List[Dict[str, Any]]
-            ],  # TODO: We can expand on this type
-            "check_in_id": str,
-            "contexts": Dict[str, Dict[str, object]],
-            "dist": str,
-            "duration": Optional[float],
-            "environment": str,
-            "errors": List[Dict[str, Any]],  # TODO: We can expand on this type
-            "event_id": str,
-            "exception": Dict[
-                Literal["values"], List[Dict[str, Any]]
-            ],  # TODO: We can expand on this type
-            # "extra": MutableMapping[str, object],
-            # "fingerprint": List[str],
-            "level": LogLevelStr,
-            # "logentry": Mapping[str, object],
-            "logger": str,
-            # "measurements": Dict[str, MeasurementValue],
-            "message": str,
-            "modules": Dict[str, str],
-            # "monitor_config": Mapping[str, object],
-            "monitor_slug": Optional[str],
-            "platform": Literal["python"],
-            "profile": object,
-            "release": str,
-            "request": Dict[str, object],
-            # "sdk": Mapping[str, object],
-            "server_name": str,
-            "spans": List[Dict[str, object]],
-            "stacktrace": Dict[
-                str, object
-            ],  # We access this key in the code, but I am unsure whether we ever set it
-            "start_timestamp": datetime,
-            "status": Optional[str],
-            # "tags": MutableMapping[
-            #     str, str
-            # ],  # Tags must be less than 200 characters each
-            "threads": Dict[
-                Literal["values"], List[Dict[str, Any]]
-            ],  # TODO: We can expand on this type
-            "timestamp": Optional[datetime],  # Must be set before sending the event
-            "transaction": str,
-            # "transaction_info": Mapping[str, Any],  # TODO: We can expand on this type
-            "type": Literal["check_in", "transaction"],
-            "user": Dict[str, object],
-            "_metrics_summary": Dict[str, object],
-        },
-        total=False,
-    )
+_MAX_VALUE_LENGTH_FOR_PATTERN_MATCH = 5_000
+_MAX_COLLECTION_ITEMS_TO_SCAN = 100
+_REGEX_METACHARACTERS = frozenset(r"\.^$*+?{}[]|()")
+
+DEFAULT_TOTAL_VARIABLES_SIZE_LIMIT = 20 * 1024
+
+
+class VariableSizeLimiter:
+    def __init__(self, max_size=DEFAULT_TOTAL_VARIABLES_SIZE_LIMIT):
+        self.max_size = max_size
+        self.current_size = 0
+
+    def can_add(self, size):
+        return self.current_size + size <= self.max_size
+
+    def add(self, size):
+        self.current_size += size
+
+    def get_remaining_space(self):
+        return self.max_size - self.current_size
+
+
+LogLevelStr = Literal["fatal", "critical", "error", "warning", "info", "debug"]
+
+Event = TypedDict(
+    "Event",
+    {
+        "breadcrumbs": Dict[
+            Literal["values"], List[Dict[str, Any]]
+        ],  # TODO: We can expand on this type
+        "check_in_id": str,
+        "contexts": Dict[str, Dict[str, object]],
+        "dist": str,
+        "duration": Optional[float],
+        "environment": str,
+        "errors": List[Dict[str, Any]],  # TODO: We can expand on this type
+        "event_id": str,
+        "exception": Dict[
+            Literal["values"], List[Dict[str, Any]]
+        ],  # TODO: We can expand on this type
+        # "extra": MutableMapping[str, object],
+        # "fingerprint": List[str],
+        "level": LogLevelStr,
+        # "logentry": Mapping[str, object],
+        "logger": str,
+        # "measurements": Dict[str, MeasurementValue],
+        "message": str,
+        "modules": Dict[str, str],
+        # "monitor_config": Mapping[str, object],
+        "monitor_slug": Optional[str],
+        "platform": Literal["python"],
+        "profile": object,
+        "release": str,
+        "request": Dict[str, object],
+        # "sdk": Mapping[str, object],
+        "server_name": str,
+        "spans": List[Dict[str, object]],
+        "stacktrace": Dict[
+            str, object
+        ],  # We access this key in the code, but I am unsure whether we ever set it
+        "start_timestamp": datetime,
+        "status": Optional[str],
+        # "tags": MutableMapping[
+        #     str, str
+        # ],  # Tags must be less than 200 characters each
+        "threads": Dict[
+            Literal["values"], List[Dict[str, Any]]
+        ],  # TODO: We can expand on this type
+        "timestamp": Optional[datetime],  # Must be set before sending the event
+        "transaction": str,
+        # "transaction_info": Mapping[str, Any],  # TODO: We can expand on this type
+        "type": Literal["check_in", "transaction"],
+        "user": Dict[str, object],
+        "_metrics_summary": Dict[str, object],
+    },
+    total=False,
+)
 
 
 epoch = datetime(1970, 1, 1)
@@ -362,12 +402,9 @@ def filename_for_module(module, abs_path):
 def serialize_frame(
     frame,
     tb_lineno=None,
-    include_local_variables=True,
-    include_source_context=True,
     max_value_length=None,
-    custom_repr=None,
 ):
-    # type: (FrameType, Optional[int], bool, bool, Optional[int], Optional[Callable[..., Optional[str]]]) -> Dict[str, Any]
+    # type: (FrameType, Optional[int], Optional[int]) -> Dict[str, Any]
     f_code = getattr(frame, "f_code", None)
     if not f_code:
         abs_path = None
@@ -392,45 +429,13 @@ def serialize_frame(
         "lineno": tb_lineno,
     }  # type: Dict[str, Any]
 
-    if include_source_context:
-        rv["pre_context"], rv["context_line"], rv["post_context"] = get_source_context(
-            frame, tb_lineno, max_value_length
-        )
-
-    if include_local_variables:
-        # TODO - we don't support local variables, yet
-        pass
+    rv["pre_context"], rv["context_line"], rv["post_context"] = get_source_context(
+        frame, tb_lineno, max_value_length
+    )
 
     return rv
 
 
-def current_stacktrace(
-    include_local_variables=True,  # type: bool
-    include_source_context=True,  # type: bool
-    max_value_length=None,  # type: Optional[int]
-):
-    # type: (...) -> Dict[str, Any]
-    __tracebackhide__ = True
-    frames = []
-
-    f = sys._getframe()  # type: Optional[FrameType]
-    while f is not None:
-        if not should_hide_frame(f):
-            frames.append(
-                serialize_frame(
-                    f,
-                    include_local_variables=include_local_variables,
-                    include_source_context=include_source_context,
-                    max_value_length=max_value_length,
-                )
-            )
-        f = f.f_back
-
-    frames.reverse()
-
-    return {"frames": frames, "type": "raw"}
-
-
 def get_errno(exc_value):
     # type: (BaseException) -> Optional[Any]
     return getattr(exc_value, "errno", None)
@@ -451,7 +456,6 @@ def single_exception_from_error_tuple(
     exc_type,  # type: Optional[type]
     exc_value,  # type: Optional[BaseException]
     tb,  # type: Optional[TracebackType]
-    client_options=None,  # type: Optional[Dict[str, Any]]
     mechanism=None,  # type: Optional[Dict[str, Any]]
     exception_id=None,  # type: Optional[int]
     parent_id=None,  # type: Optional[int]
@@ -499,25 +503,13 @@ def single_exception_from_error_tuple(
     exception_value["type"] = get_type_name(exc_type)
     exception_value["value"] = get_error_message(exc_value)
 
-    if client_options is None:
-        include_local_variables = True
-        include_source_context = True
-        max_value_length = DEFAULT_MAX_VALUE_LENGTH  # fallback
-        custom_repr = None
-    else:
-        include_local_variables = client_options["include_local_variables"]
-        include_source_context = client_options["include_source_context"]
-        max_value_length = client_options["max_value_length"]
-        custom_repr = client_options.get("custom_repr")
+    max_value_length = DEFAULT_MAX_VALUE_LENGTH  # fallback
 
     frames = [
         serialize_frame(
             tb.tb_frame,
             tb_lineno=tb.tb_lineno,
-            include_local_variables=include_local_variables,
-            include_source_context=include_source_context,
             max_value_length=max_value_length,
-            custom_repr=custom_repr,
         )
         for tb in iter_stacks(tb)
     ]
@@ -573,7 +565,6 @@ def exceptions_from_error(
     exc_type,  # type: Optional[type]
     exc_value,  # type: Optional[BaseException]
     tb,  # type: Optional[TracebackType]
-    client_options=None,  # type: Optional[Dict[str, Any]]
     mechanism=None,  # type: Optional[Dict[str, Any]]
     exception_id=0,  # type: int
     parent_id=0,  # type: int
@@ -589,7 +580,6 @@ def exceptions_from_error(
         exc_type=exc_type,
         exc_value=exc_value,
         tb=tb,
-        client_options=client_options,
         mechanism=mechanism,
         exception_id=exception_id,
         parent_id=parent_id,
@@ -617,7 +607,6 @@ def exceptions_from_error(
                 exc_type=type(cause),
                 exc_value=cause,
                 tb=getattr(cause, "__traceback__", None),
-                client_options=client_options,
                 mechanism=mechanism,
                 exception_id=exception_id,
                 source="__cause__",
@@ -638,7 +627,6 @@ def exceptions_from_error(
                 exc_type=type(context),
                 exc_value=context,
                 tb=getattr(context, "__traceback__", None),
-                client_options=client_options,
                 mechanism=mechanism,
                 exception_id=exception_id,
                 source="__context__",
@@ -653,7 +641,6 @@ def exceptions_from_error(
                 exc_type=type(e),
                 exc_value=e,
                 tb=getattr(e, "__traceback__", None),
-                client_options=client_options,
                 mechanism=mechanism,
                 exception_id=exception_id,
                 parent_id=parent_id,
@@ -666,7 +653,6 @@ def exceptions_from_error(
 
 def exceptions_from_error_tuple(
     exc_info,  # type: ExcInfo
-    client_options=None,  # type: Optional[Dict[str, Any]]
     mechanism=None,  # type: Optional[Dict[str, Any]]
 ):
     # type: (...) -> List[Dict[str, Any]]
@@ -681,7 +667,6 @@ def exceptions_from_error_tuple(
             exc_type=exc_type,
             exc_value=exc_value,
             tb=tb,
-            client_options=client_options,
             mechanism=mechanism,
             exception_id=0,
             parent_id=0,
@@ -691,9 +676,7 @@ def exceptions_from_error_tuple(
         exceptions = []
         for exc_type, exc_value, tb in walk_exception_chain(exc_info):
             exceptions.append(
-                single_exception_from_error_tuple(
-                    exc_type, exc_value, tb, client_options, mechanism
-                )
+                single_exception_from_error_tuple(exc_type, exc_value, tb, mechanism)
             )
 
     exceptions.reverse()
@@ -783,7 +766,7 @@ def set_in_app_in_frames(frames, in_app_exclude, in_app_include, project_root=No
 
 
 def exception_is_already_captured(error):
-    # type: (Union[BaseException, ExcInfo]) -> bool
+    # type: (ExceptionArg) -> bool
     if isinstance(error, BaseException):
         return hasattr(error, "__posthog_exception_captured")
     # Autocaptured exceptions are passed as a tuple from our system hooks,
@@ -796,19 +779,21 @@ def exception_is_already_captured(error):
         return False  # type: ignore[unreachable]
 
 
-def mark_exception_as_captured(error):
-    # type: (Union[BaseException, ExcInfo]) -> None
+def mark_exception_as_captured(error, uuid):
+    # type: (ExceptionArg, str) -> None
     if isinstance(error, BaseException):
         setattr(error, "__posthog_exception_captured", True)
+        setattr(error, "__posthog_exception_uuid", uuid)
     # Autocaptured exceptions are passed as a tuple from our system hooks,
     # the second item is the exception value (the first is the exception type)
     elif isinstance(error, tuple) and len(error) > 1:
         if error[1] is not None:
             setattr(error[1], "__posthog_exception_captured", True)
+            setattr(error[1], "__posthog_exception_uuid", uuid)
 
 
 def exc_info_from_error(error):
-    # type: (Union[BaseException, ExcInfo]) -> ExcInfo
+    # type: (ExceptionArg) -> ExcInfo
     if isinstance(error, tuple) and len(error) == 3:
         exc_type, exc_value, tb = error
     elif isinstance(error, BaseException):
@@ -865,27 +850,6 @@ def construct_artificial_traceback(e):
     setattr(e, "__traceback__", tb)
 
 
-def event_from_exception(
-    exc_info,  # type: Union[BaseException, ExcInfo]
-    client_options=None,  # type: Optional[Dict[str, Any]]
-    mechanism=None,  # type: Optional[Dict[str, Any]]
-):
-    # type: (...) -> Tuple[Event, Dict[str, Any]]
-    exc_info = exc_info_from_error(exc_info)
-    hint = event_hint_with_exc_info(exc_info)
-    return (
-        {
-            "level": "error",
-            "exception": {
-                "values": exceptions_from_error_tuple(
-                    exc_info, client_options, mechanism
-                )
-            },
-        },
-        hint,
-    )
-
-
 def _module_in_list(name, items):
     # type: (str | None, Optional[List[str]]) -> bool
     if name is None:
@@ -967,3 +931,258 @@ def strip_string(value, max_length=None):
             "rem": [["!limit", "x", max_length - 3, max_length]],
         },
     )
+
+
+def _extract_plain_substring(pattern):
+    # Matches inline flag groups like (?i), (?ai), (?ims), etc. that include the 'i' flag.
+    # Python regex flags: a=ASCII, i=IGNORECASE, L=LOCALE, m=MULTILINE, s=DOTALL, u=UNICODE, x=VERBOSE
+    inline_flags = re.match(r"^\(\?[aiLmsux]*i[aiLmsux]*\)", pattern)
+    if not inline_flags:
+        return None
+    remainder = pattern[inline_flags.end() :]
+    if not remainder or any(c in _REGEX_METACHARACTERS for c in remainder):
+        return None
+    return remainder.lower()
+
+
+def _compile_patterns(patterns):
+    if not patterns:
+        return None
+    substrings = []
+    regexes = []
+    for pattern in patterns:
+        simple = _extract_plain_substring(pattern)
+        if simple is not None:
+            substrings.append(simple)
+        else:
+            try:
+                regexes.append(re.compile(pattern))
+            except Exception:
+                pass
+    if not substrings and not regexes:
+        return None
+    return (substrings, regexes)
+
+
+def _pattern_matches(name, patterns):
+    if patterns is None:
+        return False
+    substrings, regexes = patterns
+    if substrings:
+        name_lower = name.lower()
+        for s in substrings:
+            if s in name_lower:
+                return True
+    for pattern in regexes:
+        if pattern.search(name):
+            return True
+    return False
+
+
+def _mask_sensitive_data(value, compiled_mask, _seen=None):
+    if not compiled_mask:
+        return value
+
+    if isinstance(value, (dict, list, tuple)):
+        if _seen is None:
+            _seen = set()
+        obj_id = id(value)
+        if obj_id in _seen:
+            return "<circular ref>"
+        _seen.add(obj_id)
+
+    if isinstance(value, dict):
+        if len(value) > _MAX_COLLECTION_ITEMS_TO_SCAN:
+            return CODE_VARIABLES_TOO_LONG_VALUE
+        result = {}
+        for k, v in value.items():
+            key_str = str(k) if not isinstance(k, str) else k
+            if len(key_str) > _MAX_VALUE_LENGTH_FOR_PATTERN_MATCH:
+                result[k] = CODE_VARIABLES_TOO_LONG_VALUE
+            elif _pattern_matches(key_str, compiled_mask):
+                result[k] = CODE_VARIABLES_REDACTED_VALUE
+            else:
+                result[k] = _mask_sensitive_data(v, compiled_mask, _seen)
+        return result
+    elif isinstance(value, (list, tuple)):
+        if len(value) > _MAX_COLLECTION_ITEMS_TO_SCAN:
+            return CODE_VARIABLES_TOO_LONG_VALUE
+        masked_items = [
+            _mask_sensitive_data(item, compiled_mask, _seen) for item in value
+        ]
+        return type(value)(masked_items)
+    elif isinstance(value, str):
+        if len(value) > _MAX_VALUE_LENGTH_FOR_PATTERN_MATCH:
+            return CODE_VARIABLES_TOO_LONG_VALUE
+        if _pattern_matches(value, compiled_mask):
+            return CODE_VARIABLES_REDACTED_VALUE
+        return value
+    else:
+        return value
+
+
+def _serialize_variable_value(value, limiter, max_length=1024, compiled_mask=None):
+    try:
+        if value is None:
+            result = "None"
+        elif isinstance(value, bool):
+            result = str(value)
+        elif isinstance(value, (int, float)):
+            result_size = len(str(value))
+            if not limiter.can_add(result_size):
+                return None
+            limiter.add(result_size)
+            return value
+        elif isinstance(value, str):
+            if len(value) > _MAX_VALUE_LENGTH_FOR_PATTERN_MATCH:
+                result = CODE_VARIABLES_TOO_LONG_VALUE
+            elif compiled_mask and _pattern_matches(value, compiled_mask):
+                result = CODE_VARIABLES_REDACTED_VALUE
+            else:
+                result = value
+        else:
+            masked_value = _mask_sensitive_data(value, compiled_mask)
+            result = json.dumps(masked_value)
+
+        if len(result) > max_length:
+            result = result[: max_length - 3] + "..."
+
+        result_size = len(result)
+        if not limiter.can_add(result_size):
+            return None
+        limiter.add(result_size)
+
+        return result
+    except Exception:
+        try:
+            result = repr(value)
+            if len(result) > max_length:
+                result = result[: max_length - 3] + "..."
+
+            result_size = len(result)
+            if not limiter.can_add(result_size):
+                return None
+            limiter.add(result_size)
+            return result
+        except Exception:
+            try:
+                fallback = f"<{type(value).__name__}>"
+                fallback_size = len(fallback)
+                if not limiter.can_add(fallback_size):
+                    return None
+                limiter.add(fallback_size)
+                return fallback
+            except Exception:
+                fallback = "<unserializable object>"
+                fallback_size = len(fallback)
+                if not limiter.can_add(fallback_size):
+                    return None
+                limiter.add(fallback_size)
+                return fallback
+
+
+def _is_simple_type(value):
+    return isinstance(value, (type(None), bool, int, float, str))
+
+
+def serialize_code_variables(
+    frame, limiter, mask_patterns=None, ignore_patterns=None, max_length=1024
+):
+    if mask_patterns is None:
+        mask_patterns = []
+    if ignore_patterns is None:
+        ignore_patterns = []
+
+    compiled_mask = _compile_patterns(mask_patterns)
+    compiled_ignore = _compile_patterns(ignore_patterns)
+
+    try:
+        local_vars = frame.f_locals.copy()
+    except Exception:
+        return {}
+
+    simple_vars = {}
+    complex_vars = {}
+
+    for name, value in local_vars.items():
+        if _pattern_matches(name, compiled_ignore):
+            continue
+
+        if _is_simple_type(value):
+            simple_vars[name] = value
+        else:
+            complex_vars[name] = value
+
+    result = {}
+
+    all_vars = {**simple_vars, **complex_vars}
+    ordered_names = list(sorted(simple_vars.keys())) + list(sorted(complex_vars.keys()))
+
+    for name in ordered_names:
+        value = all_vars[name]
+
+        if _pattern_matches(name, compiled_mask):
+            redacted_value = CODE_VARIABLES_REDACTED_VALUE
+            redacted_size = len(redacted_value)
+            if not limiter.can_add(redacted_size):
+                break
+            limiter.add(redacted_size)
+            result[name] = redacted_value
+        else:
+            serialized = _serialize_variable_value(
+                value, limiter, max_length, compiled_mask
+            )
+            if serialized is None:
+                break
+            result[name] = serialized
+
+    return result
+
+
+def try_attach_code_variables_to_frames(
+    all_exceptions, exc_info, mask_patterns, ignore_patterns
+):
+    try:
+        attach_code_variables_to_frames(
+            all_exceptions, exc_info, mask_patterns, ignore_patterns
+        )
+    except Exception:
+        pass
+
+
+def attach_code_variables_to_frames(
+    all_exceptions, exc_info, mask_patterns, ignore_patterns
+):
+    exc_type, exc_value, traceback = exc_info
+
+    if traceback is None:
+        return
+
+    tb_frames = list(iter_stacks(traceback))
+
+    if not tb_frames:
+        return
+
+    limiter = VariableSizeLimiter()
+
+    for exception in all_exceptions:
+        stacktrace = exception.get("stacktrace")
+        if not stacktrace or "frames" not in stacktrace:
+            continue
+
+        serialized_frames = stacktrace["frames"]
+
+        for serialized_frame, tb_item in zip(serialized_frames, tb_frames):
+            if not serialized_frame.get("in_app"):
+                continue
+
+            variables = serialize_code_variables(
+                tb_item.tb_frame,
+                limiter,
+                mask_patterns=mask_patterns,
+                ignore_patterns=ignore_patterns,
+                max_length=1024,
+            )
+
+            if variables:
+                serialized_frame["code_variables"] = variables

posthog/feature_flags.py

@@ -2,6 +2,7 @@ import datetime
 import hashlib
 import logging
 import re
+import warnings
 from typing import Optional
 
 from dateutil import parser
@@ -17,23 +18,59 @@ log = logging.getLogger("posthog")
 
 NONE_VALUES_ALLOWED_OPERATORS = ["is_not"]
 
+# All operators supported by match_property, grouped by category.
+EQUALITY_OPERATORS = ("exact", "is_not", "is_set", "is_not_set")
+STRING_OPERATORS = ("icontains", "not_icontains", "regex", "not_regex")
+NUMERIC_OPERATORS = ("gt", "gte", "lt", "lte")
+DATE_OPERATORS = ("is_date_before", "is_date_after")
+SEMVER_COMPARISON_OPERATORS = (
+    "semver_eq",
+    "semver_neq",
+    "semver_gt",
+    "semver_gte",
+    "semver_lt",
+    "semver_lte",
+)
+SEMVER_RANGE_OPERATORS = ("semver_tilde", "semver_caret", "semver_wildcard")
+SEMVER_OPERATORS = SEMVER_COMPARISON_OPERATORS + SEMVER_RANGE_OPERATORS
+
+PROPERTY_OPERATORS = (
+    EQUALITY_OPERATORS
+    + STRING_OPERATORS
+    + NUMERIC_OPERATORS
+    + DATE_OPERATORS
+    + SEMVER_OPERATORS
+)
+
 
 class InconclusiveMatchError(Exception):
     pass
 
 
-# This function takes a distinct_id and a feature flag key and returns a float between 0 and 1.
-# Given the same distinct_id and key, it'll always return the same float. These floats are
+class RequiresServerEvaluation(Exception):
+    """
+    Raised when feature flag evaluation requires server-side data that is not
+    available locally (e.g., static cohorts, experience continuity).
+
+    This error should propagate immediately to trigger API fallback, unlike
+    InconclusiveMatchError which allows trying other conditions.
+    """
+
+    pass
+
+
+# This function takes a bucketing value and a feature flag key and returns a float between 0 and 1.
+# Given the same bucketing value and key, it'll always return the same float. These floats are
 # uniformly distributed between 0 and 1, so if we want to show this feature to 20% of traffic
-# we can do _hash(key, distinct_id) < 0.2
-def _hash(key: str, distinct_id: str, salt: str = "") -> float:
-    hash_key = f"{key}.{distinct_id}{salt}"
+# we can do _hash(key, bucketing_value) < 0.2
+def _hash(key: str, bucketing_value: str, salt: str = "") -> float:
+    hash_key = f"{key}.{bucketing_value}{salt}"
     hash_val = int(hashlib.sha1(hash_key.encode("utf-8")).hexdigest()[:15], 16)
     return hash_val / __LONG_SCALE__
 
 
-def get_matching_variant(flag, distinct_id):
-    hash_value = _hash(flag["key"], distinct_id, salt="variant")
+def get_matching_variant(flag, bucketing_value):
+    hash_value = _hash(flag["key"], bucketing_value, salt="variant")
     for variant in variant_lookup_table(flag):
         if hash_value >= variant["value_min"] and hash_value < variant["value_max"]:
             return variant["key"]
@@ -55,39 +92,252 @@ def variant_lookup_table(feature_flag):
     return lookup_table
 
 
+def evaluate_flag_dependency(
+    property,
+    flags_by_key,
+    evaluation_cache,
+    distinct_id,
+    properties,
+    cohort_properties,
+    device_id=None,
+):
+    """
+    Evaluate a flag dependency property according to the dependency chain algorithm.
+
+    Args:
+        property: Flag property with type="flag" and dependency_chain
+        flags_by_key: Dictionary of all flags by their key
+        evaluation_cache: Cache for storing evaluation results
+        distinct_id: The distinct ID being evaluated
+        properties: Person properties for evaluation
+        cohort_properties: Cohort properties for evaluation
+        device_id: The device ID for bucketing (optional)
+
+    Returns:
+        bool: True if all dependencies in the chain evaluate to True, False otherwise
+    """
+    if flags_by_key is None or evaluation_cache is None:
+        # Cannot evaluate flag dependencies without required context
+        raise InconclusiveMatchError(
+            f"Cannot evaluate flag dependency on '{property.get('key', 'unknown')}' without flags_by_key and evaluation_cache"
+        )
+
+    # Check if dependency_chain is present - it should always be provided for flag dependencies
+    if "dependency_chain" not in property:
+        # Missing dependency_chain indicates malformed server data
+        raise InconclusiveMatchError(
+            f"Flag dependency property for '{property.get('key', 'unknown')}' is missing required 'dependency_chain' field"
+        )
+
+    dependency_chain = property["dependency_chain"]
+
+    # Handle circular dependency (empty chain means circular)
+    if len(dependency_chain) == 0:
+        log.debug(f"Circular dependency detected for flag: {property.get('key')}")
+        raise InconclusiveMatchError(
+            f"Circular dependency detected for flag '{property.get('key', 'unknown')}'"
+        )
+
+    # Evaluate all dependencies in the chain order
+    for dep_flag_key in dependency_chain:
+        if dep_flag_key not in evaluation_cache:
+            # Need to evaluate this dependency first
+            dep_flag = flags_by_key.get(dep_flag_key)
+            if not dep_flag:
+                # Missing flag dependency - cannot evaluate locally
+                evaluation_cache[dep_flag_key] = None
+                raise InconclusiveMatchError(
+                    f"Cannot evaluate flag dependency '{dep_flag_key}' - flag not found in local flags"
+                )
+            else:
+                # Check if the flag is active (same check as in client._compute_flag_locally)
+                if not dep_flag.get("active"):
+                    evaluation_cache[dep_flag_key] = False
+                else:
+                    # Recursively evaluate the dependency
+                    try:
+                        dep_flag_filters = dep_flag.get("filters") or {}
+                        dep_aggregation_group_type_index = dep_flag_filters.get(
+                            "aggregation_group_type_index"
+                        )
+                        if dep_aggregation_group_type_index is not None:
+                            # Group flags should continue bucketing by the group key
+                            # from the current evaluation context.
+                            dep_bucketing_value = distinct_id
+                        else:
+                            dep_bucketing_value = resolve_bucketing_value(
+                                dep_flag, distinct_id, device_id
+                            )
+                        dep_result = match_feature_flag_properties(
+                            dep_flag,
+                            distinct_id,
+                            properties,
+                            cohort_properties=cohort_properties,
+                            flags_by_key=flags_by_key,
+                            evaluation_cache=evaluation_cache,
+                            device_id=device_id,
+                            bucketing_value=dep_bucketing_value,
+                        )
+                        evaluation_cache[dep_flag_key] = dep_result
+                    except InconclusiveMatchError as e:
+                        # If we can't evaluate a dependency, store None and propagate the error
+                        evaluation_cache[dep_flag_key] = None
+                        raise InconclusiveMatchError(
+                            f"Cannot evaluate flag dependency '{dep_flag_key}': {e}"
+                        ) from e
+
+        # Check the cached result
+        cached_result = evaluation_cache[dep_flag_key]
+        if cached_result is None:
+            # Previously inconclusive - raise error again
+            raise InconclusiveMatchError(
+                f"Flag dependency '{dep_flag_key}' was previously inconclusive"
+            )
+        elif not cached_result:
+            # Definitive False result - dependency failed
+            return False
+
+    # All dependencies in the chain have been evaluated successfully
+    # Now check if the final flag value matches the expected value in the property
+    flag_key = property.get("key")
+    expected_value = property.get("value")
+    operator = property.get("operator", "exact")
+
+    if flag_key and expected_value is not None:
+        # Get the actual value of the flag we're checking
+        actual_value = evaluation_cache.get(flag_key)
+
+        if actual_value is None:
+            # Flag wasn't evaluated - this shouldn't happen if dependency chain is correct
+            raise InconclusiveMatchError(
+                f"Flag '{flag_key}' was not evaluated despite being in dependency chain"
+            )
+
+        # For flag dependencies, we need to compare the actual flag result with expected value
+        # using the flag_evaluates_to operator logic
+        if operator == "flag_evaluates_to":
+            return matches_dependency_value(expected_value, actual_value)
+        else:
+            # This should never happen, but just to be defensive.
+            raise InconclusiveMatchError(
+                f"Flag dependency property for '{property.get('key', 'unknown')}' has invalid operator '{operator}'"
+            )
+
+    # If no value check needed, return True (all dependencies passed)
+    return True
+
+
+def matches_dependency_value(expected_value, actual_value):
+    """
+    Check if the actual flag value matches the expected dependency value.
+
+    This follows the same logic as the C# MatchesDependencyValue function:
+    - String variant case: check for exact match or boolean true
+    - Boolean case: must match expected boolean value
+
+    Args:
+        expected_value: The expected value from the property
+        actual_value: The actual value returned by the flag evaluation
+
+    Returns:
+        bool: True if the values match according to flag dependency rules
+    """
+    # String variant case - check for exact match or boolean true
+    if isinstance(actual_value, str) and len(actual_value) > 0:
+        if isinstance(expected_value, bool):
+            # Any variant matches boolean true
+            return expected_value
+        elif isinstance(expected_value, str):
+            # variants are case-sensitive, hence our comparison is too
+            return actual_value == expected_value
+        else:
+            return False
+
+    # Boolean case - must match expected boolean value
+    elif isinstance(actual_value, bool) and isinstance(expected_value, bool):
+        return actual_value == expected_value
+
+    # Default case
+    return False
+
+
+def resolve_bucketing_value(flag, distinct_id, device_id=None):
+    """Resolve the bucketing value for a flag based on its bucketing_identifier setting.
+
+    Returns:
+        The appropriate identifier string to use for hashing/bucketing.
+
+    Raises:
+        InconclusiveMatchError: If the flag requires device_id but none was provided.
+    """
+    flag_filters = flag.get("filters") or {}
+    bucketing_identifier = flag.get("bucketing_identifier") or flag_filters.get(
+        "bucketing_identifier"
+    )
+    if bucketing_identifier == "device_id":
+        if not device_id:
+            raise InconclusiveMatchError(
+                "Flag requires device_id for bucketing but none was provided"
+            )
+        return device_id
+    return distinct_id
+
+
 def match_feature_flag_properties(
-    flag, distinct_id, properties, cohort_properties=None
+    flag,
+    distinct_id,
+    properties,
+    *,
+    cohort_properties=None,
+    flags_by_key=None,
+    evaluation_cache=None,
+    device_id=None,
+    bucketing_value=None,
 ) -> FlagValue:
-    flag_conditions = (flag.get("filters") or {}).get("groups") or []
+    if bucketing_value is None:
+        warnings.warn(
+            "Calling match_feature_flag_properties() without bucketing_value is deprecated. "
+            "Pass bucketing_value explicitly. This fallback will be removed in a future major release.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        bucketing_value = resolve_bucketing_value(flag, distinct_id, device_id)
+
+    flag_filters = flag.get("filters") or {}
+    flag_conditions = flag_filters.get("groups") or []
     is_inconclusive = False
     cohort_properties = cohort_properties or {}
     # Some filters can be explicitly set to null, which require accessing variants like so
-    flag_variants = ((flag.get("filters") or {}).get("multivariate") or {}).get(
-        "variants"
-    ) or []
+    flag_variants = (flag_filters.get("multivariate") or {}).get("variants") or []
     valid_variant_keys = [variant["key"] for variant in flag_variants]
 
-    # Stable sort conditions with variant overrides to the top. This ensures that if overrides are present, they are
-    # evaluated first, and the variant override is applied to the first matching condition.
-    sorted_flag_conditions = sorted(
-        flag_conditions,
-        key=lambda condition: 0 if condition.get("variant") else 1,
-    )
-
-    for condition in sorted_flag_conditions:
+    for condition in flag_conditions:
         try:
             # if any one condition resolves to True, we can shortcircuit and return
             # the matching variant
             if is_condition_match(
-                flag, distinct_id, condition, properties, cohort_properties
+                flag,
+                distinct_id,
+                condition,
+                properties,
+                cohort_properties,
+                flags_by_key,
+                evaluation_cache,
+                bucketing_value=bucketing_value,
+                device_id=device_id,
             ):
                 variant_override = condition.get("variant")
                 if variant_override and variant_override in valid_variant_keys:
                     variant = variant_override
                 else:
-                    variant = get_matching_variant(flag, distinct_id)
+                    variant = get_matching_variant(flag, bucketing_value)
                 return variant or True
+        except RequiresServerEvaluation:
+            # Static cohort or other missing server-side data - must fallback to API
+            raise
         except InconclusiveMatchError:
+            # Evaluation error (bad regex, invalid date, missing property, etc.)
+            # Track that we had an inconclusive match, but try other conditions
             is_inconclusive = True
 
     if is_inconclusive:
@@ -101,14 +351,41 @@ def match_feature_flag_properties(
 
 
 def is_condition_match(
-    feature_flag, distinct_id, condition, properties, cohort_properties
+    feature_flag,
+    distinct_id,
+    condition,
+    properties,
+    cohort_properties,
+    flags_by_key=None,
+    evaluation_cache=None,
+    *,
+    bucketing_value,
+    device_id=None,
 ) -> bool:
     rollout_percentage = condition.get("rollout_percentage")
     if len(condition.get("properties") or []) > 0:
         for prop in condition.get("properties"):
             property_type = prop.get("type")
             if property_type == "cohort":
-                matches = match_cohort(prop, properties, cohort_properties)
+                matches = match_cohort(
+                    prop,
+                    properties,
+                    cohort_properties,
+                    flags_by_key,
+                    evaluation_cache,
+                    distinct_id,
+                    device_id=device_id,
+                )
+            elif property_type == "flag":
+                matches = evaluate_flag_dependency(
+                    prop,
+                    flags_by_key,
+                    evaluation_cache,
+                    distinct_id,
+                    properties,
+                    cohort_properties,
+                    device_id=device_id,
+                )
             else:
                 matches = match_property(prop, properties)
             if not matches:
@@ -117,9 +394,9 @@ def is_condition_match(
         if rollout_percentage is None:
             return True
 
-    if rollout_percentage is not None and _hash(feature_flag["key"], distinct_id) > (
-        rollout_percentage / 100
-    ):
+    if rollout_percentage is not None and _hash(
+        feature_flag["key"], bucketing_value
+    ) > (rollout_percentage / 100):
         return False
 
     return True
@@ -132,6 +409,9 @@ def match_property(property, property_values) -> bool:
     operator = property.get("operator") or "exact"
     value = property.get("value")
 
+    if operator not in PROPERTY_OPERATORS:
+        raise InconclusiveMatchError(f"Unknown operator {operator}")
+
     if key not in property_values:
         raise InconclusiveMatchError(
             "can't match properties without a given property value"
@@ -252,11 +532,76 @@ def match_property(property, property_values) -> bool:
                 "The date provided must be a string or date object"
             )
 
-    # if we get here, we don't know how to handle the operator
+    if operator in SEMVER_OPERATORS:
+        try:
+            override_parsed = parse_semver(override_value)
+        except (ValueError, TypeError):
+            raise InconclusiveMatchError(
+                f"Person property value '{override_value}' is not a valid semver"
+            )
+
+        if operator in SEMVER_COMPARISON_OPERATORS:
+            try:
+                flag_parsed = parse_semver(value)
+            except (ValueError, TypeError):
+                raise InconclusiveMatchError(
+                    f"Flag semver value '{value}' is not a valid semver"
+                )
+
+            if operator == "semver_eq":
+                return override_parsed == flag_parsed
+            elif operator == "semver_neq":
+                return override_parsed != flag_parsed
+            elif operator == "semver_gt":
+                return override_parsed > flag_parsed
+            elif operator == "semver_gte":
+                return override_parsed >= flag_parsed
+            elif operator == "semver_lt":
+                return override_parsed < flag_parsed
+            elif operator == "semver_lte":
+                return override_parsed <= flag_parsed
+
+        elif operator == "semver_tilde":
+            try:
+                lower, upper = _tilde_bounds(str(value))
+            except (ValueError, TypeError):
+                raise InconclusiveMatchError(
+                    f"Flag semver value '{value}' is not valid for tilde operator"
+                )
+            return lower <= override_parsed < upper
+
+        elif operator == "semver_caret":
+            try:
+                lower, upper = _caret_bounds(str(value))
+            except (ValueError, TypeError):
+                raise InconclusiveMatchError(
+                    f"Flag semver value '{value}' is not valid for caret operator"
+                )
+            return lower <= override_parsed < upper
+
+        elif operator == "semver_wildcard":
+            try:
+                lower, upper = _wildcard_bounds(str(value))
+            except (ValueError, TypeError):
+                raise InconclusiveMatchError(
+                    f"Flag semver value '{value}' is not valid for wildcard operator"
+                )
+            return lower <= override_parsed < upper
+
+    # Unreachable: all operators in PROPERTY_OPERATORS are handled above,
+    # and unknown operators are rejected at the top of this function.
     raise InconclusiveMatchError(f"Unknown operator {operator}")
 
 
-def match_cohort(property, property_values, cohort_properties) -> bool:
+def match_cohort(
+    property,
+    property_values,
+    cohort_properties,
+    flags_by_key=None,
+    evaluation_cache=None,
+    distinct_id=None,
+    device_id=None,
+) -> bool:
     # Cohort properties are in the form of property groups like this:
     # {
     #     "cohort_id": {
@@ -268,15 +613,31 @@ def match_cohort(property, property_values, cohort_properties) -> bool:
     # }
     cohort_id = str(property.get("value"))
     if cohort_id not in cohort_properties:
-        raise InconclusiveMatchError(
-            "can't match cohort without a given cohort property value"
+        raise RequiresServerEvaluation(
+            f"cohort {cohort_id} not found in local cohorts - likely a static cohort that requires server evaluation"
         )
 
     property_group = cohort_properties[cohort_id]
-    return match_property_group(property_group, property_values, cohort_properties)
+    return match_property_group(
+        property_group,
+        property_values,
+        cohort_properties,
+        flags_by_key,
+        evaluation_cache,
+        distinct_id,
+        device_id=device_id,
+    )
 
 
-def match_property_group(property_group, property_values, cohort_properties) -> bool:
+def match_property_group(
+    property_group,
+    property_values,
+    cohort_properties,
+    flags_by_key=None,
+    evaluation_cache=None,
+    distinct_id=None,
+    device_id=None,
+) -> bool:
     if not property_group:
         return True
 
@@ -293,7 +654,15 @@ def match_property_group(property_group, property_values, cohort_properties) ->
         # a nested property group
         for prop in properties:
             try:
-                matches = match_property_group(prop, property_values, cohort_properties)
+                matches = match_property_group(
+                    prop,
+                    property_values,
+                    cohort_properties,
+                    flags_by_key,
+                    evaluation_cache,
+                    distinct_id,
+                    device_id=device_id,
+                )
                 if property_group_type == "AND":
                     if not matches:
                         return False
@@ -301,6 +670,9 @@ def match_property_group(property_group, property_values, cohort_properties) ->
                     # OR group
                     if matches:
                         return True
+            except RequiresServerEvaluation:
+                # Immediately propagate - this condition requires server-side data
+                raise
             except InconclusiveMatchError as e:
                 log.debug(f"Failed to compute property {prop} locally: {e}")
                 error_matching_locally = True
@@ -316,7 +688,25 @@ def match_property_group(property_group, property_values, cohort_properties) ->
         for prop in properties:
             try:
                 if prop.get("type") == "cohort":
-                    matches = match_cohort(prop, property_values, cohort_properties)
+                    matches = match_cohort(
+                        prop,
+                        property_values,
+                        cohort_properties,
+                        flags_by_key,
+                        evaluation_cache,
+                        distinct_id,
+                        device_id=device_id,
+                    )
+                elif prop.get("type") == "flag":
+                    matches = evaluate_flag_dependency(
+                        prop,
+                        flags_by_key,
+                        evaluation_cache,
+                        distinct_id,
+                        property_values,
+                        cohort_properties,
+                        device_id=device_id,
+                    )
                 else:
                     matches = match_property(prop, property_values)
 
@@ -334,6 +724,9 @@ def match_property_group(property_group, property_values, cohort_properties) ->
                         return True
                     if not matches and negation:
                         return True
+            except RequiresServerEvaluation:
+                # Immediately propagate - this condition requires server-side data
+                raise
             except InconclusiveMatchError as e:
                 log.debug(f"Failed to compute property {prop} locally: {e}")
                 error_matching_locally = True
@@ -377,3 +770,75 @@ def relative_date_parse_for_feature_flag_matching(
         return parsed_dt
     else:
         return None
+
+
+def parse_semver(value: str) -> tuple:
+    """Parse a semver string into a comparable (major, minor, patch) integer tuple.
+
+    Matches the behavior of the sortableSemver HogQL function:
+    - Handles v-prefix, whitespace, pre-release suffixes
+    - Defaults missing components to 0 (e.g., 1.2 -> 1.2.0)
+    Raises ValueError if parsing fails.
+    """
+    text = str(value).strip().lstrip("vV")
+    # Strip pre-release/build metadata suffix
+    text = text.split("-")[0].split("+")[0]
+    parts = text.split(".")
+
+    if not parts or not parts[0]:
+        raise ValueError("Invalid semver format")
+
+    major = int(parts[0])
+    minor = int(parts[1]) if len(parts) > 1 and parts[1] else 0
+    patch = int(parts[2]) if len(parts) > 2 and parts[2] else 0
+
+    return (major, minor, patch)
+
+
+def _tilde_bounds(value: str) -> tuple:
+    """~1.2.3 means >=1.2.3 <1.3.0 (allows patch-level changes)."""
+    major, minor, patch = parse_semver(value)
+    return (major, minor, patch), (major, minor + 1, 0)
+
+
+def _caret_bounds(value: str) -> tuple:
+    """Caret follows semver spec:
+    ^1.2.3 means >=1.2.3 <2.0.0
+    ^0.2.3 means >=0.2.3 <0.3.0
+    ^0.0.3 means >=0.0.3 <0.0.4
+    """
+    major, minor, patch = parse_semver(value)
+    lower = (major, minor, patch)
+
+    if major > 0:
+        upper = (major + 1, 0, 0)
+    elif minor > 0:
+        upper = (0, minor + 1, 0)
+    else:
+        upper = (0, 0, patch + 1)
+
+    return lower, upper
+
+
+def _wildcard_bounds(value: str) -> tuple:
+    """Wildcard matching:
+    1.* means >=1.0.0 <2.0.0
+    1.2.* means >=1.2.0 <1.3.0
+    """
+    cleaned = str(value).strip().lstrip("vV").replace("*", "").rstrip(".")
+    if not cleaned:
+        raise ValueError("Invalid wildcard pattern")
+
+    parts = [p for p in cleaned.split(".") if p]
+    if not parts:
+        raise ValueError("Invalid wildcard pattern")
+
+    if len(parts) == 1:
+        major = int(parts[0])
+        return (major, 0, 0), (major + 1, 0, 0)
+    elif len(parts) == 2:
+        major, minor = int(parts[0]), int(parts[1])
+        return (major, minor, 0), (major, minor + 1, 0)
+    else:
+        major, minor, patch = int(parts[0]), int(parts[1]), int(parts[2])
+        return (major, minor, patch), (major, minor, patch + 1)

posthog/flag_definition_cache.py

@@ -0,0 +1,127 @@
+"""
+Flag Definition Cache Provider interface for multi-worker environments.
+
+EXPERIMENTAL: This API may change in future minor version bumps.
+
+This module provides an interface for external caching of feature flag definitions,
+enabling multi-worker environments (Kubernetes, load-balanced servers, serverless
+functions) to share flag definitions and reduce API calls.
+
+Usage:
+
+    from posthog import Posthog
+    from posthog.flag_definition_cache import FlagDefinitionCacheProvider
+
+    cache = RedisFlagDefinitionCache(redis_client, "my-team")
+    posthog = Posthog(
+        "<project_api_key>",
+        personal_api_key="<personal_api_key>",
+        flag_definition_cache_provider=cache,
+    )
+"""
+
+from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
+
+from typing_extensions import Required, TypedDict
+
+
+class FlagDefinitionCacheData(TypedDict):
+    """
+    Data structure for cached flag definitions.
+
+    Attributes:
+        flags: List of feature flag definition dictionaries from the API.
+        group_type_mapping: Mapping of group type indices to group names.
+        cohorts: Dictionary of cohort definitions for local evaluation.
+    """
+
+    flags: Required[List[Dict[str, Any]]]
+    group_type_mapping: Required[Dict[str, str]]
+    cohorts: Required[Dict[str, Any]]
+
+
+@runtime_checkable
+class FlagDefinitionCacheProvider(Protocol):
+    """
+    Interface for external caching of feature flag definitions.
+
+    Enables multi-worker environments to share flag definitions, reducing API
+    calls while ensuring all workers have consistent data.
+
+    EXPERIMENTAL: This API may change in future minor version bumps.
+
+    The four methods handle the complete lifecycle of flag definition caching:
+
+    1. `should_fetch_flag_definitions()` - Called before each poll to determine
+       if this worker should fetch new definitions. Use for distributed lock
+       coordination to ensure only one worker fetches at a time.
+
+    2. `get_flag_definitions()` - Called when `should_fetch_flag_definitions()`
+       returns False. Returns cached definitions if available.
+
+    3. `on_flag_definitions_received()` - Called after successfully fetching
+       new definitions from the API. Store the data in your external cache
+       and release any locks.
+
+    4. `shutdown()` - Called when the PostHog client shuts down. Release any
+       distributed locks and clean up resources.
+
+    Error Handling:
+        All methods are wrapped in try/except. Errors will be logged but will
+        never break flag evaluation. On error:
+        - `should_fetch_flag_definitions()` errors default to fetching (fail-safe)
+        - `get_flag_definitions()` errors fall back to API fetch
+        - `on_flag_definitions_received()` errors are logged but flags remain in memory
+        - `shutdown()` errors are logged but shutdown continues
+    """
+
+    def get_flag_definitions(self) -> Optional[FlagDefinitionCacheData]:
+        """
+        Retrieve cached flag definitions.
+
+        Returns:
+            Cached flag definitions if available and valid, None otherwise.
+            Returning None will trigger a fetch from the API if this worker
+            has no flags loaded yet.
+        """
+        ...
+
+    def should_fetch_flag_definitions(self) -> bool:
+        """
+        Determine whether this instance should fetch new flag definitions.
+
+        Use this for distributed lock coordination. Only one worker should
+        return True to avoid thundering herd problems. A typical implementation
+        uses a distributed lock (e.g., Redis SETNX) that expires after the
+        poll interval.
+
+        Returns:
+            True if this instance should fetch from the API, False otherwise.
+            When False, the client will call `get_flag_definitions()` to
+            retrieve cached data instead.
+        """
+        ...
+
+    def on_flag_definitions_received(self, data: FlagDefinitionCacheData) -> None:
+        """
+        Called after successfully receiving new flag definitions from PostHog.
+
+        Use this to store the data in your external cache and release any
+        distributed locks acquired in `should_fetch_flag_definitions()`.
+
+        Args:
+            data: The flag definitions to cache, containing flags,
+                  group_type_mapping, and cohorts.
+        """
+        ...
+
+    def shutdown(self) -> None:
+        """
+        Called when the PostHog client shuts down.
+
+        Use this to release any distributed locks and clean up resources.
+        This method is called even if `should_fetch_flag_definitions()`
+        returned False, so implementations should handle the case where
+        no lock was acquired.
+        """
+        ...

posthog/integrations/django.py

@@ -1,9 +1,24 @@
 from typing import TYPE_CHECKING, cast
-from posthog import scopes
+from posthog import contexts
+from posthog.client import Client
+
+try:
+    from asgiref.sync import iscoroutinefunction, markcoroutinefunction
+except ImportError:
+    # Fallback for older Django versions without asgiref
+    import asyncio
+
+    iscoroutinefunction = asyncio.iscoroutinefunction
+
+    # No-op fallback for markcoroutinefunction
+    # Older Django versions without asgiref typically don't support async middleware anyway
+    def markcoroutinefunction(func):
+        return func
+
 
 if TYPE_CHECKING:
     from django.http import HttpRequest, HttpResponse  # noqa: F401
-    from typing import Callable, Dict, Any, Optional  # noqa: F401
+    from typing import Callable, Dict, Any, Optional, Union, Awaitable  # noqa: F401
 
 
 class PosthogContextMiddleware:
@@ -16,7 +31,8 @@ class PosthogContextMiddleware:
     - Request Method as $request_method
 
     The context will also auto-capture exceptions and send them to PostHog, unless you disable it by setting
-    `POSTHOG_MW_CAPTURE_EXCEPTIONS` to `False` in your Django settings.
+    `POSTHOG_MW_CAPTURE_EXCEPTIONS` to `False` in your Django settings. The exceptions are captured using the
+    global client, unless the setting `POSTHOG_MW_CLIENT` is set to a custom client instance
 
     The middleware behaviour is customisable through 3 additional functions:
     - `POSTHOG_MW_EXTRA_TAGS`, which is a Callable[[HttpRequest], Dict[str, Any]] expected to return a dictionary of additional tags to be added to the context.
@@ -29,11 +45,24 @@ class PosthogContextMiddleware:
     See the context documentation for more information. The extracted distinct ID and session ID, if found, are used to
     associate all events captured in the middleware context with the same distinct ID and session as currently active on the
     frontend. See the documentation for `set_context_session` and `identify_context` for more details.
+
+    This middleware is hybrid-capable: it supports both WSGI (sync) and ASGI (async) Django applications. The middleware
+    detects at initialization whether the next middleware in the chain is async or sync, and adapts its behavior accordingly.
+    This ensures compatibility with both pure sync and pure async middleware chains, as well as mixed chains in ASGI mode.
     """
 
+    sync_capable = True
+    async_capable = True
+
     def __init__(self, get_response):
-        # type: (Callable[[HttpRequest], HttpResponse]) -> None
+        # type: (Union[Callable[[HttpRequest], HttpResponse], Callable[[HttpRequest], Awaitable[HttpResponse]]]) -> None
         self.get_response = get_response
+        self._is_coroutine = iscoroutinefunction(get_response)
+
+        # Mark this instance as a coroutine function if get_response is async
+        # This is required for Django to correctly detect async middleware
+        if self._is_coroutine:
+            markcoroutinefunction(self)
 
         from django.conf import settings
 
@@ -74,19 +103,41 @@ class PosthogContextMiddleware:
         else:
             self.capture_exceptions = True
 
+        if hasattr(settings, "POSTHOG_MW_CLIENT") and isinstance(
+            settings.POSTHOG_MW_CLIENT, Client
+        ):
+            self.client = cast("Optional[Client]", settings.POSTHOG_MW_CLIENT)
+        else:
+            self.client = None
+
     def extract_tags(self, request):
         # type: (HttpRequest) -> Dict[str, Any]
+        """Extract tags from request in sync context."""
+        user_id, user_email = self.extract_request_user(request)
+        return self._build_tags(request, user_id, user_email)
+
+    def _build_tags(self, request, user_id, user_email):
+        # type: (HttpRequest, Optional[str], Optional[str]) -> Dict[str, Any]
+        """
+        Build tags dict from request and user info.
+
+        Centralized tag extraction logic used by both sync and async paths.
+        """
         tags = {}
 
         # Extract session ID from X-POSTHOG-SESSION-ID header
         session_id = request.headers.get("X-POSTHOG-SESSION-ID")
         if session_id:
-            scopes.set_context_session(session_id)
+            contexts.set_context_session(session_id)
 
-        # Extract distinct ID from X-POSTHOG-DISTINCT-ID header
-        distinct_id = request.headers.get("X-POSTHOG-DISTINCT-ID")
+        # Extract distinct ID from X-POSTHOG-DISTINCT-ID header or request user id
+        distinct_id = request.headers.get("X-POSTHOG-DISTINCT-ID") or user_id
         if distinct_id:
-            scopes.identify_context(distinct_id)
+            contexts.identify_context(distinct_id)
+
+        # Extract user email
+        if user_email:
+            tags["email"] = user_email
 
         # Extract current URL
         absolute_url = request.build_absolute_uri()
@@ -97,6 +148,20 @@ class PosthogContextMiddleware:
         if request.method:
             tags["$request_method"] = request.method
 
+        # Extract request path
+        if request.path:
+            tags["$request_path"] = request.path
+
+        # Extract IP address
+        ip_address = request.headers.get("X-Forwarded-For")
+        if ip_address:
+            tags["$ip"] = ip_address
+
+        # Extract user agent
+        user_agent = request.headers.get("User-Agent")
+        if user_agent:
+            tags["$user_agent"] = user_agent
+
         # Apply extra tags if configured
         if self.extra_tags:
             extra = self.extra_tags(request)
@@ -109,13 +174,146 @@ class PosthogContextMiddleware:
 
         return tags
 
+    def extract_request_user(self, request):
+        # type: (HttpRequest) -> tuple[Optional[str], Optional[str]]
+        """Extract user ID and email from request in sync context."""
+        user = getattr(request, "user", None)
+        return self._resolve_user_details(user)
+
+    async def aextract_tags(self, request):
+        # type: (HttpRequest) -> Dict[str, Any]
+        """
+        Async version of extract_tags for use in async request handling.
+
+        Uses await request.auser() instead of request.user to avoid
+        SynchronousOnlyOperation in async context.
+
+        Follows Django's naming convention for async methods (auser, asave, etc.).
+        """
+        user_id, user_email = await self.aextract_request_user(request)
+        return self._build_tags(request, user_id, user_email)
+
+    async def aextract_request_user(self, request):
+        # type: (HttpRequest) -> tuple[Optional[str], Optional[str]]
+        """
+        Async version of extract_request_user for use in async request handling.
+
+        Uses await request.auser() instead of request.user to avoid
+        SynchronousOnlyOperation in async context.
+
+        Follows Django's naming convention for async methods (auser, asave, etc.).
+        """
+        auser = getattr(request, "auser", None)
+        if callable(auser):
+            try:
+                user = await auser()
+                return self._resolve_user_details(user)
+            except Exception:
+                # If auser() fails, return empty - don't break the request
+                # Real errors (permissions, broken auth) will be logged by Django
+                return None, None
+
+        # Fallback for test requests without auser
+        return None, None
+
+    def _resolve_user_details(self, user):
+        # type: (Any) -> tuple[Optional[str], Optional[str]]
+        """
+        Extract user ID and email from a user object.
+
+        Handles both authenticated and unauthenticated users, as well as
+        legacy Django where is_authenticated was a method.
+        """
+        user_id = None
+        email = None
+
+        if user is None:
+            return user_id, email
+
+        # Handle is_authenticated (property in modern Django, method in legacy)
+        is_authenticated = getattr(user, "is_authenticated", False)
+        if callable(is_authenticated):
+            is_authenticated = is_authenticated()
+
+        if not is_authenticated:
+            return user_id, email
+
+        # Extract user primary key
+        user_pk = getattr(user, "pk", None)
+        if user_pk is not None:
+            user_id = str(user_pk)
+
+        # Extract user email
+        user_email = getattr(user, "email", None)
+        if user_email:
+            email = str(user_email)
+
+        return user_id, email
+
     def __call__(self, request):
-        # type: (HttpRequest) -> HttpResponse
+        # type: (HttpRequest) -> Union[HttpResponse, Awaitable[HttpResponse]]
+        """
+        Unified entry point for both sync and async request handling.
+
+        When sync_capable and async_capable are both True, Django passes requests
+        without conversion. This method detects the mode and routes accordingly.
+        """
+        if self._is_coroutine:
+            return self.__acall__(request)
+        else:
+            # Synchronous path
+            if self.request_filter and not self.request_filter(request):
+                return self.get_response(request)
+
+            with contexts.new_context(self.capture_exceptions, client=self.client):
+                for k, v in self.extract_tags(request).items():
+                    contexts.tag(k, v)
+
+                return self.get_response(request)
+
+    async def __acall__(self, request):
+        # type: (HttpRequest) -> Awaitable[HttpResponse]
+        """
+        Asynchronous entry point for async request handling.
+
+        This method is called when the middleware chain is async.
+        Uses aextract_tags() which calls request.auser() to avoid
+        SynchronousOnlyOperation when accessing user in async context.
+        """
         if self.request_filter and not self.request_filter(request):
-            return self.get_response(request)
+            return await self.get_response(request)
 
-        with scopes.new_context(self.capture_exceptions):
-            for k, v in self.extract_tags(request).items():
-                scopes.tag(k, v)
+        with contexts.new_context(self.capture_exceptions, client=self.client):
+            for k, v in (await self.aextract_tags(request)).items():
+                contexts.tag(k, v)
 
-            return self.get_response(request)
+            return await self.get_response(request)
+
+    def process_exception(self, request, exception):
+        # type: (HttpRequest, Exception) -> None
+        """
+        Process exceptions from views and downstream middleware.
+
+        Django calls this WHILE still inside the context created by __call__,
+        so request tags have already been extracted and set. This method just
+        needs to capture the exception directly.
+
+        Django converts view exceptions into responses before they propagate through
+        the middleware stack, so the context manager in __call__/__acall__ never sees them.
+
+        Note: Django's process_exception is always synchronous, even for async views.
+        """
+        if self.request_filter and not self.request_filter(request):
+            return
+
+        if not self.capture_exceptions:
+            return
+
+        # Context and tags already set by __call__ or __acall__
+        # Just capture the exception
+        if self.client:
+            self.client.capture_exception(exception)
+        else:
+            from posthog import capture_exception
+
+            capture_exception(exception)

posthog/request.py

@@ -1,28 +1,163 @@
 import json
 import logging
-from datetime import date, datetime
+import re
+import socket
+from dataclasses import dataclass
+from datetime import date, datetime, timezone
 from gzip import GzipFile
 from io import BytesIO
-from typing import Any, Optional, Union
+from typing import Any, List, Optional, Tuple, Union
 
 import requests
 from dateutil.tz import tzutc
+from requests.adapters import HTTPAdapter  # type: ignore[import-untyped]
+from urllib3.connection import HTTPConnection
 from urllib3.util.retry import Retry
 
 from posthog.utils import remove_trailing_slash
 from posthog.version import VERSION
 
-# Retry on both connect and read errors
-# by default read errors will only retry idempotent HTTP methods (so not POST)
-adapter = requests.adapters.HTTPAdapter(
-    max_retries=Retry(
-        total=2,
-        connect=2,
-        read=2,
+SocketOptions = List[Tuple[int, int, Union[int, bytes]]]
+
+KEEPALIVE_IDLE_SECONDS = 60
+KEEPALIVE_INTERVAL_SECONDS = 60
+KEEPALIVE_PROBE_COUNT = 3
+
+# TCP keepalive probes idle connections to prevent them from being dropped.
+# SO_KEEPALIVE is cross-platform, but timing options vary:
+# - Linux: TCP_KEEPIDLE, TCP_KEEPINTVL, TCP_KEEPCNT
+# - macOS: only SO_KEEPALIVE (uses system defaults)
+# - Windows: TCP_KEEPIDLE, TCP_KEEPINTVL (since Windows 10 1709)
+KEEP_ALIVE_SOCKET_OPTIONS: SocketOptions = list(
+    HTTPConnection.default_socket_options
+) + [
+    (socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1),
+]
+for attr, value in [
+    ("TCP_KEEPIDLE", KEEPALIVE_IDLE_SECONDS),
+    ("TCP_KEEPINTVL", KEEPALIVE_INTERVAL_SECONDS),
+    ("TCP_KEEPCNT", KEEPALIVE_PROBE_COUNT),
+]:
+    if hasattr(socket, attr):
+        KEEP_ALIVE_SOCKET_OPTIONS.append((socket.SOL_TCP, getattr(socket, attr), value))
+
+# Status codes that indicate transient server errors worth retrying
+RETRY_STATUS_FORCELIST = [408, 500, 502, 503, 504]
+
+
+def _mask_tokens_in_url(url: str) -> str:
+    """Mask token values in URLs for safe logging, keeping first 10 chars visible."""
+    return re.sub(r"(token=)([^&]{10})[^&]*", r"\1\2...", url)
+
+
+@dataclass
+class GetResponse:
+    """Response from a GET request with ETag support."""
+
+    data: Any
+    etag: Optional[str] = None
+    not_modified: bool = False
+
+
+class HTTPAdapterWithSocketOptions(HTTPAdapter):
+    """HTTPAdapter with configurable socket options."""
+
+    def __init__(self, *args, socket_options: Optional[SocketOptions] = None, **kwargs):
+        self.socket_options = socket_options
+        super().__init__(*args, **kwargs)
+
+    def init_poolmanager(self, *args, **kwargs):
+        if self.socket_options is not None:
+            kwargs["socket_options"] = self.socket_options
+        super().init_poolmanager(*args, **kwargs)
+
+
+def _build_session(socket_options: Optional[SocketOptions] = None) -> requests.Session:
+    """Build a session for general requests (batch, decide, etc.)."""
+    adapter = HTTPAdapterWithSocketOptions(
+        max_retries=Retry(
+            total=2,
+            connect=2,
+            read=2,
+        ),
+        socket_options=socket_options,
     )
-)
-_session = requests.sessions.Session()
-_session.mount("https://", adapter)
+    session = requests.Session()
+    session.mount("https://", adapter)
+    return session
+
+
+def _build_flags_session(
+    socket_options: Optional[SocketOptions] = None,
+) -> requests.Session:
+    """
+    Build a session for feature flag requests with POST retries.
+
+    Feature flag requests are idempotent (read-only), so retrying POST
+    requests is safe. This session retries on transient server errors
+    (408, 5xx) and network failures with exponential backoff
+    (0.5s, 1s delays between retries).
+    """
+    adapter = HTTPAdapterWithSocketOptions(
+        max_retries=Retry(
+            total=2,
+            connect=2,
+            read=2,
+            backoff_factor=0.5,
+            status_forcelist=RETRY_STATUS_FORCELIST,
+            allowed_methods=["POST"],
+        ),
+        socket_options=socket_options,
+    )
+    session = requests.Session()
+    session.mount("https://", adapter)
+    return session
+
+
+_session = _build_session()
+_flags_session = _build_flags_session()
+_socket_options: Optional[SocketOptions] = None
+_pooling_enabled = True
+
+
+def _get_session() -> requests.Session:
+    if _pooling_enabled:
+        return _session
+    return _build_session(_socket_options)
+
+
+def _get_flags_session() -> requests.Session:
+    if _pooling_enabled:
+        return _flags_session
+    return _build_flags_session(_socket_options)
+
+
+def set_socket_options(socket_options: Optional[SocketOptions]) -> None:
+    """
+    Configure socket options for all HTTP connections.
+
+    Example:
+        from posthog import set_socket_options
+        set_socket_options([(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)])
+    """
+    global _session, _flags_session, _socket_options
+    if socket_options == _socket_options:
+        return
+    _socket_options = socket_options
+    _session = _build_session(socket_options)
+    _flags_session = _build_flags_session(socket_options)
+
+
+def enable_keep_alive() -> None:
+    """Enable TCP keepalive to prevent idle connections from being dropped."""
+    set_socket_options(KEEP_ALIVE_SOCKET_OPTIONS)
+
+
+def disable_connection_reuse() -> None:
+    """Disable connection reuse, creating a fresh connection for each request."""
+    global _pooling_enabled
+    _pooling_enabled = False
+
 
 US_INGESTION_ENDPOINT = "https://us.i.posthog.com"
 EU_INGESTION_ENDPOINT = "https://eu.i.posthog.com"
@@ -48,6 +183,7 @@ def post(
     path=None,
     gzip: bool = False,
     timeout: int = 15,
+    session: Optional[requests.Session] = None,
     **kwargs,
 ) -> requests.Response:
     """Post the `kwargs` to the API"""
@@ -68,7 +204,9 @@ def post(
             gz.write(data.encode("utf-8"))
         data = buf.getvalue()
 
-    res = _session.post(url, data=data, headers=headers, timeout=timeout)
+    res = (session or _get_session()).post(
+        url, data=data, headers=headers, timeout=timeout
+    )
 
     if res.status_code == 200:
         log.debug("data uploaded successfully")
@@ -97,12 +235,31 @@ def _process_response(
             )
             raise QuotaLimitError(res.status_code, "Feature flags quota limited")
         return response
+    retry_after = None
+    retry_after_header = res.headers.get("Retry-After")
+    if retry_after_header:
+        try:
+            retry_after = float(retry_after_header)
+        except (ValueError, TypeError):
+            try:
+                from email.utils import parsedate_to_datetime
+
+                retry_after = max(
+                    0.0,
+                    (
+                        parsedate_to_datetime(retry_after_header)
+                        - datetime.now(timezone.utc)
+                    ).total_seconds(),
+                )
+            except (ValueError, TypeError):
+                pass
+
     try:
         payload = res.json()
         log.debug("received response: %s", payload)
-        raise APIError(res.status_code, payload["detail"])
+        raise APIError(res.status_code, payload["detail"], retry_after=retry_after)
     except (KeyError, ValueError):
-        raise APIError(res.status_code, res.text)
+        raise APIError(res.status_code, res.text, retry_after=retry_after)
 
 
 def decide(
@@ -124,23 +281,36 @@ def flags(
     timeout: int = 15,
     **kwargs,
 ) -> Any:
-    """Post the `kwargs to the flags API endpoint"""
-    res = post(api_key, host, "/flags/?v=2", gzip, timeout, **kwargs)
+    """Post the kwargs to the flags API endpoint with automatic retries."""
+    res = post(
+        api_key,
+        host,
+        "/flags/?v=2",
+        gzip,
+        timeout,
+        session=_get_flags_session(),
+        **kwargs,
+    )
     return _process_response(
         res, success_message="Feature flags evaluated successfully"
     )
 
 
 def remote_config(
-    personal_api_key: str, host: Optional[str] = None, key: str = "", timeout: int = 15
+    personal_api_key: str,
+    project_api_key: str,
+    host: Optional[str] = None,
+    key: str = "",
+    timeout: int = 15,
 ) -> Any:
     """Get remote config flag value from remote_config API endpoint"""
-    return get(
+    response = get(
         personal_api_key,
-        f"/api/projects/@current/feature_flags/{key}/remote_config/",
+        f"/api/projects/@current/feature_flags/{key}/remote_config?token={project_api_key}",
         host,
         timeout,
     )
+    return response.data
 
 
 def batch_post(
@@ -158,21 +328,51 @@ def batch_post(
 
 
 def get(
-    api_key: str, url: str, host: Optional[str] = None, timeout: Optional[int] = None
-) -> requests.Response:
-    url = remove_trailing_slash(host or DEFAULT_HOST) + url
-    res = requests.get(
-        url,
-        headers={"Authorization": "Bearer %s" % api_key, "User-Agent": USER_AGENT},
-        timeout=timeout,
+    api_key: str,
+    url: str,
+    host: Optional[str] = None,
+    timeout: Optional[int] = None,
+    etag: Optional[str] = None,
+) -> GetResponse:
+    """
+    Make a GET request with optional ETag support.
+
+    If an etag is provided, sends If-None-Match header. Returns GetResponse with:
+    - not_modified=True and data=None if server returns 304
+    - not_modified=False and data=response if server returns 200
+    """
+    log = logging.getLogger("posthog")
+    full_url = remove_trailing_slash(host or DEFAULT_HOST) + url
+    headers = {"Authorization": "Bearer %s" % api_key, "User-Agent": USER_AGENT}
+
+    if etag:
+        headers["If-None-Match"] = etag
+
+    res = _get_session().get(full_url, headers=headers, timeout=timeout)
+
+    masked_url = _mask_tokens_in_url(full_url)
+
+    # Handle 304 Not Modified
+    if res.status_code == 304:
+        log.debug(f"GET {masked_url} returned 304 Not Modified")
+        response_etag = res.headers.get("ETag")
+        return GetResponse(data=None, etag=response_etag or etag, not_modified=True)
+
+    # Handle normal response
+    data = _process_response(
+        res, success_message=f"GET {masked_url} completed successfully"
     )
-    return _process_response(res, success_message=f"GET {url} completed successfully")
+    response_etag = res.headers.get("ETag")
+    return GetResponse(data=data, etag=response_etag, not_modified=False)
 
 
 class APIError(Exception):
-    def __init__(self, status: Union[int, str], message: str):
+    def __init__(
+        self, status: Union[int, str], message: str, retry_after: Optional[float] = None
+    ):
         self.message = message
         self.status = status
+        self.retry_after = retry_after
 
     def __str__(self):
         msg = "[PostHog] {0} ({1})"
@@ -183,6 +383,12 @@ class QuotaLimitError(APIError):
     pass
 
 
+# Re-export requests exceptions for use in client.py
+# This keeps all requests library imports centralized in this module
+RequestsTimeout = requests.exceptions.Timeout
+RequestsConnectionError = requests.exceptions.ConnectionError
+
+
 class DatetimeSerializer(json.JSONEncoder):
     def default(self, obj: Any):
         if isinstance(obj, (date, datetime)):

posthog/test/ai/gemini/test_gemini.py

@@ -1,3 +1,4 @@
+import json
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -31,6 +32,16 @@ def mock_gemini_response():
     mock_usage = MagicMock()
     mock_usage.prompt_token_count = 20
     mock_usage.candidates_token_count = 10
+    # Ensure cache and reasoning tokens are not present (not MagicMock)
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    # Make model_dump() return a proper dict for serialization
+    mock_usage.model_dump.return_value = {
+        "prompt_token_count": 20,
+        "candidates_token_count": 10,
+        "cached_content_token_count": 0,
+        "thoughts_token_count": 0,
+    }
     mock_response.usage_metadata = mock_usage
 
     mock_candidate = MagicMock()
@@ -56,6 +67,105 @@ def mock_google_genai_client():
         yield mock_client_instance
 
 
+@pytest.fixture
+def mock_gemini_response_with_function_calls():
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 25
+    mock_usage.candidates_token_count = 15
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    # Make model_dump() return a proper dict for serialization
+    mock_usage.model_dump.return_value = {
+        "prompt_token_count": 25,
+        "candidates_token_count": 15,
+        "cached_content_token_count": 0,
+        "thoughts_token_count": 0,
+    }
+    mock_response.usage_metadata = mock_usage
+
+    # Mock function call
+    mock_function_call = MagicMock()
+    mock_function_call.name = "get_current_weather"
+    mock_function_call.args = {"location": "San Francisco"}
+
+    # Mock text part 1
+    mock_text_part1 = MagicMock()
+    mock_text_part1.text = "I'll check the weather for you."
+    # Make hasattr(part, "text") return True
+    type(mock_text_part1).text = mock_text_part1.text
+
+    # Mock text part 2
+    mock_text_part2 = MagicMock()
+    mock_text_part2.text = " Let me look that up."
+    type(mock_text_part2).text = mock_text_part2.text
+
+    # Mock function call part - need to ensure hasattr() works correctly
+    mock_function_part = MagicMock()
+    mock_function_part.function_call = mock_function_call
+    # Make hasattr(part, "function_call") return True
+    type(mock_function_part).function_call = mock_function_part.function_call
+    # Ensure hasattr(part, "text") returns False for the function part
+    del mock_function_part.text
+
+    # Mock content with 2 text parts and 1 function call part
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part1, mock_text_part2, mock_function_part]
+
+    # Mock candidate
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_response.candidates = [mock_candidate]
+
+    return mock_response
+
+
+@pytest.fixture
+def mock_gemini_response_function_calls_only():
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 30
+    mock_usage.candidates_token_count = 12
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    # Make model_dump() return a proper dict for serialization
+    mock_usage.model_dump.return_value = {
+        "prompt_token_count": 30,
+        "candidates_token_count": 12,
+        "cached_content_token_count": 0,
+        "thoughts_token_count": 0,
+    }
+    mock_response.usage_metadata = mock_usage
+
+    # Mock function call
+    mock_function_call = MagicMock()
+    mock_function_call.name = "get_current_weather"
+    mock_function_call.args = {"location": "New York", "unit": "fahrenheit"}
+
+    # Mock function call part (no text part) - need to ensure hasattr() works correctly
+    mock_function_part = MagicMock()
+    mock_function_part.function_call = mock_function_call
+    # Make hasattr(part, "function_call") return True
+    type(mock_function_part).function_call = mock_function_part.function_call
+    # Ensure hasattr(part, "text") returns False for the function part
+    del mock_function_part.text
+
+    # Mock content with only function call part
+    mock_content = MagicMock()
+    mock_content.parts = [mock_function_part]
+
+    # Mock candidate
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_response.candidates = [mock_candidate]
+
+    return mock_response
+
+
 def test_new_client_basic_generation(
     mock_client, mock_google_genai_client, mock_gemini_response
 ):
@@ -86,6 +196,15 @@ def test_new_client_basic_generation(
     assert props["foo"] == "bar"
     assert "$ai_trace_id" in props
     assert props["$ai_latency"] > 0
+    # Verify raw usage metadata is passed for backend processing
+    assert "$ai_usage" in props
+    assert props["$ai_usage"] is not None
+    # Verify it's JSON-serializable
+    json.dumps(props["$ai_usage"])
+    # Verify it has expected structure
+    assert isinstance(props["$ai_usage"], dict)
+    assert "prompt_token_count" in props["$ai_usage"]
+    assert "candidates_token_count" in props["$ai_usage"]
 
 
 def test_new_client_streaming_with_generate_content_stream(
@@ -99,6 +218,8 @@ def test_new_client_streaming_with_generate_content_stream(
         mock_usage1 = MagicMock()
         mock_usage1.prompt_token_count = 10
         mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
         mock_chunk1.usage_metadata = mock_usage1
 
         mock_chunk2 = MagicMock()
@@ -106,6 +227,8 @@ def test_new_client_streaming_with_generate_content_stream(
         mock_usage2 = MagicMock()
         mock_usage2.prompt_token_count = 10
         mock_usage2.candidates_token_count = 10
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
         mock_chunk2.usage_metadata = mock_usage2
 
         yield mock_chunk1
@@ -145,6 +268,91 @@ def test_new_client_streaming_with_generate_content_stream(
     assert isinstance(props["$ai_latency"], float)
 
 
+def test_new_client_streaming_with_tools(mock_client, mock_google_genai_client):
+    """Test that tools are captured in streaming mode"""
+
+    def mock_streaming_response():
+        mock_chunk1 = MagicMock()
+        mock_chunk1.text = "I'll check "
+        mock_usage1 = MagicMock()
+        mock_usage1.prompt_token_count = 15
+        mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
+        mock_chunk1.usage_metadata = mock_usage1
+
+        mock_chunk2 = MagicMock()
+        mock_chunk2.text = "the weather"
+        mock_usage2 = MagicMock()
+        mock_usage2.prompt_token_count = 15
+        mock_usage2.candidates_token_count = 10
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
+        mock_chunk2.usage_metadata = mock_usage2
+
+        yield mock_chunk1
+        yield mock_chunk2
+
+    # Mock the generate_content_stream method
+    mock_google_genai_client.models.generate_content_stream.return_value = (
+        mock_streaming_response()
+    )
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    # Create mock tools configuration
+    mock_tool = MagicMock()
+    mock_tool.function_declarations = [
+        MagicMock(
+            name="get_current_weather",
+            description="Gets the current weather for a given location.",
+            parameters=MagicMock(
+                type="OBJECT",
+                properties={
+                    "location": MagicMock(
+                        type="STRING",
+                        description="The city and state, e.g. San Francisco, CA",
+                    )
+                },
+                required=["location"],
+            ),
+        )
+    ]
+
+    mock_config = MagicMock()
+    mock_config.tools = [mock_tool]
+
+    response = client.models.generate_content_stream(
+        model="gemini-2.0-flash",
+        contents=["What's the weather in SF?"],
+        config=mock_config,
+        posthog_distinct_id="test-id",
+        posthog_properties={"feature": "streaming_with_tools"},
+    )
+
+    chunks = list(response)
+    assert len(chunks) == 2
+    assert chunks[0].text == "I'll check "
+    assert chunks[1].text == "the weather"
+
+    # Check that the streaming event was captured with tools
+    assert mock_client.capture.call_count == 1
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.0-flash"
+    assert props["$ai_input_tokens"] == 15
+    assert props["$ai_output_tokens"] == 10
+    assert props["feature"] == "streaming_with_tools"
+    assert isinstance(props["$ai_latency"], float)
+
+    # Verify that tools are captured in the $ai_tools property in streaming mode
+    assert props["$ai_tools"] == [mock_tool]
+
+
 def test_new_client_groups(mock_client, mock_google_genai_client, mock_gemini_response):
     """Test groups functionality with new Client API"""
     mock_google_genai_client.models.generate_content.return_value = mock_gemini_response
@@ -221,12 +429,42 @@ def test_new_client_different_input_formats(
     props = call_args["properties"]
     assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
 
-    # Test list input
-    mock_client.capture.reset_mock()
-    mock_part = MagicMock()
-    mock_part.text = "List item"
+    # Test Gemini-specific format with parts array (like in the screenshot)
+    mock_client.reset_mock()
     client.models.generate_content(
-        model="gemini-2.0-flash", contents=[mock_part], posthog_distinct_id="test-id"
+        model="gemini-2.0-flash",
+        contents=[{"role": "user", "parts": [{"text": "hey"}]}],
+        posthog_distinct_id="test-id",
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [
+        {"role": "user", "content": [{"type": "text", "text": "hey"}]}
+    ]
+
+    # Test multiple parts in the parts array
+    mock_client.reset_mock()
+    client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=[{"role": "user", "parts": [{"text": "Hello "}, {"text": "world"}]}],
+        posthog_distinct_id="test-id",
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Hello "},
+                {"type": "text", "text": "world"},
+            ],
+        }
+    ]
+
+    # Test list input with string
+    mock_client.capture.reset_mock()
+    client.models.generate_content(
+        model="gemini-2.0-flash", contents=["List item"], posthog_distinct_id="test-id"
     )
     call_args = mock_client.capture.call_args[1]
     props = call_args["properties"]
@@ -318,3 +556,608 @@ def test_new_client_override_defaults(
     assert props["team"] == "ai"  # from defaults
     assert props["feature"] == "chat"  # from call
     assert props["urgent"] is True  # from call
+
+
+def test_vertex_ai_parameters_passed_through(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test that Vertex AI parameters are properly passed to genai.Client"""
+    mock_google_genai_client.models.generate_content.return_value = mock_gemini_response
+
+    # Mock credentials object
+    mock_credentials = MagicMock()
+    mock_debug_config = MagicMock()
+    mock_http_options = MagicMock()
+
+    # Create client with Vertex AI parameters
+    Client(
+        vertexai=True,
+        credentials=mock_credentials,
+        project="test-project",
+        location="us-central1",
+        debug_config=mock_debug_config,
+        http_options=mock_http_options,
+        posthog_client=mock_client,
+    )
+
+    # Verify genai.Client was called with correct parameters
+    google_genai.Client.assert_called_once_with(
+        vertexai=True,
+        credentials=mock_credentials,
+        project="test-project",
+        location="us-central1",
+        debug_config=mock_debug_config,
+        http_options=mock_http_options,
+    )
+
+
+def test_api_key_mode(mock_client, mock_google_genai_client):
+    """Test API key authentication mode"""
+
+    # Create client with just API key (traditional mode)
+    Client(
+        api_key="test-api-key",
+        posthog_client=mock_client,
+    )
+
+    # Verify genai.Client was called with only api_key
+    google_genai.Client.assert_called_once_with(api_key="test-api-key")
+
+
+def test_vertex_ai_mode_with_optional_api_key(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test Vertex AI mode with optional API key"""
+    mock_google_genai_client.models.generate_content.return_value = mock_gemini_response
+
+    mock_credentials = MagicMock()
+
+    # Create client with Vertex AI + API key
+    Client(
+        vertexai=True,
+        api_key="test-api-key",
+        credentials=mock_credentials,
+        project="test-project",
+        posthog_client=mock_client,
+    )
+
+    # Verify genai.Client was called with both Vertex AI params and API key
+    google_genai.Client.assert_called_once_with(
+        vertexai=True,
+        api_key="test-api-key",
+        credentials=mock_credentials,
+        project="test-project",
+    )
+
+
+def test_tool_use_response(mock_client, mock_google_genai_client, mock_gemini_response):
+    """Test that tools defined in config are captured in $ai_tools property"""
+    mock_google_genai_client.models.generate_content.return_value = mock_gemini_response
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    # Create mock tools configuration
+    mock_tool = MagicMock()
+    mock_tool.function_declarations = [
+        MagicMock(
+            name="get_current_weather",
+            description="Gets the current weather for a given location.",
+            parameters=MagicMock(
+                type="OBJECT",
+                properties={
+                    "location": MagicMock(
+                        type="STRING",
+                        description="The city and state, e.g. San Francisco, CA",
+                    )
+                },
+                required=["location"],
+            ),
+        )
+    ]
+
+    mock_config = MagicMock()
+    mock_config.tools = [mock_tool]
+    # Explicitly specify this config doesn't have system_instruction
+    del mock_config.system_instruction
+
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents=["hey"],
+        config=mock_config,
+        posthog_distinct_id="test-id",
+        posthog_properties={"foo": "bar"},
+    )
+
+    assert response == mock_gemini_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.5-flash"
+    assert props["$ai_input"] == [{"role": "user", "content": "hey"}]
+    assert props["$ai_output_choices"] == [
+        {
+            "role": "assistant",
+            "content": [{"type": "text", "text": "Test response from Gemini"}],
+        }
+    ]
+    assert props["$ai_input_tokens"] == 20
+    assert props["$ai_output_tokens"] == 10
+    assert props["$ai_http_status"] == 200
+    assert props["foo"] == "bar"
+    assert isinstance(props["$ai_latency"], float)
+    # Verify that tools are captured in the $ai_tools property
+    assert props["$ai_tools"] == [mock_tool]
+
+
+def test_function_calls_in_output_choices(
+    mock_client, mock_google_genai_client, mock_gemini_response_with_function_calls
+):
+    """Test that function calls are properly included in $ai_output_choices"""
+    mock_google_genai_client.models.generate_content.return_value = (
+        mock_gemini_response_with_function_calls
+    )
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents=["What's the weather in San Francisco?"],
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_gemini_response_with_function_calls
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.5-flash"
+    assert props["$ai_output_choices"] == [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "I'll check the weather for you."},
+                {"type": "text", "text": " Let me look that up."},
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "get_current_weather",
+                        "arguments": {"location": "San Francisco"},
+                    },
+                },
+            ],
+        }
+    ]
+
+    # Check token usage
+    assert props["$ai_input_tokens"] == 25
+    assert props["$ai_output_tokens"] == 15
+    assert props["$ai_http_status"] == 200
+
+
+def test_function_calls_only_no_content(
+    mock_client, mock_google_genai_client, mock_gemini_response_function_calls_only
+):
+    """Test function calls without text content in $ai_output_choices"""
+    mock_google_genai_client.models.generate_content.return_value = (
+        mock_gemini_response_function_calls_only
+    )
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents=["Get weather for New York"],
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_gemini_response_function_calls_only
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.5-flash"
+    assert props["$ai_output_choices"] == [
+        {
+            "role": "assistant",
+            "content": [
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "get_current_weather",
+                        "arguments": {"location": "New York", "unit": "fahrenheit"},
+                    },
+                }
+            ],
+        }
+    ]
+
+    # Check token usage
+    assert props["$ai_input_tokens"] == 30
+    assert props["$ai_output_tokens"] == 12
+    assert props["$ai_http_status"] == 200
+
+
+def test_cache_and_reasoning_tokens(mock_client, mock_google_genai_client):
+    """Test that cache and reasoning tokens are properly extracted"""
+    # Create a mock response with cache and reasoning tokens
+    mock_response = MagicMock()
+    mock_response.text = "Test response with cache"
+
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 100
+    mock_usage.candidates_token_count = 50
+    mock_usage.cached_content_token_count = 30  # Cache tokens
+    mock_usage.thoughts_token_count = 10  # Reasoning tokens
+    mock_response.usage_metadata = mock_usage
+
+    # Mock candidates
+    mock_candidate = MagicMock()
+    mock_candidate.text = "Test response with cache"
+    mock_response.candidates = [mock_candidate]
+
+    mock_google_genai_client.models.generate_content.return_value = mock_response
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-pro",
+        contents="Test with cache",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Check that all token types are present
+    assert props["$ai_input_tokens"] == 100
+    assert props["$ai_output_tokens"] == 50
+    assert props["$ai_cache_read_input_tokens"] == 30
+    assert props["$ai_reasoning_tokens"] == 10
+
+
+def test_streaming_cache_and_reasoning_tokens(mock_client, mock_google_genai_client):
+    """Test that cache and reasoning tokens are properly extracted in streaming"""
+    # Create mock chunks with cache and reasoning tokens
+    chunk1 = MagicMock()
+    chunk1.text = "Hello "
+    chunk1_usage = MagicMock()
+    chunk1_usage.prompt_token_count = 100
+    chunk1_usage.candidates_token_count = 5
+    chunk1_usage.cached_content_token_count = 30  # Cache tokens
+    chunk1_usage.thoughts_token_count = 0
+    # Make model_dump() return a proper dict for serialization
+    chunk1_usage.model_dump.return_value = {
+        "prompt_token_count": 100,
+        "candidates_token_count": 5,
+        "cached_content_token_count": 30,
+        "thoughts_token_count": 0,
+    }
+    chunk1.usage_metadata = chunk1_usage
+
+    chunk2 = MagicMock()
+    chunk2.text = "world!"
+    chunk2_usage = MagicMock()
+    chunk2_usage.prompt_token_count = 100
+    chunk2_usage.candidates_token_count = 10
+    chunk2_usage.cached_content_token_count = 30  # Same cache tokens
+    chunk2_usage.thoughts_token_count = 5  # Reasoning tokens
+    # Make model_dump() return a proper dict for serialization
+    chunk2_usage.model_dump.return_value = {
+        "prompt_token_count": 100,
+        "candidates_token_count": 10,
+        "cached_content_token_count": 30,
+        "thoughts_token_count": 5,
+    }
+    chunk2.usage_metadata = chunk2_usage
+
+    mock_stream = iter([chunk1, chunk2])
+    mock_google_genai_client.models.generate_content_stream.return_value = mock_stream
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content_stream(
+        model="gemini-2.5-pro",
+        contents="Test streaming with cache",
+        posthog_distinct_id="test-id",
+    )
+
+    # Consume the stream
+    result = list(response)
+    assert len(result) == 2
+
+    # Check PostHog capture was called
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Check that all token types are present (should use final chunk's usage)
+    assert props["$ai_input_tokens"] == 100
+    assert props["$ai_output_tokens"] == 10
+    assert props["$ai_cache_read_input_tokens"] == 30
+    assert props["$ai_reasoning_tokens"] == 5
+
+    # Verify raw usage is captured in streaming mode (merged from chunks)
+    assert "$ai_usage" in props
+    assert props["$ai_usage"] is not None
+    # Verify it's JSON-serializable
+    json.dumps(props["$ai_usage"])
+    # Verify it has expected structure
+    assert isinstance(props["$ai_usage"], dict)
+    assert "prompt_token_count" in props["$ai_usage"]
+    assert "candidates_token_count" in props["$ai_usage"]
+
+
+def test_web_search_grounding(mock_client, mock_google_genai_client):
+    """Test web search detection via grounding_metadata."""
+
+    # Create mock response with grounding metadata
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 60
+    mock_usage.candidates_token_count = 40
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    # Mock grounding metadata
+    mock_grounding_chunk = MagicMock()
+    mock_grounding_chunk.uri = "https://example.com"
+
+    mock_grounding_metadata = MagicMock()
+    mock_grounding_metadata.grounding_chunks = [mock_grounding_chunk]
+
+    # Mock text part
+    mock_text_part = MagicMock()
+    mock_text_part.text = "According to search results..."
+    type(mock_text_part).text = mock_text_part.text
+
+    # Mock content with parts
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part]
+
+    # Mock candidate with grounding metadata
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_candidate.grounding_metadata = mock_grounding_metadata
+    type(mock_candidate).grounding_metadata = mock_candidate.grounding_metadata
+
+    mock_response.candidates = [mock_candidate]
+    mock_response.text = "According to search results..."
+
+    # Mock the generate_content method
+    mock_google_genai_client.models.generate_content.return_value = mock_response
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents="What's the latest news?",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is detected (binary for grounding)
+    assert props["$ai_web_search_count"] == 1
+    assert props["$ai_input_tokens"] == 60
+    assert props["$ai_output_tokens"] == 40
+
+
+def test_streaming_with_web_search(mock_client, mock_google_genai_client):
+    """Test that web search count is properly captured in streaming mode."""
+
+    def mock_streaming_response():
+        # Create chunk 1 with grounding metadata
+        mock_chunk1 = MagicMock()
+        mock_chunk1.text = "According to "
+
+        mock_usage1 = MagicMock()
+        mock_usage1.prompt_token_count = 30
+        mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
+        mock_chunk1.usage_metadata = mock_usage1
+
+        # Add grounding metadata to first chunk
+        mock_grounding_chunk = MagicMock()
+        mock_grounding_chunk.uri = "https://example.com"
+
+        mock_grounding_metadata = MagicMock()
+        mock_grounding_metadata.grounding_chunks = [mock_grounding_chunk]
+
+        mock_candidate1 = MagicMock()
+        mock_candidate1.grounding_metadata = mock_grounding_metadata
+        type(mock_candidate1).grounding_metadata = mock_candidate1.grounding_metadata
+
+        mock_chunk1.candidates = [mock_candidate1]
+
+        # Create chunk 2
+        mock_chunk2 = MagicMock()
+        mock_chunk2.text = "search results..."
+
+        mock_usage2 = MagicMock()
+        mock_usage2.prompt_token_count = 30
+        mock_usage2.candidates_token_count = 15
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
+        mock_chunk2.usage_metadata = mock_usage2
+
+        mock_candidate2 = MagicMock()
+        mock_chunk2.candidates = [mock_candidate2]
+
+        yield mock_chunk1
+        yield mock_chunk2
+
+    # Mock the generate_content_stream method
+    mock_google_genai_client.models.generate_content_stream.return_value = (
+        mock_streaming_response()
+    )
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content_stream(
+        model="gemini-2.5-flash",
+        contents="What's the latest news?",
+        posthog_distinct_id="test-id",
+    )
+
+    chunks = list(response)
+    assert len(chunks) == 2
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is detected (binary for grounding)
+    assert props["$ai_web_search_count"] == 1
+    assert props["$ai_input_tokens"] == 30
+    assert props["$ai_output_tokens"] == 15
+
+
+def test_empty_grounding_metadata_no_web_search(mock_client, mock_google_genai_client):
+    """Test that empty grounding_metadata (all null fields) does not count as web search."""
+
+    # Create mock response with empty grounding metadata (all null fields)
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 10
+    mock_usage.candidates_token_count = 10
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    # Mock empty grounding metadata (all fields are None)
+    mock_grounding_metadata = MagicMock()
+    mock_grounding_metadata.web_search_queries = None
+    mock_grounding_metadata.grounding_chunks = None
+    mock_grounding_metadata.grounding_supports = None
+    mock_grounding_metadata.retrieval_metadata = None
+    mock_grounding_metadata.retrieval_queries = None
+    mock_grounding_metadata.search_entry_point = None
+
+    # Mock text part
+    mock_text_part = MagicMock()
+    mock_text_part.text = "Hey there! How can I help you today?"
+    type(mock_text_part).text = mock_text_part.text
+
+    # Mock content with parts
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part]
+
+    # Mock candidate with empty grounding metadata
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_candidate.grounding_metadata = mock_grounding_metadata
+    type(mock_candidate).grounding_metadata = mock_candidate.grounding_metadata
+
+    mock_response.candidates = [mock_candidate]
+    mock_response.text = "Hey there! How can I help you today?"
+
+    # Mock the generate_content method
+    mock_google_genai_client.models.generate_content.return_value = mock_response
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents="Hello",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is 0 (not present in properties when 0)
+    assert "$ai_web_search_count" not in props
+    assert props["$ai_input_tokens"] == 10
+    assert props["$ai_output_tokens"] == 10
+
+
+def test_empty_array_grounding_metadata_no_web_search(
+    mock_client, mock_google_genai_client
+):
+    """Test that grounding_metadata with empty arrays does not count as web search."""
+
+    # Create mock response with grounding metadata having empty arrays
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 15
+    mock_usage.candidates_token_count = 12
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    # Mock grounding metadata with empty arrays
+    mock_grounding_metadata = MagicMock()
+    mock_grounding_metadata.web_search_queries = []
+    mock_grounding_metadata.grounding_chunks = []
+    mock_grounding_metadata.grounding_supports = []
+
+    # Mock text part
+    mock_text_part = MagicMock()
+    mock_text_part.text = "I can help with that."
+    type(mock_text_part).text = mock_text_part.text
+
+    # Mock content with parts
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part]
+
+    # Mock candidate with grounding metadata containing empty arrays
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_candidate.grounding_metadata = mock_grounding_metadata
+    type(mock_candidate).grounding_metadata = mock_candidate.grounding_metadata
+
+    mock_response.candidates = [mock_candidate]
+    mock_response.text = "I can help with that."
+
+    # Mock the generate_content method
+    mock_google_genai_client.models.generate_content.return_value = mock_response
+
+    client = Client(api_key="test-key", posthog_client=mock_client)
+
+    response = client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents="What can you do?",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is 0 (not present in properties when 0)
+    assert "$ai_web_search_count" not in props
+    assert props["$ai_input_tokens"] == 15
+    assert props["$ai_output_tokens"] == 12

posthog/test/ai/gemini/test_gemini_async.py

@@ -0,0 +1,853 @@
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+try:
+    from google import genai as google_genai
+
+    from posthog.ai.gemini import AsyncClient
+
+    GEMINI_AVAILABLE = True
+except ImportError:
+    GEMINI_AVAILABLE = False
+
+pytestmark = [
+    pytest.mark.skipif(
+        not GEMINI_AVAILABLE, reason="Google Gemini package is not available"
+    ),
+    pytest.mark.asyncio,
+]
+
+
+@pytest.fixture
+def mock_client():
+    with patch("posthog.client.Client") as mock_client:
+        mock_client.privacy_mode = False
+        yield mock_client
+
+
+@pytest.fixture
+def mock_gemini_response():
+    mock_response = MagicMock()
+    mock_response.text = "Test response from Gemini"
+
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 20
+    mock_usage.candidates_token_count = 10
+    # Ensure cache and reasoning tokens are not present (not MagicMock)
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    mock_candidate = MagicMock()
+    mock_candidate.text = "Test response from Gemini"
+    mock_content = MagicMock()
+    mock_part = MagicMock()
+    mock_part.text = "Test response from Gemini"
+    mock_content.parts = [mock_part]
+    mock_candidate.content = mock_content
+    mock_response.candidates = [mock_candidate]
+
+    return mock_response
+
+
+@pytest.fixture
+def mock_google_genai_client():
+    """Mock for the google-genai Client with async support"""
+    with patch.object(google_genai, "Client") as mock_client_class:
+        mock_client_instance = MagicMock()
+        mock_models = MagicMock()
+        mock_aio = MagicMock()
+        mock_aio_models = MagicMock()
+
+        mock_client_instance.models = mock_models
+        mock_client_instance.aio = mock_aio
+        mock_aio.models = mock_aio_models
+
+        mock_client_class.return_value = mock_client_instance
+        yield mock_client_instance
+
+
+@pytest.fixture
+def mock_gemini_response_with_function_calls():
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 25
+    mock_usage.candidates_token_count = 15
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    # Mock function call
+    mock_function_call = MagicMock()
+    mock_function_call.name = "get_current_weather"
+    mock_function_call.args = {"location": "San Francisco"}
+
+    # Mock text part 1
+    mock_text_part1 = MagicMock()
+    mock_text_part1.text = "I'll check the weather for you."
+    type(mock_text_part1).text = mock_text_part1.text
+
+    # Mock text part 2
+    mock_text_part2 = MagicMock()
+    mock_text_part2.text = " Let me look that up."
+    type(mock_text_part2).text = mock_text_part2.text
+
+    # Mock function call part
+    mock_function_part = MagicMock()
+    mock_function_part.function_call = mock_function_call
+    type(mock_function_part).function_call = mock_function_part.function_call
+    del mock_function_part.text
+
+    # Mock content with 2 text parts and 1 function call part
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part1, mock_text_part2, mock_function_part]
+
+    # Mock candidate
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_response.candidates = [mock_candidate]
+
+    return mock_response
+
+
+async def test_async_client_basic_generation(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test the async Client/AsyncModels API structure"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Tell me a fun fact about hedgehogs"],
+        posthog_distinct_id="test-id",
+        posthog_properties={"foo": "bar"},
+    )
+
+    assert response == mock_gemini_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.0-flash"
+    assert props["$ai_input_tokens"] == 20
+    assert props["$ai_output_tokens"] == 10
+    assert props["foo"] == "bar"
+    assert "$ai_trace_id" in props
+    assert props["$ai_latency"] > 0
+
+
+async def test_async_client_streaming_with_generate_content_stream(
+    mock_client, mock_google_genai_client
+):
+    """Test the async generate_content_stream method"""
+
+    async def mock_streaming_response():
+        mock_chunk1 = MagicMock()
+        mock_chunk1.text = "Hello "
+        mock_usage1 = MagicMock()
+        mock_usage1.prompt_token_count = 10
+        mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
+        mock_chunk1.usage_metadata = mock_usage1
+        yield mock_chunk1
+
+        mock_chunk2 = MagicMock()
+        mock_chunk2.text = "world!"
+        mock_usage2 = MagicMock()
+        mock_usage2.prompt_token_count = 10
+        mock_usage2.candidates_token_count = 10
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
+        mock_chunk2.usage_metadata = mock_usage2
+        yield mock_chunk2
+
+    # Mock the async generate_content_stream method
+    mock_google_genai_client.aio.models.generate_content_stream = AsyncMock(
+        return_value=mock_streaming_response()
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content_stream(
+        model="gemini-2.0-flash",
+        contents=["Write a short story"],
+        posthog_distinct_id="test-id",
+        posthog_properties={"feature": "streaming"},
+    )
+
+    chunks = []
+    async for chunk in response:
+        chunks.append(chunk)
+
+    assert len(chunks) == 2
+    assert chunks[0].text == "Hello "
+    assert chunks[1].text == "world!"
+
+    # Check that the streaming event was captured
+    assert mock_client.capture.call_count == 1
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.0-flash"
+    assert props["$ai_input_tokens"] == 10
+    assert props["$ai_output_tokens"] == 10
+    assert props["feature"] == "streaming"
+    assert isinstance(props["$ai_latency"], float)
+
+
+async def test_async_client_streaming_with_tools(mock_client, mock_google_genai_client):
+    """Test that tools are captured in async streaming mode"""
+
+    async def mock_streaming_response():
+        mock_chunk1 = MagicMock()
+        mock_chunk1.text = "I'll check "
+        mock_usage1 = MagicMock()
+        mock_usage1.prompt_token_count = 15
+        mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
+        mock_chunk1.usage_metadata = mock_usage1
+        yield mock_chunk1
+
+        mock_chunk2 = MagicMock()
+        mock_chunk2.text = "the weather"
+        mock_usage2 = MagicMock()
+        mock_usage2.prompt_token_count = 15
+        mock_usage2.candidates_token_count = 10
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
+        mock_chunk2.usage_metadata = mock_usage2
+        yield mock_chunk2
+
+    # Mock the async generate_content_stream method
+    mock_google_genai_client.aio.models.generate_content_stream = AsyncMock(
+        return_value=mock_streaming_response()
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    # Create mock tools configuration
+    mock_tool = MagicMock()
+    mock_tool.function_declarations = [
+        MagicMock(
+            name="get_current_weather",
+            description="Gets the current weather for a given location.",
+            parameters=MagicMock(
+                type="OBJECT",
+                properties={
+                    "location": MagicMock(
+                        type="STRING",
+                        description="The city and state, e.g. San Francisco, CA",
+                    )
+                },
+                required=["location"],
+            ),
+        )
+    ]
+
+    mock_config = MagicMock()
+    mock_config.tools = [mock_tool]
+
+    response = await client.models.generate_content_stream(
+        model="gemini-2.0-flash",
+        contents=["What's the weather in SF?"],
+        config=mock_config,
+        posthog_distinct_id="test-id",
+        posthog_properties={"feature": "streaming_with_tools"},
+    )
+
+    chunks = []
+    async for chunk in response:
+        chunks.append(chunk)
+
+    assert len(chunks) == 2
+    assert chunks[0].text == "I'll check "
+    assert chunks[1].text == "the weather"
+
+    # Check that the streaming event was captured with tools
+    assert mock_client.capture.call_count == 1
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.0-flash"
+    assert props["$ai_input_tokens"] == 15
+    assert props["$ai_output_tokens"] == 10
+    assert props["feature"] == "streaming_with_tools"
+    assert isinstance(props["$ai_latency"], float)
+
+    # Verify that tools are captured in the $ai_tools property in streaming mode
+    assert props["$ai_tools"] == [mock_tool]
+
+
+async def test_async_client_groups(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test groups functionality with async Client API"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Hello"],
+        posthog_distinct_id="test-id",
+        posthog_groups={"company": "company_123"},
+    )
+
+    call_args = mock_client.capture.call_args[1]
+    assert call_args["groups"] == {"company": "company_123"}
+
+
+async def test_async_client_privacy_mode_local(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test local privacy mode with async Client API"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Hello"],
+        posthog_distinct_id="test-id",
+        posthog_privacy_mode=True,
+    )
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] is None
+    assert props["$ai_output_choices"] is None
+
+
+async def test_async_client_privacy_mode_global(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test global privacy mode with async Client API"""
+    mock_client.privacy_mode = True
+
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Hello"],
+        posthog_distinct_id="test-id",
+    )
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] is None
+    assert props["$ai_output_choices"] is None
+
+
+async def test_async_client_different_input_formats(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test different input formats with async Client API"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    # Test string input
+    await client.models.generate_content(
+        model="gemini-2.0-flash", contents="Hello", posthog_distinct_id="test-id"
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
+
+    # Test Gemini-specific format with parts array
+    mock_client.reset_mock()
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=[{"role": "user", "parts": [{"text": "hey"}]}],
+        posthog_distinct_id="test-id",
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [
+        {"role": "user", "content": [{"type": "text", "text": "hey"}]}
+    ]
+
+    # Test multiple parts in the parts array
+    mock_client.reset_mock()
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=[{"role": "user", "parts": [{"text": "Hello "}, {"text": "world"}]}],
+        posthog_distinct_id="test-id",
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Hello "},
+                {"type": "text", "text": "world"},
+            ],
+        }
+    ]
+
+    # Test list input with string
+    mock_client.capture.reset_mock()
+    await client.models.generate_content(
+        model="gemini-2.0-flash", contents=["List item"], posthog_distinct_id="test-id"
+    )
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_input"] == [{"role": "user", "content": "List item"}]
+
+
+async def test_async_client_model_parameters(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test model parameters with async Client API"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Hello"],
+        posthog_distinct_id="test-id",
+        temperature=0.7,
+        max_tokens=100,
+    )
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+    assert props["$ai_model_parameters"]["temperature"] == 0.7
+    assert props["$ai_model_parameters"]["max_tokens"] == 100
+
+
+async def test_async_client_default_settings(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test async client with default PostHog settings"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(
+        api_key="test-key",
+        posthog_client=mock_client,
+        posthog_distinct_id="default_user",
+        posthog_properties={"team": "ai"},
+        posthog_privacy_mode=False,
+        posthog_groups={"company": "acme_corp"},
+    )
+
+    # Call without overriding defaults
+    await client.models.generate_content(model="gemini-2.0-flash", contents=["Hello"])
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "default_user"
+    assert call_args["groups"] == {"company": "acme_corp"}
+    assert props["team"] == "ai"
+
+
+async def test_async_client_override_defaults(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test overriding async client defaults per call"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    client = AsyncClient(
+        api_key="test-key",
+        posthog_client=mock_client,
+        posthog_distinct_id="default_user",
+        posthog_properties={"team": "ai"},
+        posthog_privacy_mode=False,
+        posthog_groups={"company": "acme_corp"},
+    )
+
+    # Override defaults in call
+    await client.models.generate_content(
+        model="gemini-2.0-flash",
+        contents=["Hello"],
+        posthog_distinct_id="specific_user",
+        posthog_properties={"feature": "chat", "urgent": True},
+        posthog_privacy_mode=True,
+        posthog_groups={"organization": "special_org"},
+    )
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Check overrides
+    assert call_args["distinct_id"] == "specific_user"
+    assert call_args["groups"] == {"organization": "special_org"}
+    assert props["$ai_input"] is None  # privacy mode was overridden
+
+    # Check merged properties (defaults + call-specific)
+    assert props["team"] == "ai"  # from defaults
+    assert props["feature"] == "chat"  # from call
+    assert props["urgent"] is True  # from call
+
+
+async def test_async_vertex_ai_parameters_passed_through(
+    mock_client, mock_google_genai_client, mock_gemini_response
+):
+    """Test that Vertex AI parameters are properly passed to genai.Client"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response
+    )
+
+    # Mock credentials object
+    mock_credentials = MagicMock()
+    mock_debug_config = MagicMock()
+    mock_http_options = MagicMock()
+
+    # Create client with Vertex AI parameters
+    AsyncClient(
+        vertexai=True,
+        credentials=mock_credentials,
+        project="test-project",
+        location="us-central1",
+        debug_config=mock_debug_config,
+        http_options=mock_http_options,
+        posthog_client=mock_client,
+    )
+
+    # Verify genai.Client was called with correct parameters
+    google_genai.Client.assert_called_once_with(
+        vertexai=True,
+        credentials=mock_credentials,
+        project="test-project",
+        location="us-central1",
+        debug_config=mock_debug_config,
+        http_options=mock_http_options,
+    )
+
+
+async def test_async_api_key_mode(mock_client, mock_google_genai_client):
+    """Test API key authentication mode with async client"""
+
+    # Create async client with just API key (traditional mode)
+    AsyncClient(
+        api_key="test-api-key",
+        posthog_client=mock_client,
+    )
+
+    # Verify genai.Client was called with only api_key
+    google_genai.Client.assert_called_once_with(api_key="test-api-key")
+
+
+async def test_async_function_calls_in_output_choices(
+    mock_client, mock_google_genai_client, mock_gemini_response_with_function_calls
+):
+    """Test that function calls are properly included in $ai_output_choices with async"""
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_gemini_response_with_function_calls
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents=["What's the weather in San Francisco?"],
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_gemini_response_with_function_calls
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    assert call_args["distinct_id"] == "test-id"
+    assert call_args["event"] == "$ai_generation"
+    assert props["$ai_provider"] == "gemini"
+    assert props["$ai_model"] == "gemini-2.5-flash"
+    assert props["$ai_output_choices"] == [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "I'll check the weather for you."},
+                {"type": "text", "text": " Let me look that up."},
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "get_current_weather",
+                        "arguments": {"location": "San Francisco"},
+                    },
+                },
+            ],
+        }
+    ]
+
+    # Check token usage
+    assert props["$ai_input_tokens"] == 25
+    assert props["$ai_output_tokens"] == 15
+    assert props["$ai_http_status"] == 200
+
+
+async def test_async_cache_and_reasoning_tokens(mock_client, mock_google_genai_client):
+    """Test that cache and reasoning tokens are properly extracted with async"""
+    # Create a mock response with cache and reasoning tokens
+    mock_response = MagicMock()
+    mock_response.text = "Test response with cache"
+
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 100
+    mock_usage.candidates_token_count = 50
+    mock_usage.cached_content_token_count = 30  # Cache tokens
+    mock_usage.thoughts_token_count = 10  # Reasoning tokens
+    mock_response.usage_metadata = mock_usage
+
+    # Mock candidates
+    mock_candidate = MagicMock()
+    mock_candidate.text = "Test response with cache"
+    mock_response.candidates = [mock_candidate]
+
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content(
+        model="gemini-2.5-pro",
+        contents="Test with cache",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Check that all token types are present
+    assert props["$ai_input_tokens"] == 100
+    assert props["$ai_output_tokens"] == 50
+    assert props["$ai_cache_read_input_tokens"] == 30
+    assert props["$ai_reasoning_tokens"] == 10
+
+
+async def test_async_streaming_cache_and_reasoning_tokens(
+    mock_client, mock_google_genai_client
+):
+    """Test that cache and reasoning tokens are properly extracted in async streaming"""
+
+    async def mock_streaming_response():
+        # Create mock chunks with cache and reasoning tokens
+        chunk1 = MagicMock()
+        chunk1.text = "Hello "
+        chunk1_usage = MagicMock()
+        chunk1_usage.prompt_token_count = 100
+        chunk1_usage.candidates_token_count = 5
+        chunk1_usage.cached_content_token_count = 30  # Cache tokens
+        chunk1_usage.thoughts_token_count = 0
+        chunk1.usage_metadata = chunk1_usage
+        yield chunk1
+
+        chunk2 = MagicMock()
+        chunk2.text = "world!"
+        chunk2_usage = MagicMock()
+        chunk2_usage.prompt_token_count = 100
+        chunk2_usage.candidates_token_count = 10
+        chunk2_usage.cached_content_token_count = 30  # Same cache tokens
+        chunk2_usage.thoughts_token_count = 5  # Reasoning tokens
+        chunk2.usage_metadata = chunk2_usage
+        yield chunk2
+
+    mock_google_genai_client.aio.models.generate_content_stream = AsyncMock(
+        return_value=mock_streaming_response()
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content_stream(
+        model="gemini-2.5-pro",
+        contents="Test streaming with cache",
+        posthog_distinct_id="test-id",
+    )
+
+    # Consume the stream
+    result = []
+    async for chunk in response:
+        result.append(chunk)
+
+    assert len(result) == 2
+
+    # Check PostHog capture was called
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Check that all token types are present (should use final chunk's usage)
+    assert props["$ai_input_tokens"] == 100
+    assert props["$ai_output_tokens"] == 10
+    assert props["$ai_cache_read_input_tokens"] == 30
+    assert props["$ai_reasoning_tokens"] == 5
+
+
+async def test_async_web_search_grounding(mock_client, mock_google_genai_client):
+    """Test async web search detection via grounding_metadata."""
+
+    # Create mock response with grounding metadata
+    mock_response = MagicMock()
+
+    # Mock usage metadata
+    mock_usage = MagicMock()
+    mock_usage.prompt_token_count = 60
+    mock_usage.candidates_token_count = 40
+    mock_usage.cached_content_token_count = 0
+    mock_usage.thoughts_token_count = 0
+    mock_response.usage_metadata = mock_usage
+
+    # Mock grounding metadata
+    mock_grounding_chunk = MagicMock()
+    mock_grounding_chunk.uri = "https://example.com"
+
+    mock_grounding_metadata = MagicMock()
+    mock_grounding_metadata.grounding_chunks = [mock_grounding_chunk]
+
+    # Mock text part
+    mock_text_part = MagicMock()
+    mock_text_part.text = "According to search results..."
+    type(mock_text_part).text = mock_text_part.text
+
+    # Mock content with parts
+    mock_content = MagicMock()
+    mock_content.parts = [mock_text_part]
+
+    # Mock candidate with grounding metadata
+    mock_candidate = MagicMock()
+    mock_candidate.content = mock_content
+    mock_candidate.grounding_metadata = mock_grounding_metadata
+    type(mock_candidate).grounding_metadata = mock_candidate.grounding_metadata
+
+    mock_response.candidates = [mock_candidate]
+    mock_response.text = "According to search results..."
+
+    # Mock the async generate_content method
+    mock_google_genai_client.aio.models.generate_content = AsyncMock(
+        return_value=mock_response
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+    response = await client.models.generate_content(
+        model="gemini-2.5-flash",
+        contents="What's the latest news?",
+        posthog_distinct_id="test-id",
+    )
+
+    assert response == mock_response
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is detected (binary for grounding)
+    assert props["$ai_web_search_count"] == 1
+    assert props["$ai_input_tokens"] == 60
+    assert props["$ai_output_tokens"] == 40
+
+
+async def test_async_streaming_with_web_search(mock_client, mock_google_genai_client):
+    """Test that web search count is properly captured in async streaming mode."""
+
+    async def mock_streaming_response():
+        # Create chunk 1 with grounding metadata
+        mock_chunk1 = MagicMock()
+        mock_chunk1.text = "According to "
+
+        mock_usage1 = MagicMock()
+        mock_usage1.prompt_token_count = 30
+        mock_usage1.candidates_token_count = 5
+        mock_usage1.cached_content_token_count = 0
+        mock_usage1.thoughts_token_count = 0
+        mock_chunk1.usage_metadata = mock_usage1
+
+        # Add grounding metadata to first chunk
+        mock_grounding_chunk = MagicMock()
+        mock_grounding_chunk.uri = "https://example.com"
+
+        mock_grounding_metadata = MagicMock()
+        mock_grounding_metadata.grounding_chunks = [mock_grounding_chunk]
+
+        mock_candidate1 = MagicMock()
+        mock_candidate1.grounding_metadata = mock_grounding_metadata
+        type(mock_candidate1).grounding_metadata = mock_candidate1.grounding_metadata
+
+        mock_chunk1.candidates = [mock_candidate1]
+        yield mock_chunk1
+
+        # Create chunk 2
+        mock_chunk2 = MagicMock()
+        mock_chunk2.text = "search results..."
+
+        mock_usage2 = MagicMock()
+        mock_usage2.prompt_token_count = 30
+        mock_usage2.candidates_token_count = 15
+        mock_usage2.cached_content_token_count = 0
+        mock_usage2.thoughts_token_count = 0
+        mock_chunk2.usage_metadata = mock_usage2
+
+        mock_candidate2 = MagicMock()
+        mock_chunk2.candidates = [mock_candidate2]
+        yield mock_chunk2
+
+    # Mock the async generate_content_stream method
+    mock_google_genai_client.aio.models.generate_content_stream = AsyncMock(
+        return_value=mock_streaming_response()
+    )
+
+    client = AsyncClient(api_key="test-key", posthog_client=mock_client)
+
+    response = await client.models.generate_content_stream(
+        model="gemini-2.5-flash",
+        contents="What's the latest news?",
+        posthog_distinct_id="test-id",
+    )
+
+    chunks = []
+    async for chunk in response:
+        chunks.append(chunk)
+
+    assert len(chunks) == 2
+    assert mock_client.capture.call_count == 1
+
+    call_args = mock_client.capture.call_args[1]
+    props = call_args["properties"]
+
+    # Verify web search count is detected (binary for grounding)
+    assert props["$ai_web_search_count"] == 1
+    assert props["$ai_input_tokens"] == 30
+    assert props["$ai_output_tokens"] == 15

posthog/test/ai/langchain/__init__.py

@@ -1,5 +1,5 @@
 import pytest
 
-pytest.importorskip("langchain")
+pytest.importorskip("langchain_core")
 pytest.importorskip("langchain_community")
 pytest.importorskip("langgraph")

posthog/test/ai/openai_agents/__init__.py

@@ -0,0 +1 @@
+# Tests for OpenAI Agents SDK integration

posthog/test/ai/openai_agents/test_processor.py

@@ -0,0 +1,810 @@
+import logging
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+try:
+    from agents.tracing.span_data import (
+        AgentSpanData,
+        CustomSpanData,
+        FunctionSpanData,
+        GenerationSpanData,
+        GuardrailSpanData,
+        HandoffSpanData,
+        ResponseSpanData,
+        SpeechSpanData,
+        TranscriptionSpanData,
+    )
+
+    from posthog.ai.openai_agents import PostHogTracingProcessor, instrument
+
+    OPENAI_AGENTS_AVAILABLE = True
+except ImportError:
+    OPENAI_AGENTS_AVAILABLE = False
+
+
+# Skip all tests if OpenAI Agents SDK is not available
+pytestmark = pytest.mark.skipif(
+    not OPENAI_AGENTS_AVAILABLE, reason="OpenAI Agents SDK is not available"
+)
+
+
+@pytest.fixture(scope="function")
+def mock_client():
+    client = MagicMock()
+    client.privacy_mode = False
+    logging.getLogger("posthog").setLevel(logging.DEBUG)
+    return client
+
+
+@pytest.fixture(scope="function")
+def processor(mock_client):
+    return PostHogTracingProcessor(
+        client=mock_client,
+        distinct_id="test-user",
+        privacy_mode=False,
+    )
+
+
+@pytest.fixture
+def mock_trace():
+    trace = MagicMock()
+    trace.trace_id = "trace_123456789"
+    trace.name = "Test Workflow"
+    trace.group_id = "group_123"
+    trace.metadata = {"key": "value"}
+    return trace
+
+
+@pytest.fixture
+def mock_span():
+    span = MagicMock()
+    span.trace_id = "trace_123456789"
+    span.span_id = "span_987654321"
+    span.parent_id = None
+    span.started_at = "2024-01-01T00:00:00Z"
+    span.ended_at = "2024-01-01T00:00:01Z"
+    span.error = None
+    return span
+
+
+class TestPostHogTracingProcessor:
+    """Tests for the PostHogTracingProcessor class."""
+
+    def test_initialization(self, mock_client):
+        """Test processor initializes correctly."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="user@example.com",
+            privacy_mode=True,
+            groups={"company": "acme"},
+            properties={"env": "test"},
+        )
+
+        assert processor._client == mock_client
+        assert processor._distinct_id == "user@example.com"
+        assert processor._privacy_mode is True
+        assert processor._groups == {"company": "acme"}
+        assert processor._properties == {"env": "test"}
+
+    def test_initialization_with_callable_distinct_id(self, mock_client, mock_trace):
+        """Test processor with callable distinct_id resolver."""
+
+        def resolver(trace):
+            return trace.metadata.get("user_id", "default")
+
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id=resolver,
+        )
+
+        mock_trace.metadata = {"user_id": "resolved-user"}
+        distinct_id = processor._get_distinct_id(mock_trace)
+        assert distinct_id == "resolved-user"
+
+    def test_on_trace_start_stores_metadata(self, processor, mock_client, mock_trace):
+        """Test that on_trace_start stores metadata but does not capture an event."""
+        processor.on_trace_start(mock_trace)
+
+        mock_client.capture.assert_not_called()
+        assert mock_trace.trace_id in processor._trace_metadata
+
+    def test_on_trace_end_captures_ai_trace(self, processor, mock_client, mock_trace):
+        """Test that on_trace_end captures $ai_trace event."""
+        processor.on_trace_start(mock_trace)
+        processor.on_trace_end(mock_trace)
+
+        mock_client.capture.assert_called_once()
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_trace"
+        assert call_kwargs["distinct_id"] == "test-user"
+        assert call_kwargs["properties"]["$ai_trace_id"] == "trace_123456789"
+        assert call_kwargs["properties"]["$ai_trace_name"] == "Test Workflow"
+        assert call_kwargs["properties"]["$ai_provider"] == "openai"
+        assert call_kwargs["properties"]["$ai_framework"] == "openai-agents"
+        assert "$ai_latency" in call_kwargs["properties"]
+
+    def test_personless_mode_when_no_distinct_id(self, mock_client, mock_trace):
+        """Test that trace events use personless mode when no distinct_id is provided."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+        )
+
+        processor.on_trace_start(mock_trace)
+        processor.on_trace_end(mock_trace)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$process_person_profile"] is False
+        # Should fallback to trace_id as the distinct_id
+        assert call_kwargs["distinct_id"] == mock_trace.trace_id
+
+    def test_personless_mode_for_spans_when_no_distinct_id(
+        self, mock_client, mock_trace, mock_span
+    ):
+        """Test that span events use personless mode when no distinct_id is provided."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+        )
+
+        processor.on_trace_start(mock_trace)
+        mock_client.capture.reset_mock()
+
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$process_person_profile"] is False
+        assert call_kwargs["distinct_id"] == mock_span.trace_id
+
+    def test_personless_mode_when_callable_returns_none(
+        self, mock_client, mock_trace, mock_span
+    ):
+        """Test personless mode when callable distinct_id returns None."""
+
+        def resolver(trace):
+            return None  # Simulate no user ID available
+
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id=resolver,
+        )
+
+        processor.on_trace_start(mock_trace)
+        mock_client.capture.reset_mock()
+
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$process_person_profile"] is False
+        assert call_kwargs["distinct_id"] == mock_span.trace_id
+
+    def test_person_profile_when_distinct_id_provided(self, mock_client, mock_trace):
+        """Test that events create person profiles when distinct_id is provided."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="real-user",
+        )
+
+        processor.on_trace_start(mock_trace)
+        processor.on_trace_end(mock_trace)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert "$process_person_profile" not in call_kwargs["properties"]
+
+    def test_on_trace_end_clears_metadata(self, processor, mock_client, mock_trace):
+        """Test that on_trace_end clears stored trace metadata."""
+        processor.on_trace_start(mock_trace)
+        assert mock_trace.trace_id in processor._trace_metadata
+
+        processor.on_trace_end(mock_trace)
+        assert mock_trace.trace_id not in processor._trace_metadata
+        # Also verify it captured the event
+        mock_client.capture.assert_called_once()
+
+    def test_on_span_start_tracks_time(self, processor, mock_span):
+        """Test that on_span_start records start time."""
+        processor.on_span_start(mock_span)
+        assert mock_span.span_id in processor._span_start_times
+
+    def test_generation_span_mapping(self, processor, mock_client, mock_span):
+        """Test GenerationSpanData maps to $ai_generation event."""
+        span_data = GenerationSpanData(
+            input=[{"role": "user", "content": "Hello"}],
+            output=[{"role": "assistant", "content": "Hi there!"}],
+            model="gpt-4o",
+            model_config={"temperature": 0.7, "max_tokens": 100},
+            usage={"input_tokens": 10, "output_tokens": 20},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        mock_client.capture.assert_called_once()
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_generation"
+        assert call_kwargs["properties"]["$ai_trace_id"] == "trace_123456789"
+        assert call_kwargs["properties"]["$ai_span_id"] == "span_987654321"
+        assert call_kwargs["properties"]["$ai_provider"] == "openai"
+        assert call_kwargs["properties"]["$ai_framework"] == "openai-agents"
+        assert call_kwargs["properties"]["$ai_model"] == "gpt-4o"
+        assert call_kwargs["properties"]["$ai_input_tokens"] == 10
+        assert call_kwargs["properties"]["$ai_output_tokens"] == 20
+        assert call_kwargs["properties"]["$ai_input"] == [
+            {"role": "user", "content": "Hello"}
+        ]
+        assert call_kwargs["properties"]["$ai_output_choices"] == [
+            {"role": "assistant", "content": "Hi there!"}
+        ]
+
+    def test_generation_span_with_reasoning_tokens(
+        self, processor, mock_client, mock_span
+    ):
+        """Test GenerationSpanData includes reasoning tokens when present."""
+        span_data = GenerationSpanData(
+            model="o1-preview",
+            usage={
+                "input_tokens": 100,
+                "output_tokens": 500,
+                "reasoning_tokens": 400,
+            },
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_reasoning_tokens"] == 400
+
+    def test_function_span_mapping(self, processor, mock_client, mock_span):
+        """Test FunctionSpanData maps to $ai_span event with type=tool."""
+        span_data = FunctionSpanData(
+            name="get_weather",
+            input='{"city": "San Francisco"}',
+            output="Sunny, 72F",
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_name"] == "get_weather"
+        assert call_kwargs["properties"]["$ai_span_type"] == "tool"
+        assert (
+            call_kwargs["properties"]["$ai_input_state"] == '{"city": "San Francisco"}'
+        )
+        assert call_kwargs["properties"]["$ai_output_state"] == "Sunny, 72F"
+
+    def test_agent_span_mapping(self, processor, mock_client, mock_span):
+        """Test AgentSpanData maps to $ai_span event with type=agent."""
+        span_data = AgentSpanData(
+            name="CustomerServiceAgent",
+            handoffs=["TechnicalAgent", "BillingAgent"],
+            tools=["search", "get_order"],
+            output_type="str",
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_name"] == "CustomerServiceAgent"
+        assert call_kwargs["properties"]["$ai_span_type"] == "agent"
+        assert call_kwargs["properties"]["$ai_agent_handoffs"] == [
+            "TechnicalAgent",
+            "BillingAgent",
+        ]
+        assert call_kwargs["properties"]["$ai_agent_tools"] == ["search", "get_order"]
+
+    def test_handoff_span_mapping(self, processor, mock_client, mock_span):
+        """Test HandoffSpanData maps to $ai_span event with type=handoff."""
+        span_data = HandoffSpanData(
+            from_agent="TriageAgent",
+            to_agent="TechnicalAgent",
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_type"] == "handoff"
+        assert call_kwargs["properties"]["$ai_handoff_from_agent"] == "TriageAgent"
+        assert call_kwargs["properties"]["$ai_handoff_to_agent"] == "TechnicalAgent"
+        assert (
+            call_kwargs["properties"]["$ai_span_name"]
+            == "TriageAgent -> TechnicalAgent"
+        )
+
+    def test_guardrail_span_mapping(self, processor, mock_client, mock_span):
+        """Test GuardrailSpanData maps to $ai_span event with type=guardrail."""
+        span_data = GuardrailSpanData(
+            name="ContentFilter",
+            triggered=True,
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_name"] == "ContentFilter"
+        assert call_kwargs["properties"]["$ai_span_type"] == "guardrail"
+        assert call_kwargs["properties"]["$ai_guardrail_triggered"] is True
+
+    def test_custom_span_mapping(self, processor, mock_client, mock_span):
+        """Test CustomSpanData maps to $ai_span event with type=custom."""
+        span_data = CustomSpanData(
+            name="database_query",
+            data={"query": "SELECT * FROM users", "rows": 100},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_name"] == "database_query"
+        assert call_kwargs["properties"]["$ai_span_type"] == "custom"
+        assert call_kwargs["properties"]["$ai_custom_data"] == {
+            "query": "SELECT * FROM users",
+            "rows": 100,
+        }
+
+    def test_privacy_mode_redacts_content(self, mock_client, mock_span):
+        """Test that privacy_mode redacts input/output content."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="test-user",
+            privacy_mode=True,
+        )
+
+        span_data = GenerationSpanData(
+            input=[{"role": "user", "content": "Secret message"}],
+            output=[{"role": "assistant", "content": "Secret response"}],
+            model="gpt-4o",
+            usage={"input_tokens": 10, "output_tokens": 20},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        # Content should be redacted
+        assert call_kwargs["properties"]["$ai_input"] is None
+        assert call_kwargs["properties"]["$ai_output_choices"] is None
+        # Token counts should still be present
+        assert call_kwargs["properties"]["$ai_input_tokens"] == 10
+        assert call_kwargs["properties"]["$ai_output_tokens"] == 20
+
+    def test_error_handling_in_span(self, processor, mock_client, mock_span):
+        """Test that span errors are captured correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {"message": "Rate limit exceeded", "data": {"code": 429}}
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["properties"]["$ai_is_error"] is True
+        assert call_kwargs["properties"]["$ai_error"] == "Rate limit exceeded"
+
+    def test_generation_span_includes_total_tokens(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that $ai_total_tokens is calculated and included."""
+        span_data = GenerationSpanData(
+            model="gpt-4o",
+            usage={"input_tokens": 100, "output_tokens": 50},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_total_tokens"] == 150
+
+    def test_error_type_categorization_model_behavior(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that ModelBehaviorError is categorized correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {
+            "message": "ModelBehaviorError: Invalid JSON output",
+            "type": "ModelBehaviorError",
+        }
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_error_type"] == "model_behavior_error"
+
+    def test_error_type_categorization_user_error(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that UserError is categorized correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {"message": "UserError: Tool failed", "type": "UserError"}
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_error_type"] == "user_error"
+
+    def test_error_type_categorization_input_guardrail(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that InputGuardrailTripwireTriggered is categorized correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {
+            "message": "InputGuardrailTripwireTriggered: Content blocked"
+        }
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert (
+            call_kwargs["properties"]["$ai_error_type"] == "input_guardrail_triggered"
+        )
+
+    def test_error_type_categorization_output_guardrail(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that OutputGuardrailTripwireTriggered is categorized correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {
+            "message": "OutputGuardrailTripwireTriggered: Response blocked"
+        }
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert (
+            call_kwargs["properties"]["$ai_error_type"] == "output_guardrail_triggered"
+        )
+
+    def test_error_type_categorization_max_turns(
+        self, processor, mock_client, mock_span
+    ):
+        """Test that MaxTurnsExceeded is categorized correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {"message": "MaxTurnsExceeded: Agent exceeded maximum turns"}
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_error_type"] == "max_turns_exceeded"
+
+    def test_error_type_categorization_unknown(self, processor, mock_client, mock_span):
+        """Test that unknown errors are categorized as unknown."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {"message": "Some random error occurred"}
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_error_type"] == "unknown"
+
+    def test_response_span_with_output_and_total_tokens(
+        self, processor, mock_client, mock_span
+    ):
+        """Test ResponseSpanData includes output choices and total tokens."""
+        # Create a mock response object
+        mock_response = MagicMock()
+        mock_response.id = "resp_123"
+        mock_response.model = "gpt-4o"
+        mock_response.output = [{"type": "message", "content": "Hello!"}]
+        mock_response.usage = MagicMock()
+        mock_response.usage.input_tokens = 25
+        mock_response.usage.output_tokens = 10
+
+        span_data = ResponseSpanData(
+            response=mock_response,
+            input="Hello, world!",
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_generation"
+        assert call_kwargs["properties"]["$ai_total_tokens"] == 35
+        assert call_kwargs["properties"]["$ai_output_choices"] == [
+            {"type": "message", "content": "Hello!"}
+        ]
+        assert call_kwargs["properties"]["$ai_response_id"] == "resp_123"
+
+    def test_speech_span_with_pass_through_properties(
+        self, processor, mock_client, mock_span
+    ):
+        """Test SpeechSpanData includes pass-through properties."""
+        span_data = SpeechSpanData(
+            input="Hello, how can I help you?",
+            output="base64_audio_data",
+            output_format="pcm",
+            model="tts-1",
+            model_config={"voice": "alloy", "speed": 1.0},
+            first_content_at="2024-01-01T00:00:00.500Z",
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_type"] == "speech"
+        assert call_kwargs["properties"]["$ai_model"] == "tts-1"
+        # Pass-through properties (no $ai_ prefix)
+        assert (
+            call_kwargs["properties"]["first_content_at"] == "2024-01-01T00:00:00.500Z"
+        )
+        assert call_kwargs["properties"]["audio_output_format"] == "pcm"
+        assert call_kwargs["properties"]["model_config"] == {
+            "voice": "alloy",
+            "speed": 1.0,
+        }
+        # Text input should be captured
+        assert call_kwargs["properties"]["$ai_input"] == "Hello, how can I help you?"
+
+    def test_transcription_span_with_pass_through_properties(
+        self, processor, mock_client, mock_span
+    ):
+        """Test TranscriptionSpanData includes pass-through properties."""
+        span_data = TranscriptionSpanData(
+            input="base64_audio_data",
+            input_format="pcm",
+            output="This is the transcribed text.",
+            model="whisper-1",
+            model_config={"language": "en"},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+
+        assert call_kwargs["event"] == "$ai_span"
+        assert call_kwargs["properties"]["$ai_span_type"] == "transcription"
+        assert call_kwargs["properties"]["$ai_model"] == "whisper-1"
+        # Pass-through properties (no $ai_ prefix)
+        assert call_kwargs["properties"]["audio_input_format"] == "pcm"
+        assert call_kwargs["properties"]["model_config"] == {"language": "en"}
+        # Transcription output should be captured
+        assert (
+            call_kwargs["properties"]["$ai_output_state"]
+            == "This is the transcribed text."
+        )
+
+    def test_latency_calculation(self, processor, mock_client, mock_span):
+        """Test that latency is calculated correctly."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+
+        with patch("time.time") as mock_time:
+            mock_time.return_value = 1000.0
+            processor.on_span_start(mock_span)
+
+            mock_time.return_value = 1001.5  # 1.5 seconds later
+            processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_latency"] == pytest.approx(1.5, rel=0.01)
+
+    def test_groups_included_in_events(self, mock_client, mock_trace, mock_span):
+        """Test that groups are included in captured events."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="test-user",
+            groups={"company": "acme", "team": "engineering"},
+        )
+
+        processor.on_trace_start(mock_trace)
+        processor.on_trace_end(mock_trace)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["groups"] == {"company": "acme", "team": "engineering"}
+
+    def test_additional_properties_included(self, mock_client, mock_trace):
+        """Test that additional properties are included in events."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="test-user",
+            properties={"environment": "production", "version": "1.0"},
+        )
+
+        processor.on_trace_start(mock_trace)
+        processor.on_trace_end(mock_trace)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["environment"] == "production"
+        assert call_kwargs["properties"]["version"] == "1.0"
+
+    def test_shutdown_clears_state(self, processor):
+        """Test that shutdown clears internal state."""
+        processor._span_start_times["span_1"] = 1000.0
+        processor._trace_metadata["trace_1"] = {"name": "test"}
+
+        processor.shutdown()
+
+        assert len(processor._span_start_times) == 0
+        assert len(processor._trace_metadata) == 0
+
+    def test_force_flush_calls_client_flush(self, processor, mock_client):
+        """Test that force_flush calls client.flush()."""
+        processor.force_flush()
+        mock_client.flush.assert_called_once()
+
+    def test_generation_span_with_no_usage(self, processor, mock_client, mock_span):
+        """Test GenerationSpanData with no usage data defaults to zero tokens."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_input_tokens"] == 0
+        assert call_kwargs["properties"]["$ai_output_tokens"] == 0
+        assert call_kwargs["properties"]["$ai_total_tokens"] == 0
+
+    def test_generation_span_with_partial_usage(
+        self, processor, mock_client, mock_span
+    ):
+        """Test GenerationSpanData with only input_tokens present."""
+        span_data = GenerationSpanData(
+            model="gpt-4o",
+            usage={"input_tokens": 42},
+        )
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_input_tokens"] == 42
+        assert call_kwargs["properties"]["$ai_output_tokens"] == 0
+        assert call_kwargs["properties"]["$ai_total_tokens"] == 42
+
+    def test_error_type_categorization_by_type_field_only(
+        self, processor, mock_client, mock_span
+    ):
+        """Test error categorization works when only the type field matches."""
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+        mock_span.error = {
+            "message": "Something went wrong",
+            "type": "ModelBehaviorError",
+        }
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["properties"]["$ai_error_type"] == "model_behavior_error"
+
+    def test_distinct_id_resolved_from_trace_for_spans(
+        self, mock_client, mock_trace, mock_span
+    ):
+        """Test that spans use the distinct_id resolved at trace start."""
+
+        def resolver(trace):
+            return f"user-{trace.name}"
+
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id=resolver,
+        )
+
+        # Start trace - this resolves and stores distinct_id
+        processor.on_trace_start(mock_trace)
+        mock_client.capture.reset_mock()
+
+        # End a span - should use the stored distinct_id from trace
+        span_data = GenerationSpanData(model="gpt-4o")
+        mock_span.span_data = span_data
+
+        processor.on_span_start(mock_span)
+        processor.on_span_end(mock_span)
+
+        call_kwargs = mock_client.capture.call_args[1]
+        assert call_kwargs["distinct_id"] == "user-Test Workflow"
+
+    def test_eviction_of_stale_entries(self, mock_client):
+        """Test that stale entries are evicted when max is exceeded."""
+        processor = PostHogTracingProcessor(
+            client=mock_client,
+            distinct_id="test-user",
+        )
+        processor._max_tracked_entries = 10
+
+        # Fill beyond max
+        for i in range(15):
+            processor._span_start_times[f"span_{i}"] = float(i)
+            processor._trace_metadata[f"trace_{i}"] = {"name": f"trace_{i}"}
+
+        processor._evict_stale_entries()
+
+        # Should have evicted half
+        assert len(processor._span_start_times) <= 10
+        assert len(processor._trace_metadata) <= 10
+
+
+class TestInstrumentHelper:
+    """Tests for the instrument() convenience function."""
+
+    def test_instrument_registers_processor(self, mock_client):
+        """Test that instrument() registers a processor."""
+        with patch("agents.tracing.add_trace_processor") as mock_add:
+            processor = instrument(
+                client=mock_client,
+                distinct_id="test-user",
+            )
+
+            mock_add.assert_called_once_with(processor)
+            assert isinstance(processor, PostHogTracingProcessor)
+
+    def test_instrument_with_privacy_mode(self, mock_client):
+        """Test instrument() respects privacy_mode."""
+        with patch("agents.tracing.add_trace_processor"):
+            processor = instrument(
+                client=mock_client,
+                privacy_mode=True,
+            )
+
+            assert processor._privacy_mode is True
+
+    def test_instrument_with_groups_and_properties(self, mock_client):
+        """Test instrument() accepts groups and properties."""
+        with patch("agents.tracing.add_trace_processor"):
+            processor = instrument(
+                client=mock_client,
+                groups={"company": "acme"},
+                properties={"env": "test"},
+            )
+
+            assert processor._groups == {"company": "acme"}
+            assert processor._properties == {"env": "test"}

posthog/test/ai/test_prompts.py

@@ -0,0 +1,607 @@
+import unittest
+from unittest.mock import MagicMock, patch
+
+from posthog.ai.prompts import Prompts
+
+
+class MockResponse:
+    """Mock HTTP response for testing."""
+
+    def __init__(self, json_data=None, status_code=200, ok=True):
+        self._json_data = json_data
+        self.status_code = status_code
+        self.ok = ok
+
+    def json(self):
+        if self._json_data is None:
+            raise ValueError("No JSON data")
+        return self._json_data
+
+
+class TestPrompts(unittest.TestCase):
+    """Tests for the Prompts class."""
+
+    mock_prompt_response = {
+        "id": 1,
+        "name": "test-prompt",
+        "prompt": "Hello, {{name}}! You are a helpful assistant for {{company}}.",
+        "version": 1,
+        "created_by": "user@example.com",
+        "created_at": "2024-01-01T00:00:00Z",
+        "updated_at": "2024-01-01T00:00:00Z",
+        "deleted": False,
+    }
+
+    def create_mock_posthog(
+        self,
+        personal_api_key="phx_test_key",
+        project_api_key="phc_test_key",
+        host="https://us.posthog.com",
+    ):
+        """Create a mock PostHog client."""
+        mock = MagicMock()
+        mock.personal_api_key = personal_api_key
+        mock.api_key = project_api_key
+        mock.raw_host = host
+        return mock
+
+
+class TestPromptsGet(TestPrompts):
+    """Tests for the Prompts.get() method."""
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_successfully_fetch_a_prompt(self, mock_get_session):
+        """Should successfully fetch a prompt."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.get("test-prompt")
+
+        self.assertEqual(result, self.mock_prompt_response["prompt"])
+        mock_get.assert_called_once()
+        call_args = mock_get.call_args
+        self.assertEqual(
+            call_args[0][0],
+            "https://us.posthog.com/api/environments/@current/llm_prompts/name/test-prompt/?token=phc_test_key",
+        )
+        self.assertIn("Authorization", call_args[1]["headers"])
+        self.assertEqual(
+            call_args[1]["headers"]["Authorization"], "Bearer phx_test_key"
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    def test_return_cached_prompt_when_fresh(self, mock_time, mock_get_session):
+        """Should return cached prompt when fresh (no API call)."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+        mock_time.return_value = 1000.0
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # First call - fetches from API
+        result1 = prompts.get("test-prompt", cache_ttl_seconds=300)
+        self.assertEqual(result1, self.mock_prompt_response["prompt"])
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time by 60 seconds (still within TTL)
+        mock_time.return_value = 1060.0
+
+        # Second call - should use cache
+        result2 = prompts.get("test-prompt", cache_ttl_seconds=300)
+        self.assertEqual(result2, self.mock_prompt_response["prompt"])
+        self.assertEqual(mock_get.call_count, 1)  # No additional fetch
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    def test_refetch_when_cache_is_stale(self, mock_time, mock_get_session):
+        """Should refetch when cache is stale."""
+        mock_get = mock_get_session.return_value.get
+        updated_prompt_response = {
+            **self.mock_prompt_response,
+            "prompt": "Updated prompt: Hello, {{name}}!",
+        }
+
+        mock_get.side_effect = [
+            MockResponse(json_data=self.mock_prompt_response),
+            MockResponse(json_data=updated_prompt_response),
+        ]
+        mock_time.return_value = 1000.0
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # First call - fetches from API
+        result1 = prompts.get("test-prompt", cache_ttl_seconds=60)
+        self.assertEqual(result1, self.mock_prompt_response["prompt"])
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time past TTL
+        mock_time.return_value = 1061.0
+
+        # Second call - should refetch
+        result2 = prompts.get("test-prompt", cache_ttl_seconds=60)
+        self.assertEqual(result2, updated_prompt_response["prompt"])
+        self.assertEqual(mock_get.call_count, 2)
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    @patch("posthog.ai.prompts.log")
+    def test_use_stale_cache_on_fetch_failure_with_warning(
+        self, mock_log, mock_time, mock_get_session
+    ):
+        """Should use stale cache on fetch failure with warning."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.side_effect = [
+            MockResponse(json_data=self.mock_prompt_response),
+            Exception("Network error"),
+        ]
+        mock_time.return_value = 1000.0
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # First call - populates cache
+        result1 = prompts.get("test-prompt", cache_ttl_seconds=60)
+        self.assertEqual(result1, self.mock_prompt_response["prompt"])
+
+        # Advance time past TTL
+        mock_time.return_value = 1061.0
+
+        # Second call - should use stale cache
+        result2 = prompts.get("test-prompt", cache_ttl_seconds=60)
+        self.assertEqual(result2, self.mock_prompt_response["prompt"])
+
+        # Check warning was logged
+        mock_log.warning.assert_called()
+        warning_call = mock_log.warning.call_args
+        self.assertIn("using stale cache", warning_call[0][0])
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.log")
+    def test_use_fallback_when_no_cache_and_fetch_fails_with_warning(
+        self, mock_log, mock_get_session
+    ):
+        """Should use fallback when no cache and fetch fails with warning."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.side_effect = Exception("Network error")
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        fallback = "Default system prompt."
+        result = prompts.get("test-prompt", fallback=fallback)
+
+        self.assertEqual(result, fallback)
+
+        # Check warning was logged
+        mock_log.warning.assert_called()
+        warning_call = mock_log.warning.call_args
+        self.assertIn("using fallback", warning_call[0][0])
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_throw_when_no_cache_no_fallback_and_fetch_fails(self, mock_get_session):
+        """Should throw when no cache, no fallback, and fetch fails."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.side_effect = Exception("Network error")
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("test-prompt")
+
+        self.assertIn("Network error", str(context.exception))
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_handle_404_response(self, mock_get_session):
+        """Should handle 404 response."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(status_code=404, ok=False)
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("nonexistent-prompt")
+
+        self.assertIn('Prompt "nonexistent-prompt" not found', str(context.exception))
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_handle_403_response(self, mock_get_session):
+        """Should handle 403 response."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(status_code=403, ok=False)
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("restricted-prompt")
+
+        self.assertIn(
+            'Access denied for prompt "restricted-prompt"', str(context.exception)
+        )
+
+    def test_throw_when_no_personal_api_key_configured(self):
+        """Should throw when no personal_api_key is configured."""
+        posthog = self.create_mock_posthog(personal_api_key=None)
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("test-prompt")
+
+        self.assertIn(
+            "personal_api_key is required to fetch prompts", str(context.exception)
+        )
+
+    def test_throw_when_no_project_api_key_configured(self):
+        """Should throw when no project_api_key is configured."""
+        posthog = self.create_mock_posthog(project_api_key=None)
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("test-prompt")
+
+        self.assertIn(
+            "project_api_key is required to fetch prompts", str(context.exception)
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_throw_when_api_returns_invalid_response_format(self, mock_get_session):
+        """Should throw when API returns invalid response format."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data={"invalid": "response"})
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        with self.assertRaises(Exception) as context:
+            prompts.get("test-prompt")
+
+        self.assertIn("Invalid response format", str(context.exception))
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_use_custom_host_from_posthog_options(self, mock_get_session):
+        """Should use custom host from PostHog options."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+
+        posthog = self.create_mock_posthog(host="https://eu.posthog.com")
+        prompts = Prompts(posthog)
+
+        prompts.get("test-prompt")
+
+        call_args = mock_get.call_args
+        self.assertTrue(
+            call_args[0][0].startswith(
+                "https://eu.posthog.com/api/environments/@current/llm_prompts/name/test-prompt/?token=phc_test_key"
+            ),
+            f"Expected URL to start with 'https://eu.posthog.com/api/environments/@current/llm_prompts/name/test-prompt/?token=phc_test_key', got {call_args[0][0]}",
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    def test_use_default_cache_ttl_5_minutes(self, mock_time, mock_get_session):
+        """Should use default cache TTL (5 minutes) when not specified."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+        mock_time.return_value = 1000.0
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # First call
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time by 4 minutes (within default 5-minute TTL)
+        mock_time.return_value = 1000.0 + (4 * 60)
+
+        # Second call - should use cache
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time past 5-minute TTL
+        mock_time.return_value = 1000.0 + (6 * 60)
+
+        # Third call - should refetch
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 2)
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    def test_use_custom_default_cache_ttl_from_constructor(
+        self, mock_time, mock_get_session
+    ):
+        """Should use custom default cache TTL from constructor."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+        mock_time.return_value = 1000.0
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog, default_cache_ttl_seconds=60)
+
+        # First call
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time past custom TTL
+        mock_time.return_value = 1061.0
+
+        # Second call - should refetch
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 2)
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_url_encode_prompt_names_with_special_characters(self, mock_get_session):
+        """Should URL-encode prompt names with special characters."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        prompts.get("prompt with spaces/and/slashes")
+
+        call_args = mock_get.call_args
+        self.assertEqual(
+            call_args[0][0],
+            "https://us.posthog.com/api/environments/@current/llm_prompts/name/prompt%20with%20spaces%2Fand%2Fslashes/?token=phc_test_key",
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_work_with_direct_options_no_posthog_client(self, mock_get_session):
+        """Should work with direct options (no PostHog client)."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+
+        prompts = Prompts(
+            personal_api_key="phx_direct_key", project_api_key="phc_direct_key"
+        )
+
+        result = prompts.get("test-prompt")
+
+        self.assertEqual(result, self.mock_prompt_response["prompt"])
+        call_args = mock_get.call_args
+        self.assertEqual(
+            call_args[0][0],
+            "https://us.posthog.com/api/environments/@current/llm_prompts/name/test-prompt/?token=phc_direct_key",
+        )
+        self.assertEqual(
+            call_args[1]["headers"]["Authorization"], "Bearer phx_direct_key"
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_use_custom_host_from_direct_options(self, mock_get_session):
+        """Should use custom host from direct options."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+
+        prompts = Prompts(
+            personal_api_key="phx_direct_key",
+            project_api_key="phc_direct_key",
+            host="https://eu.posthog.com",
+        )
+
+        prompts.get("test-prompt")
+
+        call_args = mock_get.call_args
+        self.assertEqual(
+            call_args[0][0],
+            "https://eu.posthog.com/api/environments/@current/llm_prompts/name/test-prompt/?token=phc_direct_key",
+        )
+
+    @patch("posthog.ai.prompts._get_session")
+    @patch("posthog.ai.prompts.time.time")
+    def test_use_custom_default_cache_ttl_from_direct_options(
+        self, mock_time, mock_get_session
+    ):
+        """Should use custom default cache TTL from direct options."""
+        mock_get = mock_get_session.return_value.get
+        mock_get.return_value = MockResponse(json_data=self.mock_prompt_response)
+        mock_time.return_value = 1000.0
+
+        prompts = Prompts(
+            personal_api_key="phx_direct_key",
+            project_api_key="phc_direct_key",
+            default_cache_ttl_seconds=60,
+        )
+
+        # First call
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 1)
+
+        # Advance time past custom TTL
+        mock_time.return_value = 1061.0
+
+        # Second call - should refetch
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 2)
+
+
+class TestPromptsCompile(TestPrompts):
+    """Tests for the Prompts.compile() method."""
+
+    def test_replace_a_single_variable(self):
+        """Should replace a single variable."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile("Hello, {{name}}!", {"name": "World"})
+
+        self.assertEqual(result, "Hello, World!")
+
+    def test_replace_multiple_variables(self):
+        """Should replace multiple variables."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile(
+            "Hello, {{name}}! Welcome to {{company}}. Your tier is {{tier}}.",
+            {"name": "John", "company": "Acme Corp", "tier": "premium"},
+        )
+
+        self.assertEqual(
+            result, "Hello, John! Welcome to Acme Corp. Your tier is premium."
+        )
+
+    def test_handle_numbers(self):
+        """Should handle numbers."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile("You have {{count}} items.", {"count": 42})
+
+        self.assertEqual(result, "You have 42 items.")
+
+    def test_handle_booleans(self):
+        """Should handle booleans."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile("Feature enabled: {{enabled}}", {"enabled": True})
+
+        self.assertEqual(result, "Feature enabled: True")
+
+    def test_leave_unmatched_variables_unchanged(self):
+        """Should leave unmatched variables unchanged."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile(
+            "Hello, {{name}}! Your {{unknown}} is ready.", {"name": "World"}
+        )
+
+        self.assertEqual(result, "Hello, World! Your {{unknown}} is ready.")
+
+    def test_handle_prompts_with_no_variables(self):
+        """Should handle prompts with no variables."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile("You are a helpful assistant.", {})
+
+        self.assertEqual(result, "You are a helpful assistant.")
+
+    def test_handle_empty_variables_dict(self):
+        """Should handle empty variables dict."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile("Hello, {{name}}!", {})
+
+        self.assertEqual(result, "Hello, {{name}}!")
+
+    def test_handle_multiple_occurrences_of_same_variable(self):
+        """Should handle multiple occurrences of the same variable."""
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        result = prompts.compile(
+            "Hello, {{name}}! Goodbye, {{name}}!", {"name": "World"}
+        )
+
+        self.assertEqual(result, "Hello, World! Goodbye, World!")
+
+    def test_work_with_direct_options_initialization(self):
+        """Should work with direct options initialization."""
+        prompts = Prompts(
+            personal_api_key="phx_test_key", project_api_key="phc_test_key"
+        )
+
+        result = prompts.compile("Hello, {{name}}!", {"name": "World"})
+
+        self.assertEqual(result, "Hello, World!")
+
+    def test_handle_variables_with_hyphens(self):
+        """Should handle variables with hyphens."""
+        prompts = Prompts(
+            personal_api_key="phx_test_key", project_api_key="phc_test_key"
+        )
+
+        result = prompts.compile("User ID: {{user-id}}", {"user-id": "12345"})
+
+        self.assertEqual(result, "User ID: 12345")
+
+    def test_handle_variables_with_dots(self):
+        """Should handle variables with dots."""
+        prompts = Prompts(
+            personal_api_key="phx_test_key", project_api_key="phc_test_key"
+        )
+
+        result = prompts.compile("Company: {{company.name}}", {"company.name": "Acme"})
+
+        self.assertEqual(result, "Company: Acme")
+
+
+class TestPromptsClearCache(TestPrompts):
+    """Tests for the Prompts.clear_cache() method."""
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_clear_a_specific_prompt_from_cache(self, mock_get_session):
+        """Should clear a specific prompt from cache."""
+        mock_get = mock_get_session.return_value.get
+        other_prompt_response = {**self.mock_prompt_response, "name": "other-prompt"}
+
+        mock_get.side_effect = [
+            MockResponse(json_data=self.mock_prompt_response),
+            MockResponse(json_data=other_prompt_response),
+            MockResponse(json_data=self.mock_prompt_response),
+        ]
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # Populate cache with two prompts
+        prompts.get("test-prompt")
+        prompts.get("other-prompt")
+        self.assertEqual(mock_get.call_count, 2)
+
+        # Clear only test-prompt
+        prompts.clear_cache("test-prompt")
+
+        # test-prompt should be refetched
+        prompts.get("test-prompt")
+        self.assertEqual(mock_get.call_count, 3)
+
+        # other-prompt should still be cached
+        prompts.get("other-prompt")
+        self.assertEqual(mock_get.call_count, 3)
+
+    @patch("posthog.ai.prompts._get_session")
+    def test_clear_all_prompts_from_cache(self, mock_get_session):
+        """Should clear all prompts from cache when no name is provided."""
+        mock_get = mock_get_session.return_value.get
+        other_prompt_response = {**self.mock_prompt_response, "name": "other-prompt"}
+
+        mock_get.side_effect = [
+            MockResponse(json_data=self.mock_prompt_response),
+            MockResponse(json_data=other_prompt_response),
+            MockResponse(json_data=self.mock_prompt_response),
+            MockResponse(json_data=other_prompt_response),
+        ]
+
+        posthog = self.create_mock_posthog()
+        prompts = Prompts(posthog)
+
+        # Populate cache with two prompts
+        prompts.get("test-prompt")
+        prompts.get("other-prompt")
+        self.assertEqual(mock_get.call_count, 2)
+
+        # Clear all cache
+        prompts.clear_cache()
+
+        # Both prompts should be refetched
+        prompts.get("test-prompt")
+        prompts.get("other-prompt")
+        self.assertEqual(mock_get.call_count, 4)
+
+
+if __name__ == "__main__":
+    unittest.main()

posthog/test/ai/test_sanitization.py

@@ -0,0 +1,541 @@
+import os
+import unittest
+
+from posthog.ai.sanitization import (
+    redact_base64_data_url,
+    sanitize_openai,
+    sanitize_openai_response,
+    sanitize_anthropic,
+    sanitize_gemini,
+    sanitize_langchain,
+    is_base64_data_url,
+    is_raw_base64,
+    REDACTED_IMAGE_PLACEHOLDER,
+)
+
+
+class TestSanitization(unittest.TestCase):
+    def setUp(self):
+        self.sample_base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        self.sample_base64_png = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUA..."
+        self.regular_url = "https://example.com/image.jpg"
+        self.raw_base64 = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUl=="
+
+    def test_is_base64_data_url(self):
+        self.assertTrue(is_base64_data_url(self.sample_base64_image))
+        self.assertTrue(is_base64_data_url(self.sample_base64_png))
+        self.assertFalse(is_base64_data_url(self.regular_url))
+        self.assertFalse(is_base64_data_url("regular text"))
+
+    def test_is_raw_base64(self):
+        self.assertTrue(is_raw_base64(self.raw_base64))
+        self.assertFalse(is_raw_base64("short"))
+        self.assertFalse(is_raw_base64(self.regular_url))
+        self.assertFalse(is_raw_base64("/path/to/file"))
+
+    def test_redact_base64_data_url(self):
+        self.assertEqual(
+            redact_base64_data_url(self.sample_base64_image), REDACTED_IMAGE_PLACEHOLDER
+        )
+        self.assertEqual(
+            redact_base64_data_url(self.sample_base64_png), REDACTED_IMAGE_PLACEHOLDER
+        )
+        self.assertEqual(redact_base64_data_url(self.regular_url), self.regular_url)
+        self.assertEqual(redact_base64_data_url(None), None)
+        self.assertEqual(redact_base64_data_url(123), 123)
+
+    def test_sanitize_openai(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "What is in this image?"},
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": self.sample_base64_image,
+                            "detail": "high",
+                        },
+                    },
+                ],
+            }
+        ]
+
+        result = sanitize_openai(input_data)
+
+        self.assertEqual(result[0]["content"][0]["text"], "What is in this image?")
+        self.assertEqual(
+            result[0]["content"][1]["image_url"]["url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+        self.assertEqual(result[0]["content"][1]["image_url"]["detail"], "high")
+
+    def test_sanitize_openai_input_image(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "input_image",
+                        "image_url": self.sample_base64_image,
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_openai(input_data)
+
+        self.assertEqual(
+            result[0]["content"][0]["image_url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_sanitize_openai_preserves_regular_urls(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": self.regular_url},
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_openai(input_data)
+        self.assertEqual(result[0]["content"][0]["image_url"]["url"], self.regular_url)
+
+    def test_sanitize_openai_response(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "input_image",
+                        "image_url": self.sample_base64_image,
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_openai_response(input_data)
+        self.assertEqual(
+            result[0]["content"][0]["image_url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_sanitize_anthropic(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "What is in this image?"},
+                    {
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": "image/jpeg",
+                            "data": "base64data",
+                        },
+                    },
+                ],
+            }
+        ]
+
+        result = sanitize_anthropic(input_data)
+
+        self.assertEqual(result[0]["content"][0]["text"], "What is in this image?")
+        self.assertEqual(
+            result[0]["content"][1]["source"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+        self.assertEqual(result[0]["content"][1]["source"]["type"], "base64")
+        self.assertEqual(result[0]["content"][1]["source"]["media_type"], "image/jpeg")
+
+    def test_sanitize_gemini(self):
+        input_data = [
+            {
+                "parts": [
+                    {"text": "What is in this image?"},
+                    {
+                        "inline_data": {
+                            "mime_type": "image/jpeg",
+                            "data": "base64data",
+                        }
+                    },
+                ]
+            }
+        ]
+
+        result = sanitize_gemini(input_data)
+
+        self.assertEqual(result[0]["parts"][0]["text"], "What is in this image?")
+        self.assertEqual(
+            result[0]["parts"][1]["inline_data"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+        self.assertEqual(
+            result[0]["parts"][1]["inline_data"]["mime_type"], "image/jpeg"
+        )
+
+    def test_sanitize_langchain_openai_style(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": self.sample_base64_image},
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_langchain(input_data)
+        self.assertEqual(
+            result[0]["content"][0]["image_url"]["url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_sanitize_langchain_anthropic_style(self):
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "source": {"data": "base64data"},
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_langchain(input_data)
+        self.assertEqual(
+            result[0]["content"][0]["source"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_sanitize_with_data_url_format(self):
+        # Test that data URLs are properly detected and redacted across providers
+        data_url = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD"
+
+        # OpenAI format
+        openai_data = [
+            {
+                "role": "user",
+                "content": [{"type": "image_url", "image_url": {"url": data_url}}],
+            }
+        ]
+        result = sanitize_openai(openai_data)
+        self.assertEqual(
+            result[0]["content"][0]["image_url"]["url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+        # Anthropic format
+        anthropic_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": "image/jpeg",
+                            "data": data_url,
+                        },
+                    }
+                ],
+            }
+        ]
+        result = sanitize_anthropic(anthropic_data)
+        self.assertEqual(
+            result[0]["content"][0]["source"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+        # LangChain format
+        langchain_data = [
+            {"role": "user", "content": [{"type": "image", "data": data_url}]}
+        ]
+        result = sanitize_langchain(langchain_data)
+        self.assertEqual(result[0]["content"][0]["data"], REDACTED_IMAGE_PLACEHOLDER)
+
+    def test_sanitize_with_raw_base64(self):
+        # Test that raw base64 strings (without data URL prefix) are detected
+        raw_base64 = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUl=="
+
+        # Test with Anthropic format
+        anthropic_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": "image/png",
+                            "data": raw_base64,
+                        },
+                    }
+                ],
+            }
+        ]
+        result = sanitize_anthropic(anthropic_data)
+        self.assertEqual(
+            result[0]["content"][0]["source"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+        # Test with Gemini format
+        gemini_data = [
+            {"parts": [{"inline_data": {"mime_type": "image/png", "data": raw_base64}}]}
+        ]
+        result = sanitize_gemini(gemini_data)
+        self.assertEqual(
+            result[0]["parts"][0]["inline_data"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_sanitize_preserves_regular_content(self):
+        # Ensure non-base64 content is preserved across all providers
+        regular_url = "https://example.com/image.jpg"
+        text_content = "What do you see?"
+
+        # OpenAI
+        openai_data = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": text_content},
+                    {"type": "image_url", "image_url": {"url": regular_url}},
+                ],
+            }
+        ]
+        result = sanitize_openai(openai_data)
+        self.assertEqual(result[0]["content"][0]["text"], text_content)
+        self.assertEqual(result[0]["content"][1]["image_url"]["url"], regular_url)
+
+        # Anthropic
+        anthropic_data = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": text_content},
+                    {"type": "image", "source": {"type": "url", "url": regular_url}},
+                ],
+            }
+        ]
+        result = sanitize_anthropic(anthropic_data)
+        self.assertEqual(result[0]["content"][0]["text"], text_content)
+        # URL-based images should remain unchanged
+        self.assertEqual(result[0]["content"][1]["source"]["url"], regular_url)
+
+    def test_sanitize_handles_non_dict_content(self):
+        input_data = [{"role": "user", "content": "Just text"}]
+
+        result = sanitize_openai(input_data)
+        self.assertEqual(result, input_data)
+
+    def test_sanitize_handles_none_input(self):
+        self.assertIsNone(sanitize_openai(None))
+        self.assertIsNone(sanitize_anthropic(None))
+        self.assertIsNone(sanitize_gemini(None))
+        self.assertIsNone(sanitize_langchain(None))
+
+    def test_sanitize_handles_single_message(self):
+        input_data = {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {"url": self.sample_base64_image},
+                }
+            ],
+        }
+
+        result = sanitize_openai(input_data)
+        self.assertEqual(
+            result["content"][0]["image_url"]["url"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+
+class TestAIMultipartRequest(unittest.TestCase):
+    """Test that _INTERNAL_LLMA_MULTIMODAL environment variable controls sanitization."""
+
+    def tearDown(self):
+        # Clean up environment variable after each test
+        if "_INTERNAL_LLMA_MULTIMODAL" in os.environ:
+            del os.environ["_INTERNAL_LLMA_MULTIMODAL"]
+
+    def test_multimodal_disabled_redacts_images(self):
+        """When _INTERNAL_LLMA_MULTIMODAL is not set, images should be redacted."""
+        if "_INTERNAL_LLMA_MULTIMODAL" in os.environ:
+            del os.environ["_INTERNAL_LLMA_MULTIMODAL"]
+
+        base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        result = redact_base64_data_url(base64_image)
+        self.assertEqual(result, REDACTED_IMAGE_PLACEHOLDER)
+
+    def test_multimodal_enabled_preserves_images(self):
+        """When _INTERNAL_LLMA_MULTIMODAL is true, images should be preserved."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        result = redact_base64_data_url(base64_image)
+        self.assertEqual(result, base64_image)
+
+    def test_multimodal_enabled_with_1(self):
+        """_INTERNAL_LLMA_MULTIMODAL=1 should enable multimodal."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "1"
+
+        base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        result = redact_base64_data_url(base64_image)
+        self.assertEqual(result, base64_image)
+
+    def test_multimodal_enabled_with_yes(self):
+        """_INTERNAL_LLMA_MULTIMODAL=yes should enable multimodal."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "yes"
+
+        base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        result = redact_base64_data_url(base64_image)
+        self.assertEqual(result, base64_image)
+
+    def test_multimodal_false_redacts_images(self):
+        """_INTERNAL_LLMA_MULTIMODAL=false should still redact."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "false"
+
+        base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
+        result = redact_base64_data_url(base64_image)
+        self.assertEqual(result, REDACTED_IMAGE_PLACEHOLDER)
+
+    def test_anthropic_multimodal_enabled(self):
+        """Anthropic images should be preserved when _INTERNAL_LLMA_MULTIMODAL is enabled."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": "image/jpeg",
+                            "data": "base64data",
+                        },
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_anthropic(input_data)
+        self.assertEqual(result[0]["content"][0]["source"]["data"], "base64data")
+
+    def test_gemini_multimodal_enabled(self):
+        """Gemini images should be preserved when _INTERNAL_LLMA_MULTIMODAL is enabled."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        input_data = [
+            {
+                "parts": [
+                    {"inline_data": {"mime_type": "image/jpeg", "data": "base64data"}}
+                ]
+            }
+        ]
+
+        result = sanitize_gemini(input_data)
+        self.assertEqual(result[0]["parts"][0]["inline_data"]["data"], "base64data")
+
+    def test_langchain_anthropic_style_multimodal_enabled(self):
+        """LangChain Anthropic-style images should be preserved when _INTERNAL_LLMA_MULTIMODAL is enabled."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        input_data = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "source": {"data": "base64data"},
+                    }
+                ],
+            }
+        ]
+
+        result = sanitize_langchain(input_data)
+        self.assertEqual(result[0]["content"][0]["source"]["data"], "base64data")
+
+    def test_openai_audio_redacted_by_default(self):
+        """OpenAI audio should be redacted when _INTERNAL_LLMA_MULTIMODAL is not set."""
+        if "_INTERNAL_LLMA_MULTIMODAL" in os.environ:
+            del os.environ["_INTERNAL_LLMA_MULTIMODAL"]
+
+        input_data = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "audio", "data": "base64audiodata", "id": "audio_123"}
+                ],
+            }
+        ]
+
+        result = sanitize_openai(input_data)
+        self.assertEqual(result[0]["content"][0]["data"], REDACTED_IMAGE_PLACEHOLDER)
+        self.assertEqual(result[0]["content"][0]["id"], "audio_123")
+
+    def test_openai_audio_preserved_with_flag(self):
+        """OpenAI audio should be preserved when _INTERNAL_LLMA_MULTIMODAL is enabled."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        input_data = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "audio", "data": "base64audiodata", "id": "audio_123"}
+                ],
+            }
+        ]
+
+        result = sanitize_openai(input_data)
+        self.assertEqual(result[0]["content"][0]["data"], "base64audiodata")
+
+    def test_gemini_audio_redacted_by_default(self):
+        """Gemini audio should be redacted when _INTERNAL_LLMA_MULTIMODAL is not set."""
+        if "_INTERNAL_LLMA_MULTIMODAL" in os.environ:
+            del os.environ["_INTERNAL_LLMA_MULTIMODAL"]
+
+        input_data = [
+            {
+                "parts": [
+                    {
+                        "inline_data": {
+                            "mime_type": "audio/L16;codec=pcm;rate=24000",
+                            "data": "base64audiodata",
+                        }
+                    }
+                ]
+            }
+        ]
+
+        result = sanitize_gemini(input_data)
+        self.assertEqual(
+            result[0]["parts"][0]["inline_data"]["data"], REDACTED_IMAGE_PLACEHOLDER
+        )
+
+    def test_gemini_audio_preserved_with_flag(self):
+        """Gemini audio should be preserved when _INTERNAL_LLMA_MULTIMODAL is enabled."""
+        os.environ["_INTERNAL_LLMA_MULTIMODAL"] = "true"
+
+        input_data = [
+            {
+                "parts": [
+                    {
+                        "inline_data": {
+                            "mime_type": "audio/L16;codec=pcm;rate=24000",
+                            "data": "base64audiodata",
+                        }
+                    }
+                ]
+            }
+        ]
+
+        result = sanitize_gemini(input_data)
+        self.assertEqual(
+            result[0]["parts"][0]["inline_data"]["data"], "base64audiodata"
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()

posthog/test/ai/test_system_prompts.py

@@ -0,0 +1,363 @@
+"""
+Tests for system prompt capture across all LLM providers.
+
+This test suite ensures that system prompts are correctly captured in analytics
+regardless of how they're passed to the providers:
+- As first message in messages/contents array (standard format)
+- As separate system parameter (Anthropic, OpenAI)
+- As instructions parameter (OpenAI Responses API)
+- As system_instruction parameter (Gemini)
+"""
+
+import time
+import unittest
+from unittest.mock import MagicMock, patch
+
+from posthog.client import Client
+from posthog.test.test_utils import FAKE_TEST_API_KEY
+
+
+class TestSystemPromptCapture(unittest.TestCase):
+    """Test system prompt capture for all providers."""
+
+    def setUp(self):
+        super().setUp()
+        self.test_system_prompt = "You are a helpful AI assistant."
+        self.test_user_message = "Hello, how are you?"
+        self.test_response = "I'm doing well, thank you!"
+
+        # Create mock PostHog client
+        self.client = Client(FAKE_TEST_API_KEY)
+        self.client._enqueue = MagicMock()
+        self.client.privacy_mode = False
+
+    def _assert_system_prompt_captured(self, captured_input):
+        """Helper to assert system prompt is correctly captured."""
+        self.assertEqual(
+            len(captured_input), 2, "Should have 2 messages (system + user)"
+        )
+        self.assertEqual(
+            captured_input[0]["role"], "system", "First message should be system"
+        )
+        self.assertEqual(
+            captured_input[0]["content"],
+            self.test_system_prompt,
+            "System content should match",
+        )
+        self.assertEqual(
+            captured_input[1]["role"], "user", "Second message should be user"
+        )
+        self.assertEqual(
+            captured_input[1]["content"],
+            self.test_user_message,
+            "User content should match",
+        )
+
+    # OpenAI Tests
+    def test_openai_messages_array_system_prompt(self):
+        """Test OpenAI with system prompt in messages array."""
+        try:
+            from openai.types.chat import ChatCompletion, ChatCompletionMessage
+            from openai.types.chat.chat_completion import Choice
+            from openai.types.completion_usage import CompletionUsage
+
+            from posthog.ai.openai import OpenAI
+        except ImportError:
+            self.skipTest("OpenAI package not available")
+
+        mock_response = ChatCompletion(
+            id="test",
+            model="gpt-4",
+            object="chat.completion",
+            created=int(time.time()),
+            choices=[
+                Choice(
+                    finish_reason="stop",
+                    index=0,
+                    message=ChatCompletionMessage(
+                        content=self.test_response, role="assistant"
+                    ),
+                )
+            ],
+            usage=CompletionUsage(
+                completion_tokens=10, prompt_tokens=20, total_tokens=30
+            ),
+        )
+
+        with patch(
+            "openai.resources.chat.completions.Completions.create",
+            return_value=mock_response,
+        ):
+            client = OpenAI(posthog_client=self.client, api_key="test")
+
+            messages = [
+                {"role": "system", "content": self.test_system_prompt},
+                {"role": "user", "content": self.test_user_message},
+            ]
+
+            client.chat.completions.create(
+                model="gpt-4", messages=messages, posthog_distinct_id="test-user"
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    def test_openai_separate_system_parameter(self):
+        """Test OpenAI with system prompt as separate parameter."""
+        try:
+            from openai.types.chat import ChatCompletion, ChatCompletionMessage
+            from openai.types.chat.chat_completion import Choice
+            from openai.types.completion_usage import CompletionUsage
+
+            from posthog.ai.openai import OpenAI
+        except ImportError:
+            self.skipTest("OpenAI package not available")
+
+        mock_response = ChatCompletion(
+            id="test",
+            model="gpt-4",
+            object="chat.completion",
+            created=int(time.time()),
+            choices=[
+                Choice(
+                    finish_reason="stop",
+                    index=0,
+                    message=ChatCompletionMessage(
+                        content=self.test_response, role="assistant"
+                    ),
+                )
+            ],
+            usage=CompletionUsage(
+                completion_tokens=10, prompt_tokens=20, total_tokens=30
+            ),
+        )
+
+        with patch(
+            "openai.resources.chat.completions.Completions.create",
+            return_value=mock_response,
+        ):
+            client = OpenAI(posthog_client=self.client, api_key="test")
+
+            messages = [{"role": "user", "content": self.test_user_message}]
+
+            client.chat.completions.create(
+                model="gpt-4",
+                messages=messages,
+                system=self.test_system_prompt,
+                posthog_distinct_id="test-user",
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    def test_openai_streaming_system_parameter(self):
+        """Test OpenAI streaming with system parameter."""
+        try:
+            from openai.types.chat.chat_completion_chunk import (
+                ChatCompletionChunk,
+                ChoiceDelta,
+            )
+            from openai.types.chat.chat_completion_chunk import Choice as ChoiceChunk
+            from openai.types.completion_usage import CompletionUsage
+
+            from posthog.ai.openai import OpenAI
+        except ImportError:
+            self.skipTest("OpenAI package not available")
+
+        chunk1 = ChatCompletionChunk(
+            id="test",
+            model="gpt-4",
+            object="chat.completion.chunk",
+            created=int(time.time()),
+            choices=[
+                ChoiceChunk(
+                    finish_reason=None,
+                    index=0,
+                    delta=ChoiceDelta(content="Hello", role="assistant"),
+                )
+            ],
+        )
+
+        chunk2 = ChatCompletionChunk(
+            id="test",
+            model="gpt-4",
+            object="chat.completion.chunk",
+            created=int(time.time()),
+            choices=[
+                ChoiceChunk(
+                    finish_reason="stop",
+                    index=0,
+                    delta=ChoiceDelta(content=" there!", role=None),
+                )
+            ],
+            usage=CompletionUsage(
+                completion_tokens=10, prompt_tokens=20, total_tokens=30
+            ),
+        )
+
+        with patch(
+            "openai.resources.chat.completions.Completions.create",
+            return_value=[chunk1, chunk2],
+        ):
+            client = OpenAI(posthog_client=self.client, api_key="test")
+
+            messages = [{"role": "user", "content": self.test_user_message}]
+
+            response_generator = client.chat.completions.create(
+                model="gpt-4",
+                messages=messages,
+                system=self.test_system_prompt,
+                stream=True,
+                posthog_distinct_id="test-user",
+            )
+
+            list(response_generator)  # Consume generator
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    # Anthropic Tests
+    def test_anthropic_messages_array_system_prompt(self):
+        """Test Anthropic with system prompt in messages array."""
+        try:
+            from posthog.ai.anthropic import Anthropic
+        except ImportError:
+            self.skipTest("Anthropic package not available")
+
+        with patch("anthropic.resources.messages.Messages.create") as mock_create:
+            mock_response = MagicMock()
+            mock_response.usage.input_tokens = 20
+            mock_response.usage.output_tokens = 10
+            mock_response.usage.cache_read_input_tokens = None
+            mock_response.usage.cache_creation_input_tokens = None
+            mock_create.return_value = mock_response
+
+            client = Anthropic(posthog_client=self.client, api_key="test")
+
+            messages = [
+                {"role": "system", "content": self.test_system_prompt},
+                {"role": "user", "content": self.test_user_message},
+            ]
+
+            client.messages.create(
+                model="claude-3-5-sonnet-20241022",
+                messages=messages,
+                posthog_distinct_id="test-user",
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    def test_anthropic_separate_system_parameter(self):
+        """Test Anthropic with system prompt as separate parameter."""
+        try:
+            from posthog.ai.anthropic import Anthropic
+        except ImportError:
+            self.skipTest("Anthropic package not available")
+
+        with patch("anthropic.resources.messages.Messages.create") as mock_create:
+            mock_response = MagicMock()
+            mock_response.usage.input_tokens = 20
+            mock_response.usage.output_tokens = 10
+            mock_response.usage.cache_read_input_tokens = None
+            mock_response.usage.cache_creation_input_tokens = None
+            mock_create.return_value = mock_response
+
+            client = Anthropic(posthog_client=self.client, api_key="test")
+
+            messages = [{"role": "user", "content": self.test_user_message}]
+
+            client.messages.create(
+                model="claude-3-5-sonnet-20241022",
+                messages=messages,
+                system=self.test_system_prompt,
+                posthog_distinct_id="test-user",
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    # Gemini Tests
+    def test_gemini_contents_array_system_prompt(self):
+        """Test Gemini with system prompt in contents array."""
+        try:
+            from posthog.ai.gemini import Client
+        except ImportError:
+            self.skipTest("Gemini package not available")
+
+        with patch("google.genai.Client") as mock_genai_class:
+            mock_response = MagicMock()
+            mock_response.candidates = [MagicMock()]
+            mock_response.candidates[0].content.parts = [MagicMock()]
+            mock_response.candidates[0].content.parts[0].text = self.test_response
+            mock_response.usage_metadata.prompt_token_count = 20
+            mock_response.usage_metadata.candidates_token_count = 10
+            mock_response.usage_metadata.cached_content_token_count = None
+            mock_response.usage_metadata.thoughts_token_count = None
+
+            mock_client_instance = MagicMock()
+            mock_models_instance = MagicMock()
+            mock_models_instance.generate_content.return_value = mock_response
+            mock_client_instance.models = mock_models_instance
+            mock_genai_class.return_value = mock_client_instance
+
+            client = Client(posthog_client=self.client, api_key="test")
+
+            contents = [
+                {"role": "system", "content": self.test_system_prompt},
+                {"role": "user", "content": self.test_user_message},
+            ]
+
+            client.models.generate_content(
+                model="gemini-2.0-flash",
+                contents=contents,
+                posthog_distinct_id="test-user",
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])
+
+    def test_gemini_system_instruction_parameter(self):
+        """Test Gemini with system_instruction in config parameter."""
+        try:
+            from posthog.ai.gemini import Client
+        except ImportError:
+            self.skipTest("Gemini package not available")
+
+        with patch("google.genai.Client") as mock_genai_class:
+            mock_response = MagicMock()
+            mock_response.candidates = [MagicMock()]
+            mock_response.candidates[0].content.parts = [MagicMock()]
+            mock_response.candidates[0].content.parts[0].text = self.test_response
+            mock_response.usage_metadata.prompt_token_count = 20
+            mock_response.usage_metadata.candidates_token_count = 10
+            mock_response.usage_metadata.cached_content_token_count = None
+            mock_response.usage_metadata.thoughts_token_count = None
+
+            mock_client_instance = MagicMock()
+            mock_models_instance = MagicMock()
+            mock_models_instance.generate_content.return_value = mock_response
+            mock_client_instance.models = mock_models_instance
+            mock_genai_class.return_value = mock_client_instance
+
+            client = Client(posthog_client=self.client, api_key="test")
+
+            contents = [{"role": "user", "content": self.test_user_message}]
+            config = {"system_instruction": self.test_system_prompt}
+
+            client.models.generate_content(
+                model="gemini-2.0-flash",
+                contents=contents,
+                config=config,
+                posthog_distinct_id="test-user",
+            )
+
+            self.assertEqual(len(self.client._enqueue.call_args_list), 1)
+            properties = self.client._enqueue.call_args_list[0][0][0]["properties"]
+            self._assert_system_prompt_captured(properties["$ai_input"])

posthog/test/ai/test_tokens_source.py

@@ -0,0 +1,62 @@
+from parameterized import parameterized
+
+from posthog.ai.utils import _get_tokens_source
+
+
+@parameterized.expand(
+    [
+        ("no_posthog_properties", {"$ai_input_tokens": 100}, None, "sdk"),
+        ("empty_posthog_properties", {"$ai_input_tokens": 100}, {}, "sdk"),
+        (
+            "unrelated_posthog_properties",
+            {"$ai_input_tokens": 100},
+            {"foo": "bar"},
+            "sdk",
+        ),
+        (
+            "override_input_tokens",
+            {"$ai_input_tokens": 100},
+            {"$ai_input_tokens": 999},
+            "passthrough",
+        ),
+        (
+            "override_output_tokens",
+            {"$ai_output_tokens": 50},
+            {"$ai_output_tokens": 999},
+            "passthrough",
+        ),
+        (
+            "override_total_tokens",
+            {"$ai_input_tokens": 100},
+            {"$ai_total_tokens": 999},
+            "passthrough",
+        ),
+        (
+            "override_cache_read",
+            {"$ai_input_tokens": 100},
+            {"$ai_cache_read_input_tokens": 500},
+            "passthrough",
+        ),
+        (
+            "override_cache_creation",
+            {"$ai_input_tokens": 100},
+            {"$ai_cache_creation_input_tokens": 200},
+            "passthrough",
+        ),
+        (
+            "override_reasoning_tokens",
+            {"$ai_input_tokens": 100},
+            {"$ai_reasoning_tokens": 300},
+            "passthrough",
+        ),
+        (
+            "mixed_override_and_custom",
+            {"$ai_input_tokens": 100},
+            {"$ai_input_tokens": 999, "custom_key": "value"},
+            "passthrough",
+        ),
+    ]
+)
+def test_get_tokens_source(name, sdk_tags, posthog_properties, expected):
+    result = _get_tokens_source(sdk_tags, posthog_properties)
+    assert result == expected

posthog/test/exception_integrations/__init__.py

@@ -1,3 +0,0 @@
-import pytest
-
-pytest.importorskip("django")

posthog/test/exception_integrations/test_django.py

@@ -1,121 +0,0 @@
-from posthog.exception_integrations.django import DjangoRequestExtractor
-from django.test import RequestFactory
-from django.conf import settings
-from django.core.management import call_command
-import django
-
-DEFAULT_USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
-
-# setup a test app
-if not settings.configured:
-    settings.configure(
-        SECRET_KEY="test",
-        DEFAULT_CHARSET="utf-8",
-        INSTALLED_APPS=[
-            "django.contrib.auth",
-            "django.contrib.contenttypes",
-        ],
-        DATABASES={
-            "default": {
-                "ENGINE": "django.db.backends.sqlite3",
-                "NAME": ":memory:",
-            }
-        },
-    )
-    django.setup()
-
-    call_command("migrate", verbosity=0, interactive=False)
-
-
-def mock_request_factory(override_headers):
-    factory = RequestFactory(
-        headers={
-            "User-Agent": DEFAULT_USER_AGENT,
-            "Referrer": "http://example.com",
-            "X-Forwarded-For": "193.4.5.12",
-            **(override_headers or {}),
-        }
-    )
-
-    request = factory.get("/api/endpoint")
-    return request
-
-
-def test_request_extractor_with_no_trace():
-    request = mock_request_factory(None)
-    extractor = DjangoRequestExtractor(request)
-    assert extractor.extract_person_data() == {
-        "ip": "193.4.5.12",
-        "user_agent": DEFAULT_USER_AGENT,
-        "traceparent": None,
-        "distinct_id": None,
-        "$request_path": "/api/endpoint",
-    }
-
-
-def test_request_extractor_with_trace():
-    request = mock_request_factory(
-        {"traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01"}
-    )
-
-    extractor = DjangoRequestExtractor(request)
-    assert extractor.extract_person_data() == {
-        "ip": "193.4.5.12",
-        "user_agent": DEFAULT_USER_AGENT,
-        "traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
-        "distinct_id": None,
-        "$request_path": "/api/endpoint",
-    }
-
-
-def test_request_extractor_with_tracestate():
-    request = mock_request_factory(
-        {
-            "traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
-            "tracestate": "posthog-distinct-id=1234",
-        }
-    )
-    extractor = DjangoRequestExtractor(request)
-    assert extractor.extract_person_data() == {
-        "ip": "193.4.5.12",
-        "user_agent": DEFAULT_USER_AGENT,
-        "traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
-        "distinct_id": "1234",
-        "$request_path": "/api/endpoint",
-    }
-
-
-def test_request_extractor_with_complicated_tracestate():
-    request = mock_request_factory(
-        {"tracestate": "posthog-distinct-id=alohaMountainsXUYZ,rojo=00f067aa0ba902b7"}
-    )
-    extractor = DjangoRequestExtractor(request)
-    assert extractor.extract_person_data() == {
-        "ip": "193.4.5.12",
-        "user_agent": DEFAULT_USER_AGENT,
-        "traceparent": None,
-        "distinct_id": "alohaMountainsXUYZ",
-        "$request_path": "/api/endpoint",
-    }
-
-
-def test_request_extractor_with_request_user():
-    from django.contrib.auth.models import User
-
-    user = User.objects.create_user(
-        username="test", email="test@posthog.com", password="top_secret"
-    )
-
-    request = mock_request_factory(None)
-    request.user = user
-
-    extractor = DjangoRequestExtractor(request)
-    assert extractor.extract_person_data() == {
-        "ip": "193.4.5.12",
-        "user_agent": DEFAULT_USER_AGENT,
-        "traceparent": None,
-        "distinct_id": None,
-        "$request_path": "/api/endpoint",
-        "email": "test@posthog.com",
-        "$user_id": "1",
-    }

posthog/test/integrations/test_middleware.py

@@ -1,6 +1,24 @@
-from posthog.scopes import new_context, get_context_session_id, get_context_distinct_id
+from posthog.contexts import (
+    new_context,
+    get_context_session_id,
+    get_context_distinct_id,
+)
 import unittest
-from unittest.mock import Mock
+from unittest.mock import Mock, patch
+import asyncio
+
+# Configure Django settings before importing middleware
+import django
+from django.conf import settings
+
+if not settings.configured:
+    settings.configure(
+        DEBUG=True,
+        SECRET_KEY="test-secret-key",
+        INSTALLED_APPS=[],
+        MIDDLEWARE=[],
+    )
+    django.setup()
 
 from posthog.integrations.django import PosthogContextMiddleware
 
@@ -34,14 +52,33 @@ class TestPosthogContextMiddleware(unittest.TestCase):
         request_filter=None,
         tag_map=None,
         capture_exceptions=True,
+        get_response=None,
     ):
-        """Helper to create middleware instance without calling __init__"""
-        middleware = PosthogContextMiddleware.__new__(PosthogContextMiddleware)
-        middleware.get_response = Mock()
-        middleware.extra_tags = extra_tags
-        middleware.request_filter = request_filter
-        middleware.tag_map = tag_map
-        middleware.capture_exceptions = capture_exceptions
+        """Helper to create middleware instance with mock Django settings"""
+        if get_response is None:
+            get_response = Mock()
+
+        with patch("django.conf.settings") as mock_settings:
+            # Configure mock settings
+            mock_settings.POSTHOG_MW_EXTRA_TAGS = extra_tags
+            mock_settings.POSTHOG_MW_REQUEST_FILTER = request_filter
+            mock_settings.POSTHOG_MW_TAG_MAP = tag_map
+            mock_settings.POSTHOG_MW_CAPTURE_EXCEPTIONS = capture_exceptions
+            mock_settings.POSTHOG_MW_CLIENT = None
+
+            # Make hasattr work correctly
+            def mock_hasattr(obj, name):
+                return name in [
+                    "POSTHOG_MW_EXTRA_TAGS",
+                    "POSTHOG_MW_REQUEST_FILTER",
+                    "POSTHOG_MW_TAG_MAP",
+                    "POSTHOG_MW_CAPTURE_EXCEPTIONS",
+                    "POSTHOG_MW_CLIENT",
+                ]
+
+            with patch("builtins.hasattr", side_effect=mock_hasattr):
+                middleware = PosthogContextMiddleware(get_response)
+
         return middleware
 
     def test_extract_tags_basic(self):
@@ -164,6 +201,573 @@ class TestPosthogContextMiddleware(unittest.TestCase):
 
         self.assertEqual(tags["$request_method"], "PATCH")
 
+    def test_process_exception_called_during_view_exception(self):
+        """
+        Unit test verifying process_exception captures exceptions per Django's contract.
+
+        Since this is a library test (no Django runtime), we simulate how Django
+        would invoke our middleware in production:
+        1. Middleware.__call__ creates context with request tags
+        2. View raises exception inside get_response
+        3. Django's BaseHandler catches it, calls process_exception, returns error response
+        4. Exception never propagates to middleware's context manager
+
+        We manually call process_exception to simulate Django's behavior - this is
+        the only way to test the hook without a full Django integration test.
+        """
+        mock_client = Mock()
+        view_exception = ValueError("View raised this error")
+        error_response = Mock(status_code=500)
+
+        def mock_get_response(request):
+            # Simulate Django's exception handling: catches view exception,
+            # calls process_exception hook if it exists, returns error response
+            if hasattr(middleware, "process_exception"):
+                middleware.process_exception(request, view_exception)
+            return error_response
+
+        middleware = self.create_middleware(get_response=mock_get_response)
+        middleware.client = mock_client
+
+        request = MockRequest(
+            headers={"X-POSTHOG-DISTINCT-ID": "test-user"},
+            method="POST",
+            path="/api/endpoint",
+        )
+        response = middleware(request)
+
+        self.assertEqual(response.status_code, 500)
+        mock_client.capture_exception.assert_called_once_with(view_exception)
+
+    def test_process_exception_respects_capture_exceptions_false(self):
+        """Verify process_exception respects capture_exceptions=False setting"""
+        mock_client = Mock()
+        view_exception = ValueError("Should not be captured")
+
+        def mock_get_response(request):
+            if hasattr(middleware, "process_exception"):
+                middleware.process_exception(request, view_exception)
+            return Mock(status_code=500)
+
+        middleware = self.create_middleware(
+            capture_exceptions=False, get_response=mock_get_response
+        )
+        middleware.client = mock_client
+
+        request = MockRequest()
+        middleware(request)
+
+        mock_client.capture_exception.assert_not_called()
+
+    def test_process_exception_respects_request_filter(self):
+        """Verify process_exception respects request_filter setting"""
+        mock_client = Mock()
+        view_exception = ValueError("Should be filtered")
+
+        def mock_get_response(request):
+            if hasattr(middleware, "process_exception"):
+                middleware.process_exception(request, view_exception)
+            return Mock(status_code=500)
+
+        middleware = self.create_middleware(
+            request_filter=lambda req: False,
+            capture_exceptions=True,
+            get_response=mock_get_response,
+        )
+        middleware.client = mock_client
+
+        request = MockRequest()
+        middleware(request)
+
+        mock_client.capture_exception.assert_not_called()
+
+
+class TestPosthogContextMiddlewareSync(unittest.TestCase):
+    """Test synchronous middleware behavior"""
+
+    def test_sync_middleware_call(self):
+        """Test that sync middleware correctly processes requests"""
+        mock_response = Mock()
+        get_response = Mock(return_value=mock_response)
+
+        # Create middleware with sync get_response
+        middleware = PosthogContextMiddleware(get_response)
+
+        # Verify sync mode detected
+        self.assertFalse(middleware._is_coroutine)
+
+        request = MockRequest(
+            headers={"X-POSTHOG-SESSION-ID": "test-session"},
+            method="GET",
+            path="/test",
+        )
+
+        with new_context():
+            response = middleware(request)
+
+            # Verify response returned
+            self.assertEqual(response, mock_response)
+            get_response.assert_called_once_with(request)
+
+    def test_sync_middleware_with_filter(self):
+        """Test sync middleware respects request filter"""
+        mock_response = Mock()
+        get_response = Mock(return_value=mock_response)
+
+        # Create middleware with request filter that filters all requests
+        def request_filter(req):
+            return False
+
+        middleware = PosthogContextMiddleware.__new__(PosthogContextMiddleware)
+        middleware.get_response = get_response
+        middleware._is_coroutine = False
+        middleware.request_filter = request_filter
+        middleware.capture_exceptions = True
+        middleware.client = None
+
+        request = MockRequest()
+
+        # Should skip context creation and return response directly
+        response = middleware(request)
+        self.assertEqual(response, mock_response)
+        get_response.assert_called_once_with(request)
+
+    def test_view_exceptions_only_captured_via_process_exception(self):
+        """
+        Demonstrates that process_exception is required to capture view exceptions.
+
+        In production Django, view exceptions don't propagate to middleware's context
+        manager because Django's BaseHandler catches them first and converts them to
+        error responses. Django provides the exception via process_exception hook instead.
+
+        This unit test proves:
+        1. Context manager in __call__ never sees view exceptions (Django intercepts)
+        2. Only process_exception can capture them
+        3. Without process_exception, exceptions are silently lost (v6.7.5 regression)
+
+        We manually call process_exception to verify the hook works - in production,
+        Django's BaseHandler would call it when a view raises.
+        """
+        mock_client = Mock()
+        get_response = Mock(return_value=Mock(status_code=500))
+
+        middleware = PosthogContextMiddleware(get_response)
+        middleware.client = mock_client
+
+        def get_response_simulating_django(request):
+            # Simulates Django behavior: view exception converted to error response,
+            # never propagates to middleware's context manager
+            return Mock(status_code=500)
+
+        middleware._sync_get_response = get_response_simulating_django
+
+        request = MockRequest()
+
+        response = middleware(request)
+        self.assertEqual(response.status_code, 500)
+
+        # Context manager didn't capture anything - exception was intercepted by Django
+        mock_client.capture_exception.assert_not_called()
+
+        # Verify process_exception hook exists and captures exceptions when called
+        if hasattr(middleware, "process_exception"):
+            exception = ValueError("View error")
+            middleware.process_exception(request, exception)
+            mock_client.capture_exception.assert_called_once_with(exception)
+        else:
+            self.fail(
+                "process_exception missing - view exceptions will not be captured!"
+            )
+
+
+class TestPosthogContextMiddlewareAsync(unittest.TestCase):
+    """Test asynchronous middleware behavior"""
+
+    def test_async_middleware_detection(self):
+        """Test that async get_response is correctly detected"""
+
+        async def async_get_response(request):
+            return Mock()
+
+        middleware = PosthogContextMiddleware(async_get_response)
+
+        # Verify async mode detected
+        self.assertTrue(middleware._is_coroutine)
+
+    def test_async_middleware_call(self):
+        """Test that async middleware correctly processes requests"""
+
+        async def run_test():
+            mock_response = Mock()
+
+            async def async_get_response(request):
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "async-session"},
+                method="POST",
+                path="/async-test",
+            )
+
+            with new_context():
+                # Call should return the coroutine from __acall__
+                result = middleware(request)
+
+                # Verify it's a coroutine
+                self.assertTrue(asyncio.iscoroutine(result))
+
+                # Await the result
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_with_filter(self):
+        """Test async middleware respects request filter"""
+
+        async def run_test():
+            mock_response = Mock()
+
+            async def async_get_response(request):
+                return mock_response
+
+            # Properly initialize middleware
+            middleware = PosthogContextMiddleware(async_get_response)
+            # Override request filter after initialization
+            middleware.request_filter = lambda req: False
+
+            request = MockRequest()
+
+            # Should skip context creation and return response directly
+            result = middleware(request)
+            response = await result
+            self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_context_propagation(self):
+        """Test that async middleware properly propagates context"""
+
+        async def run_test():
+            mock_response = Mock()
+
+            async def async_get_response(request):
+                # Verify context is available during async processing
+                session_id = get_context_session_id()
+                self.assertEqual(session_id, "async-session-123")
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "async-session-123"},
+                method="GET",
+            )
+
+            with new_context():
+                result = middleware(request)
+                await result
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_exception_capture(self):
+        """Test that async middleware captures exceptions during request processing"""
+
+        async def run_test():
+            mock_client = Mock()
+
+            # Make async_get_response raise an exception
+            async def raise_exception(request):
+                raise ValueError("Async test exception")
+
+            # Properly initialize middleware
+            middleware = PosthogContextMiddleware(raise_exception)
+            middleware.client = mock_client  # Override with mock client
+
+            request = MockRequest()
+
+            # Should capture exception and re-raise
+            with self.assertRaises(ValueError):
+                result = middleware(request)
+                await result
+
+            # Verify exception was captured by middleware
+            mock_client.capture_exception.assert_called_once()
+            captured_exception = mock_client.capture_exception.call_args[0][0]
+            self.assertIsInstance(captured_exception, ValueError)
+            self.assertEqual(str(captured_exception), "Async test exception")
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_with_authenticated_user(self):
+        """
+        Test that async middleware correctly extracts user info in async context.
+
+        Django's request.user is a SimpleLazyObject that defers DB access.
+        In async context, accessing it directly raises SynchronousOnlyOperation.
+        The middleware should use request.auser() instead.
+
+        This tests the fix for issue #355.
+        """
+
+        async def run_test():
+            mock_response = Mock()
+            mock_user = Mock()
+            mock_user.is_authenticated = True
+            mock_user.pk = 123
+            mock_user.email = "test@example.com"
+
+            async def async_get_response(request):
+                # Verify user info was extracted and set as distinct_id
+                distinct_id = get_context_distinct_id()
+                self.assertEqual(distinct_id, "123")
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.client = Mock()
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "test-session"}, method="GET"
+            )
+
+            # Mock auser() to return authenticated user
+            async def mock_auser():
+                return mock_user
+
+            request.auser = mock_auser
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_with_unauthenticated_user(self):
+        """
+        Test that async middleware handles unauthenticated users correctly.
+        """
+
+        async def run_test():
+            mock_response = Mock()
+            mock_user = Mock()
+            mock_user.is_authenticated = False  # Not authenticated
+
+            async def async_get_response(request):
+                # Verify no distinct_id was set (no user)
+                distinct_id = get_context_distinct_id()
+                self.assertIsNone(distinct_id)
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.client = Mock()
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "test-session"}, method="GET"
+            )
+
+            async def mock_auser():
+                return mock_user
+
+            request.auser = mock_auser
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_without_user_attribute(self):
+        """
+        Test that async middleware handles requests without user attribute (no auth middleware).
+        """
+
+        async def run_test():
+            mock_response = Mock()
+
+            async def async_get_response(request):
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.client = Mock()
+
+            # Request without auser method (no auth middleware)
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "test-session"}, method="GET"
+            )
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_with_extra_tags(self):
+        """
+        Test that async middleware works with extra_tags callback.
+        """
+
+        async def run_test():
+            mock_response = Mock()
+
+            def extra_tags_callback(request):
+                # Simple sync callback - should work
+                return {"custom_tag": "custom_value"}
+
+            async def async_get_response(request):
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.extra_tags = extra_tags_callback
+            middleware.client = Mock()
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "test-session"}, method="GET"
+            )
+
+            # Mock auser for no user
+            async def mock_auser():
+                return None
+
+            request.auser = mock_auser
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_with_tag_map(self):
+        """
+        Test that async middleware works with tag_map callback.
+        """
+
+        async def run_test():
+            mock_response = Mock()
+
+            def tag_map_callback(tags):
+                # Simple sync callback - should work
+                tags["mapped"] = "yes"
+                return tags
+
+            async def async_get_response(request):
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.tag_map = tag_map_callback
+            middleware.client = Mock()
+
+            request = MockRequest(
+                headers={"X-POSTHOG-SESSION-ID": "test-session"}, method="GET"
+            )
+
+            # Mock auser for no user
+            async def mock_auser():
+                return None
+
+            request.auser = mock_auser
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+    def test_async_middleware_user_extraction_with_all_headers(self):
+        """
+        Test async middleware extracts all request info correctly.
+        """
+
+        async def run_test():
+            mock_response = Mock()
+            mock_user = Mock()
+            mock_user.is_authenticated = True
+            mock_user.pk = 456
+            mock_user.email = "async@test.com"
+
+            async def async_get_response(request):
+                # Verify all context was set correctly
+                distinct_id = get_context_distinct_id()
+                session_id = get_context_session_id()
+                self.assertEqual(distinct_id, "456")
+                self.assertEqual(session_id, "async-sess-123")
+                return mock_response
+
+            middleware = PosthogContextMiddleware(async_get_response)
+            middleware.client = Mock()
+
+            request = MockRequest(
+                headers={
+                    "X-POSTHOG-SESSION-ID": "async-sess-123",
+                    "X-Forwarded-For": "192.168.1.1",
+                    "User-Agent": "TestAgent/1.0",
+                },
+                method="POST",
+                path="/api/test",
+            )
+
+            async def mock_auser():
+                return mock_user
+
+            request.auser = mock_auser
+
+            with new_context():
+                result = middleware(request)
+                response = await result
+                self.assertEqual(response, mock_response)
+
+        asyncio.run(run_test())
+
+
+class TestPosthogContextMiddlewareHybrid(unittest.TestCase):
+    """Test hybrid middleware behavior with mixed sync/async chains"""
+
+    def test_hybrid_flags_set(self):
+        """Test that both capability flags are set"""
+        self.assertTrue(PosthogContextMiddleware.sync_capable)
+        self.assertTrue(PosthogContextMiddleware.async_capable)
+
+    def test_sync_to_async_routing(self):
+        """Test that __call__ routes to __acall__ when async"""
+
+        async def run_test():
+            async def async_get_response(request):
+                return Mock()
+
+            middleware = PosthogContextMiddleware(async_get_response)
+
+            # Verify routing happens
+            request = MockRequest()
+            result = middleware(request)
+
+            # Should be a coroutine from __acall__
+            self.assertTrue(asyncio.iscoroutine(result))
+            await result  # Clean up
+
+        asyncio.run(run_test())
+
+    def test_sync_path_direct_return(self):
+        """Test that sync path returns directly without coroutine"""
+        mock_response = Mock()
+
+        def sync_get_response(request):
+            return mock_response
+
+        middleware = PosthogContextMiddleware(sync_get_response)
+
+        request = MockRequest()
+        result = middleware(request)
+
+        # Should NOT be a coroutine
+        self.assertFalse(asyncio.iscoroutine(result))
+        self.assertEqual(result, mock_response)
+
 
 if __name__ == "__main__":
     unittest.main()

posthog/test/test_before_send.py

@@ -40,16 +40,30 @@ class TestClient(unittest.TestCase):
             event["properties"]["processed_by_before_send"] = True
             return event
 
-        client = Client(
-            FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=my_before_send
-        )
-        success, msg = client.capture("user1", "test_event", {"original": "value"})
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=my_before_send,
+                sync_mode=True,
+            )
+            msg_uuid = client.capture(
+                "test_event", distinct_id="user1", properties={"original": "value"}
+            )
 
-        self.assertTrue(success)
-        self.assertEqual(msg["properties"]["processed_by_before_send"], True)
-        self.assertEqual(msg["properties"]["original"], "value")
-        self.assertEqual(len(processed_events), 1)
-        self.assertEqual(processed_events[0]["event"], "test_event")
+            self.assertIsNotNone(msg_uuid)
+
+            # Get the enqueued message from the mock
+            mock_post.assert_called_once()
+            batch_data = mock_post.call_args[1]["batch"]
+            enqueued_msg = batch_data[0]
+
+            self.assertEqual(
+                enqueued_msg["properties"]["processed_by_before_send"], True
+            )
+            self.assertEqual(enqueued_msg["properties"]["original"], "value")
+            self.assertEqual(len(processed_events), 1)
+            self.assertEqual(processed_events[0]["event"], "test_event")
 
     def test_before_send_callback_drops_event(self):
         """Test that before_send callback can drop events by returning None."""
@@ -59,20 +73,27 @@ class TestClient(unittest.TestCase):
                 return None
             return event
 
-        client = Client(
-            FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=drop_test_events
-        )
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=drop_test_events,
+                sync_mode=True,
+            )
 
-        # Event should be dropped
-        success, msg = client.capture("user1", "test_drop_me")
-        self.assertTrue(success)
-        self.assertIsNone(msg)
+            # Event should be dropped
+            msg_uuid = client.capture("test_drop_me", distinct_id="user1")
+            self.assertIsNone(msg_uuid)
 
-        # Event should go through
-        success, msg = client.capture("user1", "keep_me")
-        self.assertTrue(success)
-        self.assertIsNotNone(msg)
-        self.assertEqual(msg["event"], "keep_me")
+            # Event should go through
+            msg_uuid = client.capture("keep_me", distinct_id="user1")
+            self.assertIsNotNone(msg_uuid)
+
+            # Check the enqueued message
+            mock_post.assert_called_once()
+            batch_data = mock_post.call_args[1]["batch"]
+            enqueued_msg = batch_data[0]
+            self.assertEqual(enqueued_msg["event"], "keep_me")
 
     def test_before_send_callback_handles_exceptions(self):
         """Test that exceptions in before_send don't crash the client."""
@@ -80,18 +101,26 @@ class TestClient(unittest.TestCase):
         def buggy_before_send(event):
             raise ValueError("Oops!")
 
-        client = Client(
-            FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=buggy_before_send
-        )
-        success, msg = client.capture("user1", "robust_event")
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=buggy_before_send,
+                sync_mode=True,
+            )
+            msg_uuid = client.capture("robust_event", distinct_id="user1")
 
-        # Event should still be sent despite the exception
-        self.assertTrue(success)
-        self.assertIsNotNone(msg)
-        self.assertEqual(msg["event"], "robust_event")
+            # Event should still be sent despite the exception
+            self.assertIsNotNone(msg_uuid)
+
+            # Check the enqueued message
+            mock_post.assert_called_once()
+            batch_data = mock_post.call_args[1]["batch"]
+            enqueued_msg = batch_data[0]
+            self.assertEqual(enqueued_msg["event"], "robust_event")
 
     def test_before_send_callback_works_with_all_event_types(self):
-        """Test that before_send works with capture, identify, set, etc."""
+        """Test that before_send works with capture, set, etc."""
 
         def add_marker(event):
             if "properties" not in event:
@@ -99,38 +128,46 @@ class TestClient(unittest.TestCase):
             event["properties"]["marked"] = True
             return event
 
-        client = Client(
-            FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=add_marker
-        )
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=add_marker,
+                sync_mode=True,
+            )
 
-        # Test capture
-        success, msg = client.capture("user1", "event")
-        self.assertTrue(success)
-        self.assertTrue(msg["properties"]["marked"])
+            # Test capture
+            msg_uuid = client.capture("event", distinct_id="user1")
+            self.assertIsNotNone(msg_uuid)
 
-        # Test identify
-        success, msg = client.identify("user1", {"trait": "value"})
-        self.assertTrue(success)
-        self.assertTrue(msg["properties"]["marked"])
+            # Test set
+            msg_uuid = client.set(distinct_id="user1", properties={"prop": "value"})
+            self.assertIsNotNone(msg_uuid)
 
-        # Test set
-        success, msg = client.set("user1", {"prop": "value"})
-        self.assertTrue(success)
-        self.assertTrue(msg["properties"]["marked"])
-
-        # Test page
-        success, msg = client.page("user1", "https://example.com")
-        self.assertTrue(success)
-        self.assertTrue(msg["properties"]["marked"])
+            # Check all events were marked
+            self.assertEqual(mock_post.call_count, 2)
+            for call in mock_post.call_args_list:
+                batch_data = call[1]["batch"]
+                enqueued_msg = batch_data[0]
+                self.assertTrue(enqueued_msg["properties"]["marked"])
 
     def test_before_send_callback_disabled_when_none(self):
         """Test that client works normally when before_send is None."""
-        client = Client(FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=None)
-        success, msg = client.capture("user1", "normal_event")
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=None,
+                sync_mode=True,
+            )
+            msg_uuid = client.capture("normal_event", distinct_id="user1")
+            self.assertIsNotNone(msg_uuid)
 
-        self.assertTrue(success)
-        self.assertIsNotNone(msg)
-        self.assertEqual(msg["event"], "normal_event")
+            # Check the event was sent normally
+            mock_post.assert_called_once()
+            batch_data = mock_post.call_args[1]["batch"]
+            enqueued_msg = batch_data[0]
+            self.assertEqual(enqueued_msg["event"], "normal_event")
 
     def test_before_send_callback_pii_scrubbing_example(self):
         """Test a realistic PII scrubbing use case."""
@@ -152,20 +189,30 @@ class TestClient(unittest.TestCase):
 
             return event
 
-        client = Client(
-            FAKE_TEST_API_KEY, on_error=self.set_fail, before_send=scrub_pii
-        )
-        success, msg = client.capture(
-            "user1",
-            "form_submit",
-            {
-                "email": "user@example.com",
-                "credit_card": "1234-5678-9012-3456",
-                "form_name": "contact",
-            },
-        )
+        with mock.patch("posthog.client.batch_post") as mock_post:
+            client = Client(
+                FAKE_TEST_API_KEY,
+                on_error=self.set_fail,
+                before_send=scrub_pii,
+                sync_mode=True,
+            )
+            msg_uuid = client.capture(
+                "form_submit",
+                distinct_id="user1",
+                properties={
+                    "email": "user@example.com",
+                    "credit_card": "1234-5678-9012-3456",
+                    "form_name": "contact",
+                },
+            )
 
-        self.assertTrue(success)
-        self.assertEqual(msg["properties"]["email"], "***@example.com")
-        self.assertNotIn("credit_card", msg["properties"])
-        self.assertEqual(msg["properties"]["form_name"], "contact")
+            self.assertIsNotNone(msg_uuid)
+
+            # Check the enqueued message was scrubbed
+            mock_post.assert_called_once()
+            batch_data = mock_post.call_args[1]["batch"]
+            enqueued_msg = batch_data[0]
+
+            self.assertEqual(enqueued_msg["properties"]["email"], "***@example.com")
+            self.assertNotIn("credit_card", enqueued_msg["properties"])
+            self.assertEqual(enqueued_msg["properties"]["form_name"], "contact")

posthog/test/test_consumer.py

@@ -1,8 +1,10 @@
 import json
 import time
 import unittest
+from typing import Any
 
 import mock
+from parameterized import parameterized
 
 try:
     from queue import Queue
@@ -14,15 +16,19 @@ from posthog.request import APIError
 from posthog.test.test_utils import TEST_API_KEY
 
 
+def _track_event(event_name: str = "python event") -> dict[str, str]:
+    return {"type": "track", "event": event_name, "distinct_id": "distinct_id"}
+
+
 class TestConsumer(unittest.TestCase):
-    def test_next(self):
+    def test_next(self) -> None:
         q = Queue()
         consumer = Consumer(q, "")
         q.put(1)
         next = consumer.next()
         self.assertEqual(next, [1])
 
-    def test_next_limit(self):
+    def test_next_limit(self) -> None:
         q = Queue()
         flush_at = 50
         consumer = Consumer(q, "", flush_at)
@@ -31,7 +37,7 @@ class TestConsumer(unittest.TestCase):
         next = consumer.next()
         self.assertEqual(next, list(range(flush_at)))
 
-    def test_dropping_oversize_msg(self):
+    def test_dropping_oversize_msg(self) -> None:
         q = Queue()
         consumer = Consumer(q, "")
         oversize_msg = {"m": "x" * MAX_MSG_SIZE}
@@ -40,15 +46,14 @@ class TestConsumer(unittest.TestCase):
         self.assertEqual(next, [])
         self.assertTrue(q.empty())
 
-    def test_upload(self):
+    def test_upload(self) -> None:
         q = Queue()
         consumer = Consumer(q, TEST_API_KEY)
-        track = {"type": "track", "event": "python event", "distinct_id": "distinct_id"}
-        q.put(track)
+        q.put(_track_event())
         success = consumer.upload()
         self.assertTrue(success)
 
-    def test_flush_interval(self):
+    def test_flush_interval(self) -> None:
         # Put _n_ items in the queue, pausing a little bit more than
         # _flush_interval_ after each one.
         # The consumer should upload _n_ times.
@@ -57,17 +62,12 @@ class TestConsumer(unittest.TestCase):
         consumer = Consumer(q, TEST_API_KEY, flush_at=10, flush_interval=flush_interval)
         with mock.patch("posthog.consumer.batch_post") as mock_post:
             consumer.start()
-            for i in range(0, 3):
-                track = {
-                    "type": "track",
-                    "event": "python event %d" % i,
-                    "distinct_id": "distinct_id",
-                }
-                q.put(track)
+            for i in range(3):
+                q.put(_track_event("python event %d" % i))
                 time.sleep(flush_interval * 1.1)
             self.assertEqual(mock_post.call_count, 3)
 
-    def test_multiple_uploads_per_interval(self):
+    def test_multiple_uploads_per_interval(self) -> None:
         # Put _flush_at*2_ items in the queue at once, then pause for
         # _flush_interval_. The consumer should upload 2 times.
         q = Queue()
@@ -78,88 +78,60 @@ class TestConsumer(unittest.TestCase):
         )
         with mock.patch("posthog.consumer.batch_post") as mock_post:
             consumer.start()
-            for i in range(0, flush_at * 2):
-                track = {
-                    "type": "track",
-                    "event": "python event %d" % i,
-                    "distinct_id": "distinct_id",
-                }
-                q.put(track)
+            for i in range(flush_at * 2):
+                q.put(_track_event("python event %d" % i))
             time.sleep(flush_interval * 1.1)
             self.assertEqual(mock_post.call_count, 2)
 
-    def test_request(self):
+    def test_request(self) -> None:
         consumer = Consumer(None, TEST_API_KEY)
-        track = {"type": "track", "event": "python event", "distinct_id": "distinct_id"}
-        consumer.request([track])
+        consumer.request([_track_event()])
 
-    def _test_request_retry(self, consumer, expected_exception, exception_count):
-        def mock_post(*args, **kwargs):
-            mock_post.call_count += 1
-            if mock_post.call_count <= exception_count:
-                raise expected_exception
+    def _run_retry_test(
+        self, exception: Exception, exception_count: int, retries: int = 10
+    ) -> None:
+        call_count = [0]
 
-        mock_post.call_count = 0
+        def mock_post(*args: Any, **kwargs: Any) -> None:
+            call_count[0] += 1
+            if call_count[0] <= exception_count:
+                raise exception
 
+        consumer = Consumer(None, TEST_API_KEY, retries=retries)
         with mock.patch(
             "posthog.consumer.batch_post", mock.Mock(side_effect=mock_post)
         ):
-            track = {
-                "type": "track",
-                "event": "python event",
-                "distinct_id": "distinct_id",
-            }
-            # request() should succeed if the number of exceptions raised is
-            # less than the retries paramater.
-            if exception_count <= consumer.retries:
-                consumer.request([track])
+            if exception_count <= retries:
+                consumer.request([_track_event()])
             else:
-                # if exceptions are raised more times than the retries
-                # parameter, we expect the exception to be returned to
-                # the caller.
-                try:
-                    consumer.request([track])
-                except type(expected_exception) as exc:
-                    self.assertEqual(exc, expected_exception)
-                else:
-                    self.fail(
-                        "request() should raise an exception if still failing after %d retries"
-                        % consumer.retries
-                    )
+                with self.assertRaises(type(exception)):
+                    consumer.request([_track_event()])
 
-    def test_request_retry(self):
-        # we should retry on general errors
-        consumer = Consumer(None, TEST_API_KEY)
-        self._test_request_retry(consumer, Exception("generic exception"), 2)
+    @parameterized.expand(
+        [
+            ("general_errors", Exception("generic exception"), 2),
+            ("server_errors", APIError(500, "Internal Server Error"), 2),
+            ("rate_limit_errors", APIError(429, "Too Many Requests"), 2),
+        ]
+    )
+    def test_request_retries_on_retriable_errors(
+        self, _name: str, exception: Exception, exception_count: int
+    ) -> None:
+        self._run_retry_test(exception, exception_count)
 
-        # we should retry on server errors
-        consumer = Consumer(None, TEST_API_KEY)
-        self._test_request_retry(consumer, APIError(500, "Internal Server Error"), 2)
+    def test_request_does_not_retry_client_errors(self) -> None:
+        with self.assertRaises(APIError):
+            self._run_retry_test(APIError(400, "Client Errors"), 1)
 
-        # we should retry on HTTP 429 errors
-        consumer = Consumer(None, TEST_API_KEY)
-        self._test_request_retry(consumer, APIError(429, "Too Many Requests"), 2)
+    def test_request_fails_when_exceptions_exceed_retries(self) -> None:
+        self._run_retry_test(APIError(500, "Internal Server Error"), 4, retries=3)
 
-        # we should NOT retry on other client errors
-        consumer = Consumer(None, TEST_API_KEY)
-        api_error = APIError(400, "Client Errors")
-        try:
-            self._test_request_retry(consumer, api_error, 1)
-        except APIError:
-            pass
-        else:
-            self.fail("request() should not retry on client errors")
-
-        # test for number of exceptions raise > retries value
-        consumer = Consumer(None, TEST_API_KEY, retries=3)
-        self._test_request_retry(consumer, APIError(500, "Internal Server Error"), 3)
-
-    def test_pause(self):
+    def test_pause(self) -> None:
         consumer = Consumer(None, TEST_API_KEY)
         consumer.pause()
         self.assertFalse(consumer.running)
 
-    def test_max_batch_size(self):
+    def test_max_batch_size(self) -> None:
         q = Queue()
         consumer = Consumer(q, TEST_API_KEY, flush_at=100000, flush_interval=3)
         properties = {}
@@ -175,7 +147,7 @@ class TestConsumer(unittest.TestCase):
         # Let's capture 8MB of data to trigger two batches
         n_msgs = int(8_000_000 / msg_size)
 
-        def mock_post_fn(_, data, **kwargs):
+        def mock_post_fn(_: str, data: str, **kwargs: Any) -> mock.Mock:
             res = mock.Mock()
             res.status_code = 200
             request_size = len(data.encode())
@@ -194,3 +166,91 @@ class TestConsumer(unittest.TestCase):
                 q.put(track)
             q.join()
             self.assertEqual(mock_post.call_count, 2)
+
+    def test_request_sleeps_with_retry_after(self) -> None:
+        error = APIError(429, "Too Many Requests", retry_after=5.0)
+        call_count = [0]
+
+        def mock_post(*args: Any, **kwargs: Any) -> None:
+            call_count[0] += 1
+            if call_count[0] <= 1:
+                raise error
+
+        consumer = Consumer(None, TEST_API_KEY, retries=3)
+        with (
+            mock.patch("posthog.consumer.batch_post", side_effect=mock_post),
+            mock.patch("posthog.consumer.time.sleep") as mock_sleep,
+        ):
+            consumer.request([_track_event()])
+            mock_sleep.assert_called_once_with(5.0)
+
+    def test_request_uses_exponential_backoff_without_retry_after(self) -> None:
+        error = APIError(503, "Service Unavailable")
+        call_count = [0]
+
+        def mock_post(*args: Any, **kwargs: Any) -> None:
+            call_count[0] += 1
+            if call_count[0] <= 3:
+                raise error
+
+        consumer = Consumer(None, TEST_API_KEY, retries=3)
+        with (
+            mock.patch("posthog.consumer.batch_post", side_effect=mock_post),
+            mock.patch("posthog.consumer.time.sleep") as mock_sleep,
+        ):
+            consumer.request([_track_event()])
+            self.assertEqual(
+                mock_sleep.call_args_list,
+                [
+                    mock.call(1),  # 2^0
+                    mock.call(2),  # 2^1
+                    mock.call(4),  # 2^2
+                ],
+            )
+
+    def test_request_retries_on_408(self) -> None:
+        call_count = [0]
+
+        def mock_post(*args: Any, **kwargs: Any) -> None:
+            call_count[0] += 1
+            if call_count[0] <= 1:
+                raise APIError(408, "Request Timeout")
+
+        consumer = Consumer(None, TEST_API_KEY, retries=3)
+        with (
+            mock.patch("posthog.consumer.batch_post", side_effect=mock_post),
+            mock.patch("posthog.consumer.time.sleep"),
+        ):
+            consumer.request([_track_event()])
+            self.assertEqual(call_count[0], 2)
+
+    @parameterized.expand(
+        [
+            ("on_error_succeeds", False),
+            ("on_error_raises", True),
+        ]
+    )
+    def test_upload_exception_calls_on_error_and_does_not_raise(
+        self, _name: str, on_error_raises: bool
+    ) -> None:
+        on_error_called: list[tuple[Exception, list[dict[str, str]]]] = []
+
+        def on_error(e: Exception, batch: list[dict[str, str]]) -> None:
+            on_error_called.append((e, batch))
+            if on_error_raises:
+                raise Exception("on_error failed")
+
+        q = Queue()
+        consumer = Consumer(q, TEST_API_KEY, on_error=on_error)
+        track = _track_event()
+        q.put(track)
+
+        with mock.patch.object(
+            consumer, "request", side_effect=Exception("request failed")
+        ):
+            result = consumer.upload()
+
+        self.assertFalse(result)
+        self.assertEqual(len(on_error_called), 1)
+        self.assertEqual(str(on_error_called[0][0]), "request failed")
+        self.assertEqual(on_error_called[0][1], [track])

posthog/test/test_contexts.py

@@ -1,8 +1,7 @@
 import unittest
 from unittest.mock import patch
 
-from posthog.scopes import (
-    clear_tags,
+from posthog.contexts import (
     get_tags,
     new_context,
     scoped,
@@ -14,11 +13,7 @@ from posthog.scopes import (
 )
 
 
-class TestScopes(unittest.TestCase):
-    def setUp(self):
-        # Reset any context between tests
-        clear_tags()
-
+class TestContexts(unittest.TestCase):
     def test_tag_and_get_tags(self):
         with new_context(fresh=True):
             tag("key1", "value1")
@@ -28,14 +23,6 @@ class TestScopes(unittest.TestCase):
             assert tags["key1"] == "value1"
             assert tags["key2"] == 2
 
-    def test_clear_tags(self):
-        with new_context(fresh=True):
-            tag("key1", "value1")
-            assert get_tags()["key1"] == "value1"
-
-            clear_tags()
-            assert get_tags() == {}
-
     def test_new_context_isolation(self):
         with new_context(fresh=True):
             # Set tag in outer context
@@ -204,6 +191,32 @@ class TestScopes(unittest.TestCase):
             assert get_context_distinct_id() == "user123"
             assert get_context_session_id() == "session456"
 
+    def test_child_tags_override_parent_tags_in_non_fresh_context(self):
+        with new_context(fresh=True):
+            tag("shared_key", "parent_value")
+            tag("parent_only", "parent")
+
+            with new_context(fresh=False):
+                # Child should inherit parent tags
+                assert get_tags()["parent_only"] == "parent"
+
+                # Child sets same key - should override parent
+                tag("shared_key", "child_value")
+                tag("child_only", "child")
+
+                tags = get_tags()
+                # Child value should win for shared key
+                assert tags["shared_key"] == "child_value"
+                # Both parent and child tags should be present
+                assert tags["parent_only"] == "parent"
+                assert tags["child_only"] == "child"
+
+            # Parent context should be unchanged
+            parent_tags = get_tags()
+            assert parent_tags["shared_key"] == "parent_value"
+            assert parent_tags["parent_only"] == "parent"
+            assert "child_only" not in parent_tags
+
     def test_scoped_decorator_with_context_ids(self):
         @scoped()
         def function_with_context():

posthog/test/test_exception_capture.py

@@ -34,17 +34,72 @@ def test_excepthook(tmpdir):
     )
 
 
-def test_trying_to_use_django_integration(tmpdir):
+def test_code_variables_capture(tmpdir):
     app = tmpdir.join("app.py")
     app.write(
         dedent(
             """
-    from posthog import Posthog, Integrations
-    posthog = Posthog('phc_x', host='https://eu.i.posthog.com', enable_exception_autocapture=True, exception_autocapture_integrations=[Integrations.Django], debug=True, on_error=lambda e, batch: print('error handling batch: ', e, batch))
-
-    # frame_value = "LOL"
-
-    1/0
+    import os
+    from posthog import Posthog
+    
+    class UnserializableObject:
+        pass
+    
+    posthog = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def trigger_error():
+        my_string = "hello world"
+        my_number = 42
+        my_bool = True
+        my_dict = {"name": "test", "value": 123}
+        my_sensitive_dict = {
+            "safe_key": "safe_value",
+            "password": "secret123",  # key matches pattern -> should be masked
+            "other_key": "contains_password_here",  # value matches pattern -> should be masked
+        }
+        my_nested_dict = {
+            "level1": {
+                "level2": {
+                    "api_key": "nested_secret",  # deeply nested key matches
+                    "data": "contains_token_here",  # deeply nested value matches
+                    "safe": "visible",
+                }
+            }
+        }
+        my_list = ["safe_item", "has_password_inside", "another_safe"]
+        my_tuple = ("tuple_safe", "secret_in_value", "tuple_also_safe")
+        my_list_of_dicts = [
+            {"id": 1, "password": "list_dict_secret"},
+            {"id": 2, "value": "safe_value"},
+        ]
+        my_obj = UnserializableObject()
+        my_password = "secret123"  # Should be masked by default (name matches)
+        my_innocent_var = "contains_password_here"  # Should be masked by default (value matches)
+        __should_be_ignored = "hidden"  # Should be ignored by default
+        
+        1/0  # Trigger exception
+    
+    def intermediate_function():
+        request_id = "abc-123"
+        user_count = 100
+        is_active = True
+        
+        trigger_error()
+    
+    def process_data():
+        batch_size = 50
+        retry_count = 3
+        
+        intermediate_function()
+    
+    process_data()
     """
         )
     )
@@ -55,9 +110,580 @@ def test_trying_to_use_django_integration(tmpdir):
     output = excinfo.value.output
 
     assert b"ZeroDivisionError" in output
-    assert b"LOL" in output
-    assert b"DEBUG:posthog:data uploaded successfully" in output
+    assert b"code_variables" in output
+
+    # Variables from trigger_error frame
+    assert b"'my_string': 'hello world'" in output
+    assert b"'my_number': 42" in output
+    assert b"'my_bool': 'True'" in output
+    assert b'"my_dict": "{\\"name\\": \\"test\\", \\"value\\": 123}"' in output
     assert (
-        b'"$exception_list": [{"mechanism": {"type": "generic", "handled": true}, "module": null, "type": "ZeroDivisionError", "value": "division by zero", "stacktrace": {"frames": [{"platform": "python", "filename": "app.py", "abs_path"'
+        b'{\\"safe_key\\": \\"safe_value\\", \\"password\\": \\"$$_posthog_redacted_based_on_masking_rules_$$\\", \\"other_key\\": \\"$$_posthog_redacted_based_on_masking_rules_$$\\"}'
         in output
     )
+    assert (
+        b'{\\"level1\\": {\\"level2\\": {\\"api_key\\": \\"$$_posthog_redacted_based_on_masking_rules_$$\\", \\"data\\": \\"$$_posthog_redacted_based_on_masking_rules_$$\\", \\"safe\\": \\"visible\\"}}}'
+        in output
+    )
+    assert (
+        b'[\\"safe_item\\", \\"$$_posthog_redacted_based_on_masking_rules_$$\\", \\"another_safe\\"]'
+        in output
+    )
+    assert (
+        b'[\\"tuple_safe\\", \\"$$_posthog_redacted_based_on_masking_rules_$$\\", \\"tuple_also_safe\\"]'
+        in output
+    )
+    assert (
+        b'[{\\"id\\": 1, \\"password\\": \\"$$_posthog_redacted_based_on_masking_rules_$$\\"}, {\\"id\\": 2, \\"value\\": \\"safe_value\\"}]'
+        in output
+    )
+    assert b"<__main__.UnserializableObject object at" in output
+    assert b"'my_password': '$$_posthog_redacted_based_on_masking_rules_$$'" in output
+    assert (
+        b"'my_innocent_var': '$$_posthog_redacted_based_on_masking_rules_$$'" in output
+    )
+    assert b"'__should_be_ignored':" not in output
+
+    # Variables from intermediate_function frame
+    assert b"'request_id': 'abc-123'" in output
+    assert b"'user_count': 100" in output
+    assert b"'is_active': 'True'" in output
+
+    # Variables from process_data frame
+    assert b"'batch_size': 50" in output
+    assert b"'retry_count': 3" in output
+
+
+def test_code_variables_context_override(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    import posthog
+    from posthog import Posthog
+    
+    posthog_client = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=False,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def process_data():
+        bank = "should_be_masked"
+        __dunder_var = "should_be_visible"
+        
+        1/0
+    
+    with posthog.new_context(client=posthog_client):
+        posthog.set_capture_exception_code_variables_context(True)
+        posthog.set_code_variables_mask_patterns_context([r"(?i).*bank.*"])
+        posthog.set_code_variables_ignore_patterns_context([])
+        
+        process_data()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output
+
+    assert b"ZeroDivisionError" in output
+    assert b"code_variables" in output
+    assert b"'bank': '$$_posthog_redacted_based_on_masking_rules_$$'" in output
+    assert b"'__dunder_var': 'should_be_visible'" in output
+
+
+def test_code_variables_size_limiter(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    from posthog import Posthog
+    
+    posthog = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def trigger_error():
+        var_a = "a" * 2000
+        var_b = "b" * 2000
+        var_c = "c" * 2000
+        var_d = "d" * 2000
+        var_e = "e" * 2000
+        var_f = "f" * 2000
+        var_g = "g" * 2000
+        
+        1/0
+    
+    def intermediate_function():
+        var_h = "h" * 2000
+        var_i = "i" * 2000
+        var_j = "j" * 2000
+        var_k = "k" * 2000
+        var_l = "l" * 2000
+        var_m = "m" * 2000
+        var_n = "n" * 2000
+        
+        trigger_error()
+    
+    def process_data():
+        var_o = "o" * 2000
+        var_p = "p" * 2000
+        var_q = "q" * 2000
+        var_r = "r" * 2000
+        var_s = "s" * 2000
+        var_t = "t" * 2000
+        var_u = "u" * 2000
+        
+        intermediate_function()
+    
+    process_data()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "code_variables" in output
+
+    captured_vars = []
+    for var_name in [
+        "var_a",
+        "var_b",
+        "var_c",
+        "var_d",
+        "var_e",
+        "var_f",
+        "var_g",
+        "var_h",
+        "var_i",
+        "var_j",
+        "var_k",
+        "var_l",
+        "var_m",
+        "var_n",
+        "var_o",
+        "var_p",
+        "var_q",
+        "var_r",
+        "var_s",
+        "var_t",
+        "var_u",
+    ]:
+        if f"'{var_name}'" in output:
+            captured_vars.append(var_name)
+
+    assert len(captured_vars) > 0
+    assert len(captured_vars) < 21
+
+
+def test_code_variables_disabled_capture(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    from posthog import Posthog
+    
+    posthog = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=False,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def trigger_error():
+        my_string = "hello world"
+        my_number = 42
+        my_bool = True
+        
+        1/0
+    
+    trigger_error()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "'code_variables':" not in output
+    assert '"code_variables":' not in output
+    assert "'my_string'" not in output
+    assert "'my_number'" not in output
+
+
+def test_code_variables_enabled_then_disabled_in_context(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    import posthog
+    from posthog import Posthog
+    
+    posthog_client = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def process_data():
+        my_var = "should not be captured"
+        important_value = 123
+        
+        1/0
+    
+    with posthog.new_context(client=posthog_client):
+        posthog.set_capture_exception_code_variables_context(False)
+        
+        process_data()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "'code_variables':" not in output
+    assert '"code_variables":' not in output
+    assert "'my_var'" not in output
+    assert "'important_value'" not in output
+
+
+def test_code_variables_repr_fallback(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    import re
+    from datetime import datetime, timedelta
+    from decimal import Decimal
+    from fractions import Fraction
+    from posthog import Posthog
+    
+    class CustomReprClass:
+        def __repr__(self):
+            return '<CustomReprClass: custom representation>'
+    
+    posthog = Posthog(
+        'phc_x', 
+        host='https://eu.i.posthog.com', 
+        debug=True, 
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+    
+    def trigger_error():
+        my_regex = re.compile(r'\\d+')
+        my_datetime = datetime(2024, 1, 15, 10, 30, 45)
+        my_timedelta = timedelta(days=5, hours=3)
+        my_decimal = Decimal('123.456')
+        my_fraction = Fraction(3, 4)
+        my_set = {1, 2, 3}
+        my_frozenset = frozenset([4, 5, 6])
+        my_bytes = b'hello bytes'
+        my_bytearray = bytearray(b'mutable bytes')
+        my_memoryview = memoryview(b'memory view')
+        my_complex = complex(3, 4)
+        my_range = range(10)
+        my_custom = CustomReprClass()
+        my_lambda = lambda x: x * 2
+        my_function = trigger_error
+        
+        1/0
+    
+    trigger_error()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "code_variables" in output
+
+    assert "re.compile(" in output and "\\\\d+" in output
+    assert "datetime.datetime(2024, 1, 15, 10, 30, 45)" in output
+    assert "datetime.timedelta(days=5, seconds=10800)" in output
+    assert "Decimal('123.456')" in output
+    assert "Fraction(3, 4)" in output
+    assert "{1, 2, 3}" in output
+    assert "frozenset({4, 5, 6})" in output
+    assert "b'hello bytes'" in output
+    assert "bytearray(b'mutable bytes')" in output
+    assert "<memory at" in output
+    assert "(3+4j)" in output
+    assert "range(0, 10)" in output
+    assert "<CustomReprClass: custom representation>" in output
+    assert "<lambda>" in output
+    assert "<function trigger_error at" in output
+
+
+def test_code_variables_too_long_string_value_replaced(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    from posthog import Posthog
+
+    posthog = Posthog(
+        'phc_x',
+        host='https://eu.i.posthog.com',
+        debug=True,
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+
+    def trigger_error():
+        short_value = "I am short"
+        long_value = "x" * 20000
+        long_blob = "password_" + "a" * 20000
+
+        1/0
+
+    trigger_error()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "code_variables" in output
+
+    assert "'short_value': 'I am short'" in output
+
+    assert "$$_posthog_value_too_long_$$" in output
+
+    assert "'long_blob': '$$_posthog_value_too_long_$$'" in output
+
+
+def test_code_variables_too_long_string_in_nested_dict(tmpdir):
+    app = tmpdir.join("app.py")
+    app.write(
+        dedent(
+            """
+    import os
+    from posthog import Posthog
+
+    posthog = Posthog(
+        'phc_x',
+        host='https://eu.i.posthog.com',
+        debug=True,
+        enable_exception_autocapture=True,
+        capture_exception_code_variables=True,
+        project_root=os.path.dirname(os.path.abspath(__file__))
+    )
+
+    def trigger_error():
+        my_data = {
+            "short_key": "short_val",
+            "long_key": "y" * 20000,
+            "nested": {
+                "deep_long": "z" * 20000,
+                "deep_short": "ok",
+            },
+        }
+
+        1/0
+
+    trigger_error()
+    """
+        )
+    )
+
+    with pytest.raises(subprocess.CalledProcessError) as excinfo:
+        subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
+
+    output = excinfo.value.output.decode("utf-8")
+
+    assert "ZeroDivisionError" in output
+    assert "code_variables" in output
+
+    assert "short_val" in output
+    assert "ok" in output
+
+    assert "$$_posthog_value_too_long_$$" in output
+    assert "y" * 1000 not in output
+    assert "z" * 1000 not in output
+
+
+def test_mask_sensitive_data_too_long_dict_key():
+    from posthog.exception_utils import (
+        CODE_VARIABLES_TOO_LONG_VALUE,
+        _compile_patterns,
+        _mask_sensitive_data,
+    )
+
+    compiled_mask = _compile_patterns([r"(?i)password"])
+
+    result = _mask_sensitive_data(
+        {
+            "short": "visible",
+            "k" * 20000: "hidden_val",
+            "password": "secret",
+        },
+        compiled_mask,
+    )
+
+    assert result["short"] == "visible"
+    # This then gets shortened by the JSON truncation at 1024 chars anyways so no worries
+    assert result["k" * 20000] == CODE_VARIABLES_TOO_LONG_VALUE
+    assert result["password"] == "$$_posthog_redacted_based_on_masking_rules_$$"
+
+
+def test_mask_sensitive_data_circular_ref():
+    from posthog.exception_utils import _compile_patterns, _mask_sensitive_data
+
+    compiled_mask = _compile_patterns([r"(?i)password"])
+
+    # Circular dict
+    circular_dict = {"key": "value"}
+    circular_dict["self"] = circular_dict
+
+    result = _mask_sensitive_data(circular_dict, compiled_mask)
+    assert result["key"] == "value"
+    assert result["self"] == "<circular ref>"
+
+    # Circular list
+    circular_list = ["item"]
+    circular_list.append(circular_list)
+
+    result = _mask_sensitive_data(circular_list, compiled_mask)
+    assert result[0] == "item"
+    assert result[1] == "<circular ref>"
+
+
+def test_compile_patterns_fast_path_and_regex_fallback():
+    from posthog.exception_utils import _compile_patterns, _pattern_matches
+
+    # Simple case-insensitive patterns should become substrings
+    simple_only = _compile_patterns([r"(?i)password", r"(?i)token", r"(?i)jwt"])
+    substrings, regexes = simple_only
+    assert substrings == ["password", "token", "jwt"]
+    assert regexes == []
+
+    assert _pattern_matches("my_password_var", simple_only) is True
+    assert _pattern_matches("MY_TOKEN", simple_only) is True
+    assert _pattern_matches("safe_variable", simple_only) is False
+
+    # Complex regex patterns should stay as compiled regexes
+    complex_only = _compile_patterns([r"^__.*", r"\d{3,}", r"^sk_live_"])
+    substrings, regexes = complex_only
+    assert substrings == []
+    assert len(regexes) == 3
+
+    assert _pattern_matches("__dunder", complex_only) is True
+    assert _pattern_matches("has_999_numbers", complex_only) is True
+    assert _pattern_matches("sk_live_abc123", complex_only) is True
+    assert _pattern_matches("normal_var", complex_only) is False
+
+    # Mixed: simple substrings + complex regexes together
+    mixed = _compile_patterns(
+        [
+            r"(?i)secret",  # simple
+            r"(?i)api_key",  # simple
+            r"^__.*",  # regex
+            r"\btoken_\w+",  # regex
+        ]
+    )
+    substrings, regexes = mixed
+    assert substrings == ["secret", "api_key"]
+    assert len(regexes) == 2
+
+    # Substring matches
+    assert _pattern_matches("my_secret", mixed) is True
+    assert _pattern_matches("API_KEY_VALUE", mixed) is True
+
+    # Regex matches
+    assert _pattern_matches("__private", mixed) is True
+    assert _pattern_matches("token_abc", mixed) is True
+
+    # No match
+    assert _pattern_matches("safe_var", mixed) is False
+
+
+def test_mask_sensitive_data_large_dict_replaced():
+    from posthog.exception_utils import (
+        CODE_VARIABLES_TOO_LONG_VALUE,
+        _compile_patterns,
+        _mask_sensitive_data,
+    )
+
+    compiled_mask = _compile_patterns([r"(?i)password"])
+
+    large_dict = {f"key_{i}": f"value_{i}" for i in range(300)}
+
+    result = _mask_sensitive_data(large_dict, compiled_mask)
+
+    assert result == CODE_VARIABLES_TOO_LONG_VALUE
+
+
+def test_mask_sensitive_data_large_list_replaced():
+    from posthog.exception_utils import (
+        CODE_VARIABLES_TOO_LONG_VALUE,
+        _compile_patterns,
+        _mask_sensitive_data,
+    )
+
+    compiled_mask = _compile_patterns([r"(?i)password"])
+
+    large_list = [f"item_{i}" for i in range(300)]
+
+    result = _mask_sensitive_data(large_list, compiled_mask)
+
+    assert result == CODE_VARIABLES_TOO_LONG_VALUE
+
+
+def test_mask_sensitive_data_large_tuple_replaced():
+    from posthog.exception_utils import (
+        CODE_VARIABLES_TOO_LONG_VALUE,
+        _compile_patterns,
+        _mask_sensitive_data,
+    )
+
+    compiled_mask = _compile_patterns([r"(?i)password"])
+
+    large_tuple = tuple(f"item_{i}" for i in range(300))
+
+    result = _mask_sensitive_data(large_tuple, compiled_mask)
+
+    assert result == CODE_VARIABLES_TOO_LONG_VALUE

posthog/test/test_feature_flag_result.py

@@ -4,7 +4,13 @@ import mock
 
 from posthog.client import Client
 from posthog.test.test_utils import FAKE_TEST_API_KEY
-from posthog.types import FeatureFlag, FeatureFlagResult, FlagMetadata, FlagReason
+from posthog.types import (
+    FeatureFlag,
+    FeatureFlagError,
+    FeatureFlagResult,
+    FlagMetadata,
+    FlagReason,
+)
 
 
 class TestFeatureFlagResult(unittest.TestCase):
@@ -189,7 +195,6 @@ class TestGetFeatureFlagResult(unittest.TestCase):
 
     def set_fail(self, e, batch):
         """Mark the failure handler"""
-        print("FAIL", e, batch)  # noqa: T201
         self.failed = True
 
     def setUp(self):
@@ -229,9 +234,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
         self.assertEqual(flag_result.variant, None)
         self.assertEqual(flag_result.payload, 300)
         patch_capture.assert_called_with(
-            "some-distinct-id",
             "$feature_flag_called",
-            {
+            distinct_id="some-distinct-id",
+            properties={
                 "$feature_flag": "person-flag",
                 "$feature_flag_response": True,
                 "locally_evaluated": True,
@@ -241,6 +246,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
             groups={},
             disable_geoip=None,
         )
+        # Verify error property is NOT present on successful evaluation
+        captured_properties = patch_capture.call_args[1]["properties"]
+        self.assertNotIn("$feature_flag_error", captured_properties)
 
     @mock.patch.object(Client, "capture")
     def test_get_feature_flag_result_variant_local_evaluation(self, patch_capture):
@@ -283,9 +291,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
         self.assertEqual(flag_result.payload, {"some": "value"})
 
         patch_capture.assert_called_with(
-            "distinct_id",
             "$feature_flag_called",
-            {
+            distinct_id="distinct_id",
+            properties={
                 "$feature_flag": "person-flag",
                 "$feature_flag_response": "variant-1",
                 "locally_evaluated": True,
@@ -295,6 +303,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
             groups={},
             disable_geoip=None,
         )
+        # Verify error property is NOT present on successful evaluation
+        captured_properties = patch_capture.call_args[1]["properties"]
+        self.assertNotIn("$feature_flag_error", captured_properties)
 
         another_flag_result = self.client.get_feature_flag_result(
             "person-flag", "another-distinct-id", person_properties={"region": "USA"}
@@ -305,9 +316,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
         self.assertIsNone(another_flag_result.payload)
 
         patch_capture.assert_called_with(
-            "another-distinct-id",
             "$feature_flag_called",
-            {
+            distinct_id="another-distinct-id",
+            properties={
                 "$feature_flag": "person-flag",
                 "$feature_flag_response": "variant-2",
                 "locally_evaluated": True,
@@ -345,9 +356,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
         self.assertEqual(flag_result.variant, None)
         self.assertEqual(flag_result.payload, 300)
         patch_capture.assert_called_with(
-            "some-distinct-id",
             "$feature_flag_called",
-            {
+            distinct_id="some-distinct-id",
+            properties={
                 "$feature_flag": "person-flag",
                 "$feature_flag_response": True,
                 "locally_evaluated": False,
@@ -360,6 +371,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
             groups={},
             disable_geoip=None,
         )
+        # Verify error property is NOT present on successful evaluation
+        captured_properties = patch_capture.call_args[1]["properties"]
+        self.assertNotIn("$feature_flag_error", captured_properties)
 
     @mock.patch("posthog.client.flags")
     @mock.patch.object(Client, "capture")
@@ -388,9 +402,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
         self.assertEqual(flag_result.get_value(), "variant-1")
         self.assertEqual(flag_result.payload, [1, 2, 3])
         patch_capture.assert_called_with(
-            "distinct_id",
             "$feature_flag_called",
-            {
+            distinct_id="distinct_id",
+            properties={
                 "$feature_flag": "person-flag",
                 "$feature_flag_response": "variant-1",
                 "locally_evaluated": False,
@@ -403,6 +417,9 @@ class TestGetFeatureFlagResult(unittest.TestCase):
             groups={},
             disable_geoip=None,
         )
+        # Verify error property is NOT present on successful evaluation
+        captured_properties = patch_capture.call_args[1]["properties"]
+        self.assertNotIn("$feature_flag_error", captured_properties)
 
     @mock.patch("posthog.client.flags")
     @mock.patch.object(Client, "capture")
@@ -431,13 +448,435 @@ class TestGetFeatureFlagResult(unittest.TestCase):
 
         self.assertIsNone(flag_result)
         patch_capture.assert_called_with(
-            "some-distinct-id",
             "$feature_flag_called",
-            {
+            distinct_id="some-distinct-id",
+            properties={
                 "$feature_flag": "no-person-flag",
                 "$feature_flag_response": None,
                 "locally_evaluated": False,
                 "$feature/no-person-flag": None,
+                "$feature_flag_error": FeatureFlagError.FLAG_MISSING,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_with_errors_while_computing_flags(
+        self, patch_capture, patch_flags
+    ):
+        """Test that errors_while_computing_flags is included in the $feature_flag_called event.
+
+        When the server returns errorsWhileComputingFlags=true, it indicates that there
+        was an error computing one or more flags. We include this in the event so users
+        can identify and debug flag evaluation issues.
+        """
+        patch_flags.return_value = {
+            "flags": {
+                "my-flag": {
+                    "key": "my-flag",
+                    "enabled": True,
+                    "variant": None,
+                    "reason": {"description": "Matched condition set 1"},
+                    "metadata": {"id": 1, "version": 1, "payload": None},
+                },
+            },
+            "requestId": "test-request-id-789",
+            "errorsWhileComputingFlags": True,
+        }
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertEqual(flag_result.enabled, True)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": True,
+                "locally_evaluated": False,
+                "$feature/my-flag": True,
+                "$feature_flag_request_id": "test-request-id-789",
+                "$feature_flag_reason": "Matched condition set 1",
+                "$feature_flag_id": 1,
+                "$feature_flag_version": 1,
+                "$feature_flag_error": FeatureFlagError.ERRORS_WHILE_COMPUTING,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_flag_not_in_response(
+        self, patch_capture, patch_flags
+    ):
+        """Test that when a flag is not in the API response, we capture flag_missing error.
+
+        This happens when a flag doesn't exist or the user doesn't match any conditions.
+        """
+        patch_flags.return_value = {
+            "flags": {
+                "other-flag": {
+                    "key": "other-flag",
+                    "enabled": True,
+                    "variant": None,
+                    "reason": {"description": "Matched condition set 1"},
+                    "metadata": {"id": 1, "version": 1, "payload": None},
+                },
+            },
+            "requestId": "test-request-id-456",
+        }
+
+        flag_result = self.client.get_feature_flag_result(
+            "missing-flag", "some-distinct-id"
+        )
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "missing-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/missing-flag": None,
+                "$feature_flag_request_id": "test-request-id-456",
+                "$feature_flag_error": FeatureFlagError.FLAG_MISSING,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_errors_computing_and_flag_missing(
+        self, patch_capture, patch_flags
+    ):
+        """Test that both errors are reported when errorsWhileComputingFlags=true AND flag is missing.
+
+        This can happen when the server encounters errors computing flags AND the requested
+        flag is not in the response. Both conditions should be reported for debugging.
+        """
+        patch_flags.return_value = {
+            "flags": {},  # Flag is missing
+            "requestId": "test-request-id-999",
+            "errorsWhileComputingFlags": True,  # But errors also occurred
+        }
+
+        flag_result = self.client.get_feature_flag_result(
+            "missing-flag", "some-distinct-id"
+        )
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "missing-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/missing-flag": None,
+                "$feature_flag_request_id": "test-request-id-999",
+                "$feature_flag_error": f"{FeatureFlagError.ERRORS_WHILE_COMPUTING},{FeatureFlagError.FLAG_MISSING}",
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_unknown_error(self, patch_capture, patch_flags):
+        """Test that unexpected exceptions are captured as unknown_error."""
+        patch_flags.side_effect = Exception("Unexpected error")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.UNKNOWN_ERROR,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_timeout_error(self, patch_capture, patch_flags):
+        """Test that timeout errors are captured specifically."""
+        from posthog.request import RequestsTimeout
+
+        patch_flags.side_effect = RequestsTimeout("Request timed out")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.TIMEOUT,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_connection_error(self, patch_capture, patch_flags):
+        """Test that connection errors are captured specifically."""
+        from posthog.request import RequestsConnectionError
+
+        patch_flags.side_effect = RequestsConnectionError("Connection refused")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.CONNECTION_ERROR,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_api_error(self, patch_capture, patch_flags):
+        """Test that API errors include the status code."""
+        from posthog.request import APIError
+
+        patch_flags.side_effect = APIError(500, "Internal server error")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.api_error(500),
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_get_feature_flag_result_quota_limited(self, patch_capture, patch_flags):
+        """Test that quota limit errors are captured specifically."""
+        from posthog.request import QuotaLimitError
+
+        patch_flags.side_effect = QuotaLimitError(429, "Rate limit exceeded")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        self.assertIsNone(flag_result)
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.QUOTA_LIMITED,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+
+class TestFeatureFlagErrorWithStaleCacheFallback(unittest.TestCase):
+    """Tests for stale cache fallback behavior when flag evaluation fails.
+
+    When the PostHog API is unavailable (timeout, connection error, etc.), the SDK
+    falls back to stale cached flag values if available. These tests verify that:
+    1. The stale cached value is returned when an error occurs
+    2. The $feature_flag_error property is still set (for debugging)
+    3. The response reflects the cached value, not None
+    """
+
+    def set_fail(self, e, batch):
+        """Mark the failure handler"""
+        self.failed = True
+
+    def setUp(self):
+        self.failed = False
+        # Create client with memory-based flag cache enabled
+        self.client = Client(
+            FAKE_TEST_API_KEY,
+            on_error=self.set_fail,
+            flag_fallback_cache_url="memory://local/?ttl=300&size=10000",
+        )
+
+    def _populate_stale_cache(self, distinct_id, flag_key, flag_result):
+        """Pre-populate the flag cache with a value that will be used for stale fallback."""
+        self.client.flag_cache.set_cached_flag(
+            distinct_id,
+            flag_key,
+            flag_result,
+            flag_definition_version=self.client.flag_definition_version,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_timeout_error_returns_stale_cached_value(self, patch_capture, patch_flags):
+        """Test that timeout errors return stale cached value when available."""
+        from posthog.request import RequestsTimeout
+
+        # Pre-populate cache with a flag result
+        cached_result = FeatureFlagResult.from_value_and_payload(
+            "my-flag", "cached-variant", '{"from": "cache"}'
+        )
+        self._populate_stale_cache("some-distinct-id", "my-flag", cached_result)
+
+        # Simulate timeout error
+        patch_flags.side_effect = RequestsTimeout("Request timed out")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        # Should return the stale cached value
+        self.assertIsNotNone(flag_result)
+        self.assertEqual(flag_result.variant, "cached-variant")
+        self.assertEqual(flag_result.payload, {"from": "cache"})
+
+        # Error should still be tracked for debugging
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": "cached-variant",
+                "locally_evaluated": False,
+                "$feature/my-flag": "cached-variant",
+                "$feature_flag_payload": {"from": "cache"},
+                "$feature_flag_error": FeatureFlagError.TIMEOUT,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_connection_error_returns_stale_cached_value(
+        self, patch_capture, patch_flags
+    ):
+        """Test that connection errors return stale cached value when available."""
+        from posthog.request import RequestsConnectionError
+
+        # Pre-populate cache with a boolean flag result
+        cached_result = FeatureFlagResult.from_value_and_payload("my-flag", True, None)
+        self._populate_stale_cache("some-distinct-id", "my-flag", cached_result)
+
+        # Simulate connection error
+        patch_flags.side_effect = RequestsConnectionError("Connection refused")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        # Should return the stale cached value
+        self.assertIsNotNone(flag_result)
+        self.assertEqual(flag_result.enabled, True)
+        self.assertIsNone(flag_result.variant)
+
+        # Error should still be tracked
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": True,
+                "locally_evaluated": False,
+                "$feature/my-flag": True,
+                "$feature_flag_error": FeatureFlagError.CONNECTION_ERROR,
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_api_error_returns_stale_cached_value(self, patch_capture, patch_flags):
+        """Test that API errors return stale cached value when available."""
+        from posthog.request import APIError
+
+        # Pre-populate cache
+        cached_result = FeatureFlagResult.from_value_and_payload(
+            "my-flag", "control", None
+        )
+        self._populate_stale_cache("some-distinct-id", "my-flag", cached_result)
+
+        # Simulate API error
+        patch_flags.side_effect = APIError(503, "Service unavailable")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        # Should return the stale cached value
+        self.assertIsNotNone(flag_result)
+        self.assertEqual(flag_result.variant, "control")
+
+        # Error should still be tracked with status code
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": "control",
+                "locally_evaluated": False,
+                "$feature/my-flag": "control",
+                "$feature_flag_error": FeatureFlagError.api_error(503),
+            },
+            groups={},
+            disable_geoip=None,
+        )
+
+    @mock.patch("posthog.client.flags")
+    @mock.patch.object(Client, "capture")
+    def test_error_without_cache_returns_none(self, patch_capture, patch_flags):
+        """Test that errors return None when no stale cache is available."""
+        from posthog.request import RequestsTimeout
+
+        # Do NOT populate cache - no fallback available
+
+        patch_flags.side_effect = RequestsTimeout("Request timed out")
+
+        flag_result = self.client.get_feature_flag_result("my-flag", "some-distinct-id")
+
+        # Should return None since no cache available
+        self.assertIsNone(flag_result)
+
+        # Error should still be tracked
+        patch_capture.assert_called_with(
+            "$feature_flag_called",
+            distinct_id="some-distinct-id",
+            properties={
+                "$feature_flag": "my-flag",
+                "$feature_flag_response": None,
+                "locally_evaluated": False,
+                "$feature/my-flag": None,
+                "$feature_flag_error": FeatureFlagError.TIMEOUT,
             },
             groups={},
             disable_geoip=None,

posthog/test/test_flag_definition_cache.py

@@ -0,0 +1,612 @@
+"""
+Tests for FlagDefinitionCacheProvider functionality.
+
+These tests follow the patterns from the TypeScript implementation in posthog-js/packages/node.
+"""
+
+import threading
+import unittest
+from typing import Optional
+from unittest import mock
+
+from posthog.client import Client
+from posthog.flag_definition_cache import (
+    FlagDefinitionCacheData,
+    FlagDefinitionCacheProvider,
+)
+from posthog.request import GetResponse
+from posthog.test.test_utils import FAKE_TEST_API_KEY
+
+
+class MockCacheProvider:
+    """A mock implementation of FlagDefinitionCacheProvider for testing."""
+
+    def __init__(self):
+        self.stored_data: Optional[FlagDefinitionCacheData] = None
+        self.should_fetch_return_value = True
+        self.get_call_count = 0
+        self.should_fetch_call_count = 0
+        self.on_received_call_count = 0
+        self.shutdown_call_count = 0
+        self.should_fetch_error: Optional[Exception] = None
+        self.get_error: Optional[Exception] = None
+        self.on_received_error: Optional[Exception] = None
+        self.shutdown_error: Optional[Exception] = None
+
+    def get_flag_definitions(self) -> Optional[FlagDefinitionCacheData]:
+        self.get_call_count += 1
+        if self.get_error:
+            raise self.get_error
+        return self.stored_data
+
+    def should_fetch_flag_definitions(self) -> bool:
+        self.should_fetch_call_count += 1
+        if self.should_fetch_error:
+            raise self.should_fetch_error
+        return self.should_fetch_return_value
+
+    def on_flag_definitions_received(self, data: FlagDefinitionCacheData) -> None:
+        self.on_received_call_count += 1
+        if self.on_received_error:
+            raise self.on_received_error
+        self.stored_data = data
+
+    def shutdown(self) -> None:
+        self.shutdown_call_count += 1
+        if self.shutdown_error:
+            raise self.shutdown_error
+
+
+class TestFlagDefinitionCacheProvider(unittest.TestCase):
+    """Tests for the FlagDefinitionCacheProvider protocol."""
+
+    @classmethod
+    def setUpClass(cls):
+        # Prevent real HTTP requests
+        cls.client_post_patcher = mock.patch("posthog.client.batch_post")
+        cls.consumer_post_patcher = mock.patch("posthog.consumer.batch_post")
+        cls.client_post_patcher.start()
+        cls.consumer_post_patcher.start()
+
+    @classmethod
+    def tearDownClass(cls):
+        cls.client_post_patcher.stop()
+        cls.consumer_post_patcher.stop()
+
+    def setUp(self):
+        self.cache_provider = MockCacheProvider()
+        self.sample_flags_data: FlagDefinitionCacheData = {
+            "flags": [
+                {"key": "test-flag", "active": True, "filters": {}},
+                {"key": "another-flag", "active": False, "filters": {}},
+            ],
+            "group_type_mapping": {"0": "company", "1": "project"},
+            "cohorts": {"1": {"properties": []}},
+        }
+
+    def tearDown(self):
+        # Ensure client cleanup
+        pass
+
+    def _create_client_with_cache(self) -> Client:
+        """Create a client with the mock cache provider."""
+        return Client(
+            FAKE_TEST_API_KEY,
+            personal_api_key="test-personal-key",
+            flag_definition_cache_provider=self.cache_provider,
+            sync_mode=True,
+            enable_local_evaluation=False,  # Disable poller for tests
+        )
+
+
+class TestCacheInitialization(TestFlagDefinitionCacheProvider):
+    """Tests for cache initialization behavior."""
+
+    @mock.patch("posthog.client.get")
+    def test_uses_cached_data_when_should_fetch_returns_false(self, mock_get):
+        """When should_fetch returns False and cache has data, use cached data."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = self.sample_flags_data
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should not call API
+        mock_get.assert_not_called()
+
+        # Should have called cache methods
+        self.assertEqual(self.cache_provider.should_fetch_call_count, 1)
+        self.assertEqual(self.cache_provider.get_call_count, 1)
+
+        # Flags should be loaded from cache
+        self.assertEqual(len(client.feature_flags), 2)
+        self.assertEqual(client.feature_flags[0]["key"], "test-flag")
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_fetches_from_api_when_should_fetch_returns_true(self, mock_get):
+        """When should_fetch returns True, fetch from API."""
+        self.cache_provider.should_fetch_return_value = True
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should call API
+        mock_get.assert_called_once()
+
+        # Should have called should_fetch but not get
+        self.assertEqual(self.cache_provider.should_fetch_call_count, 1)
+        self.assertEqual(self.cache_provider.get_call_count, 0)
+
+        # Should have called on_received to store in cache
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_emergency_fallback_when_cache_empty_and_no_flags(self, mock_get):
+        """When should_fetch=False but cache is empty and no flags loaded, fetch anyway."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = None  # Empty cache
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should call API due to emergency fallback
+        mock_get.assert_called_once()
+
+        # Should have called on_received
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_preserves_existing_flags_when_cache_returns_none(self, mock_get):
+        """When cache returns None but client has flags, preserve existing flags."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = None  # Empty cache
+
+        client = self._create_client_with_cache()
+
+        # Pre-load flags (simulating a previous successful fetch)
+        client.feature_flags = self.sample_flags_data["flags"]
+        client.group_type_mapping = self.sample_flags_data["group_type_mapping"]
+        client.cohorts = self.sample_flags_data["cohorts"]
+
+        client._load_feature_flags()
+
+        # Should NOT call API since we already have flags
+        mock_get.assert_not_called()
+
+        # Existing flags should be preserved
+        self.assertEqual(len(client.feature_flags), 2)
+        self.assertEqual(client.feature_flags[0]["key"], "test-flag")
+
+        client.join()
+
+
+class TestFetchCoordination(TestFlagDefinitionCacheProvider):
+    """Tests for fetch coordination between workers."""
+
+    @mock.patch("posthog.client.get")
+    def test_calls_should_fetch_before_each_poll(self, mock_get):
+        """should_fetch_flag_definitions is called before each poll cycle."""
+        self.cache_provider.should_fetch_return_value = True
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+
+        # First poll
+        client._load_feature_flags()
+        self.assertEqual(self.cache_provider.should_fetch_call_count, 1)
+
+        # Second poll
+        client._load_feature_flags()
+        self.assertEqual(self.cache_provider.should_fetch_call_count, 2)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_does_not_call_on_received_when_fetch_skipped(self, mock_get):
+        """on_flag_definitions_received is NOT called when fetch is skipped."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = self.sample_flags_data
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should not call on_received since we didn't fetch
+        self.assertEqual(self.cache_provider.on_received_call_count, 0)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_stores_data_in_cache_after_api_fetch(self, mock_get):
+        """on_flag_definitions_received receives the fetched data."""
+        self.cache_provider.should_fetch_return_value = True
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should have stored data in cache
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+        self.assertIsNotNone(self.cache_provider.stored_data)
+        self.assertEqual(len(self.cache_provider.stored_data["flags"]), 2)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_304_not_modified_does_not_update_cache(self, mock_get):
+        """When API returns 304 Not Modified, cache should not be updated."""
+        self.cache_provider.should_fetch_return_value = True
+
+        # First fetch to populate flags and ETag
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Verify initial fetch worked
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+        self.assertEqual(len(client.feature_flags), 2)
+
+        # Second fetch returns 304 Not Modified
+        mock_get.return_value = GetResponse(
+            data=None, etag="test-etag", not_modified=True
+        )
+
+        client._load_feature_flags()
+
+        # API was called twice
+        self.assertEqual(mock_get.call_count, 2)
+
+        # should_fetch was called twice
+        self.assertEqual(self.cache_provider.should_fetch_call_count, 2)
+
+        # on_received should NOT be called again (304 = no new data)
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+
+        # Flags should still be present
+        self.assertEqual(len(client.feature_flags), 2)
+
+        client.join()
+
+
+class TestErrorHandling(TestFlagDefinitionCacheProvider):
+    """Tests for error handling in cache provider operations."""
+
+    @mock.patch("posthog.client.get")
+    def test_should_fetch_error_defaults_to_fetching(self, mock_get):
+        """When should_fetch throws an error, default to fetching from API."""
+        self.cache_provider.should_fetch_error = Exception("Lock acquisition failed")
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should still fetch from API
+        mock_get.assert_called_once()
+
+        # Flags should be loaded
+        self.assertEqual(len(client.feature_flags), 2)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_get_error_falls_back_to_api_fetch(self, mock_get):
+        """When get_flag_definitions throws an error, fetch from API."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.get_error = Exception("Cache read failed")
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should fall back to API
+        mock_get.assert_called_once()
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_on_received_error_keeps_flags_in_memory(self, mock_get):
+        """When on_flag_definitions_received throws, flags are still in memory."""
+        self.cache_provider.should_fetch_return_value = True
+        self.cache_provider.on_received_error = Exception("Cache write failed")
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Flags should still be loaded in memory despite cache error
+        self.assertEqual(len(client.feature_flags), 2)
+        self.assertEqual(client.feature_flags[0]["key"], "test-flag")
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_shutdown_error_is_logged_but_continues(self, mock_get):
+        """When shutdown throws an error, it's logged but shutdown continues."""
+        self.cache_provider.shutdown_error = Exception("Lock release failed")
+
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Should not raise when joining
+        client.join()
+
+        # Shutdown was called
+        self.assertEqual(self.cache_provider.shutdown_call_count, 1)
+
+
+class TestShutdownLifecycle(TestFlagDefinitionCacheProvider):
+    """Tests for shutdown lifecycle."""
+
+    @mock.patch("posthog.client.get")
+    def test_shutdown_calls_cache_provider_shutdown(self, mock_get):
+        """Client shutdown calls cache provider shutdown."""
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Shutdown
+        client.join()
+
+        self.assertEqual(self.cache_provider.shutdown_call_count, 1)
+
+    @mock.patch("posthog.client.get")
+    def test_shutdown_called_even_without_fetching(self, mock_get):
+        """Shutdown is called even when cache was used instead of fetching."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = self.sample_flags_data
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+        client.join()
+
+        # Shutdown should still be called
+        self.assertEqual(self.cache_provider.shutdown_call_count, 1)
+
+    @mock.patch("posthog.client.get")
+    def test_multiple_join_calls_only_shutdown_once(self, mock_get):
+        """Calling join() multiple times should only call cache provider shutdown once."""
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Call join multiple times
+        client.join()
+        client.join()
+        client.join()
+
+        # Shutdown should be called each time (current behavior - no guard)
+        # This test documents the current behavior
+        self.assertGreaterEqual(self.cache_provider.shutdown_call_count, 1)
+
+
+class TestBackwardCompatibility(TestFlagDefinitionCacheProvider):
+    """Tests for backward compatibility without cache provider."""
+
+    @mock.patch("posthog.client.get")
+    def test_works_without_cache_provider(self, mock_get):
+        """Client works normally without a cache provider configured."""
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        # Create client without cache provider
+        client = Client(
+            FAKE_TEST_API_KEY,
+            personal_api_key="test-personal-key",
+            sync_mode=True,
+            enable_local_evaluation=False,
+        )
+        client._load_feature_flags()
+
+        # Should fetch from API
+        mock_get.assert_called_once()
+
+        # Flags should be loaded
+        self.assertEqual(len(client.feature_flags), 2)
+
+        client.join()
+
+
+class TestDataIntegrity(TestFlagDefinitionCacheProvider):
+    """Tests for data integrity between cache and client state."""
+
+    @mock.patch("posthog.client.get")
+    def test_cached_flags_available_for_evaluation(self, mock_get):
+        """Flags loaded from cache are available for local evaluation."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = {
+            "flags": [
+                {
+                    "key": "test-flag",
+                    "active": True,
+                    "filters": {
+                        "groups": [
+                            {
+                                "properties": [],
+                                "rollout_percentage": 100,
+                            }
+                        ]
+                    },
+                }
+            ],
+            "group_type_mapping": {},
+            "cohorts": {},
+        }
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        # Flag should be accessible
+        self.assertEqual(len(client.feature_flags), 1)
+        self.assertEqual(client.feature_flags_by_key["test-flag"]["key"], "test-flag")
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_group_type_mapping_loaded_from_cache(self, mock_get):
+        """Group type mapping is correctly loaded from cache."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = self.sample_flags_data
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        self.assertEqual(client.group_type_mapping["0"], "company")
+        self.assertEqual(client.group_type_mapping["1"], "project")
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_cohorts_loaded_from_cache(self, mock_get):
+        """Cohorts are correctly loaded from cache."""
+        self.cache_provider.should_fetch_return_value = False
+        self.cache_provider.stored_data = self.sample_flags_data
+
+        client = self._create_client_with_cache()
+        client._load_feature_flags()
+
+        self.assertIn("1", client.cohorts)
+
+        client.join()
+
+    @mock.patch("posthog.client.get")
+    def test_cache_updated_when_api_returns_new_data(self, mock_get):
+        """State transition: cache has old data -> API returns new -> cache updated."""
+        # Start with old cached data
+        old_flags_data: FlagDefinitionCacheData = {
+            "flags": [{"key": "old-flag", "active": True, "filters": {}}],
+            "group_type_mapping": {},
+            "cohorts": {},
+        }
+        self.cache_provider.stored_data = old_flags_data
+        self.cache_provider.should_fetch_return_value = False
+
+        client = self._create_client_with_cache()
+
+        # First load from cache
+        client._load_feature_flags()
+        self.assertEqual(client.feature_flags[0]["key"], "old-flag")
+        self.assertEqual(self.cache_provider.on_received_call_count, 0)
+
+        # Now trigger API fetch with new data
+        self.cache_provider.should_fetch_return_value = True
+        new_flags_data: FlagDefinitionCacheData = {
+            "flags": [{"key": "new-flag", "active": True, "filters": {}}],
+            "group_type_mapping": {"0": "company"},
+            "cohorts": {"1": {"properties": []}},
+        }
+        mock_get.return_value = GetResponse(
+            data=new_flags_data, etag="new-etag", not_modified=False
+        )
+
+        client._load_feature_flags()
+
+        # Verify new flags loaded
+        self.assertEqual(client.feature_flags[0]["key"], "new-flag")
+        self.assertEqual(client.group_type_mapping["0"], "company")
+
+        # Verify cache was updated
+        self.assertEqual(self.cache_provider.on_received_call_count, 1)
+        self.assertEqual(self.cache_provider.stored_data["flags"][0]["key"], "new-flag")
+
+        client.join()
+
+
+class TestConcurrency(TestFlagDefinitionCacheProvider):
+    """Tests for thread safety and concurrent access."""
+
+    @mock.patch("posthog.client.get")
+    def test_concurrent_load_feature_flags_is_thread_safe(self, mock_get):
+        """Multiple threads calling _load_feature_flags should not cause errors."""
+        mock_get.return_value = GetResponse(
+            data=self.sample_flags_data, etag="test-etag", not_modified=False
+        )
+
+        client = self._create_client_with_cache()
+        errors = []
+
+        def load_flags():
+            try:
+                client._load_feature_flags()
+            except Exception as e:
+                errors.append(e)
+
+        # Launch 5 threads concurrently
+        threads = [threading.Thread(target=load_flags) for _ in range(5)]
+        for t in threads:
+            t.start()
+        for t in threads:
+            t.join()
+
+        # Should complete without errors
+        self.assertEqual(len(errors), 0, f"Unexpected errors: {errors}")
+
+        # Flags should be loaded
+        self.assertIsNotNone(client.feature_flags)
+        self.assertEqual(len(client.feature_flags), 2)
+
+        client.join()
+
+
+class TestProtocolCompliance(unittest.TestCase):
+    """Tests for Protocol compliance."""
+
+    def test_mock_provider_is_protocol_instance(self):
+        """MockCacheProvider satisfies FlagDefinitionCacheProvider protocol."""
+        provider = MockCacheProvider()
+        self.assertIsInstance(provider, FlagDefinitionCacheProvider)
+
+    def test_incomplete_provider_is_not_protocol_instance(self):
+        """Class missing methods is not a FlagDefinitionCacheProvider."""
+
+        class IncompleteProvider:
+            def get_flag_definitions(self):
+                return None
+
+        provider = IncompleteProvider()
+        self.assertNotIsInstance(provider, FlagDefinitionCacheProvider)
+
+
+if __name__ == "__main__":
+    unittest.main()

posthog/test/test_module.py

@@ -7,8 +7,7 @@ class TestModule(unittest.TestCase):
     posthog = None
 
     def _assert_enqueue_result(self, result):
-        self.assertEqual(type(result[0]), bool)
-        self.assertEqual(type(result[1]), dict)
+        self.assertEqual(type(result[0]), str)
 
     def failed(self):
         self.failed = True
@@ -19,21 +18,8 @@ class TestModule(unittest.TestCase):
             "testsecret", host="http://localhost:8000", on_error=self.failed
         )
 
-    def test_no_api_key(self):
-        self.posthog.api_key = None
-        self.assertRaises(Exception, self.posthog.capture)
-
-    def test_no_host(self):
-        self.posthog.host = None
-        self.assertRaises(Exception, self.posthog.capture)
-
     def test_track(self):
-        res = self.posthog.capture("distinct_id", "python module event")
-        self._assert_enqueue_result(res)
-        self.posthog.flush()
-
-    def test_identify(self):
-        res = self.posthog.identify("distinct_id", {"email": "user@email.com"})
+        res = self.posthog.capture("python module event", distinct_id="distinct_id")
         self._assert_enqueue_result(res)
         self.posthog.flush()
 
@@ -42,9 +28,5 @@ class TestModule(unittest.TestCase):
         self._assert_enqueue_result(res)
         self.posthog.flush()
 
-    def test_page(self):
-        self.posthog.page("distinct_id", "https://posthog.com/contact")
-        self.posthog.flush()
-
     def test_flush(self):
         self.posthog.flush()

posthog/test/test_request.py

@@ -6,16 +6,60 @@ import mock
 import pytest
 import requests
 
+import posthog.request as request_module
 from posthog.request import (
+    APIError,
     DatetimeSerializer,
+    GetResponse,
+    KEEP_ALIVE_SOCKET_OPTIONS,
     QuotaLimitError,
+    _mask_tokens_in_url,
     batch_post,
     decide,
     determine_server_host,
+    disable_connection_reuse,
+    enable_keep_alive,
+    flags,
+    get,
+    set_socket_options,
 )
 from posthog.test.test_utils import TEST_API_KEY
 
 
+@pytest.mark.parametrize(
+    "url, expected",
+    [
+        # Token with params after - masks keeping first 10 chars
+        (
+            "https://example.com/api/flags?token=phc_abc123xyz789&send_cohorts",
+            "https://example.com/api/flags?token=phc_abc123...&send_cohorts",
+        ),
+        # Token at end of URL
+        (
+            "https://example.com/api/flags?token=phc_abc123xyz789",
+            "https://example.com/api/flags?token=phc_abc123...",
+        ),
+        # No token - unchanged
+        (
+            "https://example.com/api/flags?other=value",
+            "https://example.com/api/flags?other=value",
+        ),
+        # Short token (<10 chars) - unchanged
+        (
+            "https://example.com/api/flags?token=short",
+            "https://example.com/api/flags?token=short",
+        ),
+        # Exactly 10 char token - gets ellipsis
+        (
+            "https://example.com/api/flags?token=1234567890",
+            "https://example.com/api/flags?token=1234567890...",
+        ),
+    ],
+)
+def test_mask_tokens_in_url(url, expected):
+    assert _mask_tokens_in_url(url) == expected
+
+
 class TestRequests(unittest.TestCase):
     def test_valid_request(self):
         res = batch_post(
@@ -107,6 +151,184 @@ class TestRequests(unittest.TestCase):
             self.assertEqual(response["featureFlags"], {"flag1": True})
 
 
+class TestGet(unittest.TestCase):
+    """Unit tests for the get() function HTTP-level behavior."""
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_returns_data_and_etag(self, mock_get):
+        """Test that get() returns GetResponse with data and etag from headers."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response.headers["ETag"] = '"abc123"'
+        mock_response._content = json.dumps({"flags": [{"key": "test-flag"}]}).encode(
+            "utf-8"
+        )
+        mock_get.return_value = mock_response
+
+        response = get("api_key", "/test-url", host="https://example.com")
+
+        self.assertIsInstance(response, GetResponse)
+        self.assertEqual(response.data, {"flags": [{"key": "test-flag"}]})
+        self.assertEqual(response.etag, '"abc123"')
+        self.assertFalse(response.not_modified)
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_sends_if_none_match_header_when_etag_provided(self, mock_get):
+        """Test that If-None-Match header is sent when etag parameter is provided."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response.headers["ETag"] = '"new-etag"'
+        mock_response._content = json.dumps({"flags": []}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/test-url", host="https://example.com", etag='"previous-etag"')
+
+        call_kwargs = mock_get.call_args[1]
+        self.assertEqual(call_kwargs["headers"]["If-None-Match"], '"previous-etag"')
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_does_not_send_if_none_match_when_no_etag(self, mock_get):
+        """Test that If-None-Match header is not sent when no etag provided."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({"flags": []}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/test-url", host="https://example.com")
+
+        call_kwargs = mock_get.call_args[1]
+        self.assertNotIn("If-None-Match", call_kwargs["headers"])
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_handles_304_not_modified(self, mock_get):
+        """Test that 304 Not Modified response returns not_modified=True with no data."""
+        mock_response = requests.Response()
+        mock_response.status_code = 304
+        mock_response.headers["ETag"] = '"unchanged-etag"'
+        mock_get.return_value = mock_response
+
+        response = get(
+            "api_key", "/test-url", host="https://example.com", etag='"unchanged-etag"'
+        )
+
+        self.assertIsInstance(response, GetResponse)
+        self.assertIsNone(response.data)
+        self.assertEqual(response.etag, '"unchanged-etag"')
+        self.assertTrue(response.not_modified)
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_304_without_etag_header_uses_request_etag(self, mock_get):
+        """Test that 304 response without ETag header falls back to request etag."""
+        mock_response = requests.Response()
+        mock_response.status_code = 304
+        # Server doesn't return ETag header on 304
+        mock_get.return_value = mock_response
+
+        response = get(
+            "api_key", "/test-url", host="https://example.com", etag='"original-etag"'
+        )
+
+        self.assertTrue(response.not_modified)
+        self.assertEqual(response.etag, '"original-etag"')
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_200_without_etag_header(self, mock_get):
+        """Test that 200 response without ETag header returns None for etag."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({"flags": []}).encode("utf-8")
+        # No ETag header
+        mock_get.return_value = mock_response
+
+        response = get("api_key", "/test-url", host="https://example.com")
+
+        self.assertFalse(response.not_modified)
+        self.assertIsNone(response.etag)
+        self.assertEqual(response.data, {"flags": []})
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_error_response_raises_api_error(self, mock_get):
+        """Test that error responses raise APIError."""
+        mock_response = requests.Response()
+        mock_response.status_code = 401
+        mock_response._content = json.dumps({"detail": "Unauthorized"}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        with self.assertRaises(APIError) as ctx:
+            get("bad_key", "/test-url", host="https://example.com")
+
+        self.assertEqual(ctx.exception.status, 401)
+        self.assertEqual(ctx.exception.message, "Unauthorized")
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_sends_authorization_header(self, mock_get):
+        """Test that Authorization header is sent with Bearer token."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("my-api-key", "/test-url", host="https://example.com")
+
+        call_kwargs = mock_get.call_args[1]
+        self.assertEqual(call_kwargs["headers"]["Authorization"], "Bearer my-api-key")
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_sends_user_agent_header(self, mock_get):
+        """Test that User-Agent header is sent."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/test-url", host="https://example.com")
+
+        call_kwargs = mock_get.call_args[1]
+        self.assertIn("User-Agent", call_kwargs["headers"])
+        self.assertTrue(
+            call_kwargs["headers"]["User-Agent"].startswith("posthog-python/")
+        )
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_passes_timeout(self, mock_get):
+        """Test that timeout parameter is passed to the request."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/test-url", host="https://example.com", timeout=30)
+
+        call_kwargs = mock_get.call_args[1]
+        self.assertEqual(call_kwargs["timeout"], 30)
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_constructs_full_url(self, mock_get):
+        """Test that host and url are combined correctly."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/api/flags", host="https://example.com")
+
+        call_args = mock_get.call_args[0]
+        self.assertEqual(call_args[0], "https://example.com/api/flags")
+
+    @mock.patch("posthog.request._session.get")
+    def test_get_removes_trailing_slash_from_host(self, mock_get):
+        """Test that trailing slash is removed from host."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps({}).encode("utf-8")
+        mock_get.return_value = mock_response
+
+        get("api_key", "/api/flags", host="https://example.com/")
+
+        call_args = mock_get.call_args[0]
+        self.assertEqual(call_args[0], "https://example.com/api/flags")
+
+
 @pytest.mark.parametrize(
     "host, expected",
     [
@@ -128,3 +350,317 @@ class TestRequests(unittest.TestCase):
 )
 def test_routing_to_custom_host(host, expected):
     assert determine_server_host(host) == expected
+
+
+def test_enable_keep_alive_sets_socket_options():
+    try:
+        enable_keep_alive()
+        from posthog.request import _session
+
+        adapter = _session.get_adapter("https://example.com")
+        assert adapter.socket_options == KEEP_ALIVE_SOCKET_OPTIONS
+    finally:
+        set_socket_options(None)
+
+
+def test_set_socket_options_clears_with_none():
+    try:
+        enable_keep_alive()
+        set_socket_options(None)
+        from posthog.request import _session
+
+        adapter = _session.get_adapter("https://example.com")
+        assert adapter.socket_options is None
+    finally:
+        set_socket_options(None)
+
+
+def test_disable_connection_reuse_creates_fresh_sessions():
+    try:
+        disable_connection_reuse()
+        session1 = request_module._get_session()
+        session2 = request_module._get_session()
+        assert session1 is not session2
+    finally:
+        request_module._pooling_enabled = True
+
+
+def test_set_socket_options_is_idempotent():
+    try:
+        enable_keep_alive()
+        session1 = request_module._session
+        enable_keep_alive()
+        session2 = request_module._session
+        assert session1 is session2
+    finally:
+        set_socket_options(None)
+
+
+class TestFlagsSession(unittest.TestCase):
+    """Tests for flags session configuration."""
+
+    def test_retry_status_forcelist_excludes_rate_limits(self):
+        """Verify 429 (rate limit) is NOT retried - need to wait, not hammer."""
+        from posthog.request import RETRY_STATUS_FORCELIST
+
+        self.assertNotIn(429, RETRY_STATUS_FORCELIST)
+
+    def test_retry_status_forcelist_excludes_quota_errors(self):
+        """Verify 402 (payment required/quota) is NOT retried - won't resolve."""
+        from posthog.request import RETRY_STATUS_FORCELIST
+
+        self.assertNotIn(402, RETRY_STATUS_FORCELIST)
+
+    @mock.patch("posthog.request._get_flags_session")
+    def test_flags_uses_flags_session(self, mock_get_flags_session):
+        """flags() uses the dedicated flags session, not the general session."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps(
+            {
+                "featureFlags": {"test-flag": True},
+                "featureFlagPayloads": {},
+                "errorsWhileComputingFlags": False,
+            }
+        ).encode("utf-8")
+
+        mock_session = mock.MagicMock()
+        mock_session.post.return_value = mock_response
+        mock_get_flags_session.return_value = mock_session
+
+        result = flags("test-key", "https://test.posthog.com", distinct_id="user123")
+
+        self.assertEqual(result["featureFlags"]["test-flag"], True)
+        mock_get_flags_session.assert_called_once()
+        mock_session.post.assert_called_once()
+
+    @mock.patch("posthog.request._get_flags_session")
+    def test_flags_no_retry_on_quota_limit(self, mock_get_flags_session):
+        """flags() raises QuotaLimitError without retrying (at application level)."""
+        mock_response = requests.Response()
+        mock_response.status_code = 200
+        mock_response._content = json.dumps(
+            {
+                "quotaLimited": ["feature_flags"],
+                "featureFlags": {},
+                "featureFlagPayloads": {},
+                "errorsWhileComputingFlags": False,
+            }
+        ).encode("utf-8")
+
+        mock_session = mock.MagicMock()
+        mock_session.post.return_value = mock_response
+        mock_get_flags_session.return_value = mock_session
+
+        with self.assertRaises(QuotaLimitError):
+            flags("test-key", "https://test.posthog.com", distinct_id="user123")
+
+        # QuotaLimitError is raised after response is received, not retried
+        self.assertEqual(mock_session.post.call_count, 1)
+
+
+class TestFlagsSessionNetworkRetries(unittest.TestCase):
+    """Tests for network failure retries in the flags session."""
+
+    def test_flags_session_retry_config_includes_connection_errors(self):
+        """
+        Verify that the flags session is configured to retry on connection errors.
+
+        The urllib3 Retry adapter with connect=2 and read=2 automatically
+        retries on network-level failures (DNS failures, connection refused,
+        connection reset, etc.) up to 2 times each.
+        """
+        from posthog.request import _build_flags_session
+
+        session = _build_flags_session()
+
+        # Get the adapter for https://
+        adapter = session.get_adapter("https://test.posthog.com")
+
+        # Verify retry configuration
+        retry = adapter.max_retries
+        self.assertEqual(retry.total, 2, "Should have 2 total retries")
+        self.assertEqual(retry.connect, 2, "Should retry connection errors twice")
+        self.assertEqual(retry.read, 2, "Should retry read errors twice")
+        self.assertIn("POST", retry.allowed_methods, "Should allow POST retries")
+
+    def test_flags_session_retries_on_server_errors(self):
+        """
+        Verify that transient server errors (5xx) trigger retries.
+
+        This tests the status_forcelist configuration which specifies
+        which HTTP status codes should trigger a retry.
+        """
+        from posthog.request import _build_flags_session, RETRY_STATUS_FORCELIST
+
+        session = _build_flags_session()
+        adapter = session.get_adapter("https://test.posthog.com")
+        retry = adapter.max_retries
+
+        # Verify the status codes that trigger retries
+        self.assertEqual(
+            set(retry.status_forcelist),
+            set(RETRY_STATUS_FORCELIST),
+            "Should retry on transient server errors",
+        )
+
+        # Verify specific codes are included
+        self.assertIn(500, retry.status_forcelist)
+        self.assertIn(502, retry.status_forcelist)
+        self.assertIn(503, retry.status_forcelist)
+        self.assertIn(504, retry.status_forcelist)
+
+        # Verify rate limits and quota errors are NOT retried
+        self.assertNotIn(429, retry.status_forcelist)
+        self.assertNotIn(402, retry.status_forcelist)
+
+    def test_flags_session_has_backoff(self):
+        """
+        Verify that retries use exponential backoff to avoid thundering herd.
+        """
+        from posthog.request import _build_flags_session
+
+        session = _build_flags_session()
+        adapter = session.get_adapter("https://test.posthog.com")
+        retry = adapter.max_retries
+
+        self.assertEqual(
+            retry.backoff_factor,
+            0.5,
+            "Should use 0.5s backoff factor (0.5s, 1s delays)",
+        )
+
+
+class TestFlagsSessionRetryIntegration(unittest.TestCase):
+    """Integration tests that verify actual retry behavior with a local server."""
+
+    def test_retries_on_503_then_succeeds(self):
+        """
+        Verify that 503 errors trigger retries and eventually succeed.
+
+        Uses a local HTTP server that fails twice with 503, then succeeds.
+        This tests the full retry flow including backoff timing.
+        """
+        import threading
+        from http.server import HTTPServer, BaseHTTPRequestHandler
+        from socketserver import ThreadingMixIn
+        from urllib3.util.retry import Retry
+        from posthog.request import HTTPAdapterWithSocketOptions, RETRY_STATUS_FORCELIST
+
+        request_count = 0
+
+        class RetryTestHandler(BaseHTTPRequestHandler):
+            protocol_version = "HTTP/1.1"
+
+            def do_POST(self):
+                nonlocal request_count
+                request_count += 1
+
+                # Read and discard request body to prevent connection issues
+                content_length = int(self.headers.get("Content-Length", 0))
+                if content_length > 0:
+                    self.rfile.read(content_length)
+
+                if request_count <= 2:
+                    self.send_response(503)
+                    self.send_header("Content-Type", "application/json")
+                    body = b'{"error": "Service unavailable"}'
+                    self.send_header("Content-Length", str(len(body)))
+                    self.end_headers()
+                    self.wfile.write(body)
+                else:
+                    self.send_response(200)
+                    self.send_header("Content-Type", "application/json")
+                    body = (
+                        b'{"featureFlags": {"test": true}, "featureFlagPayloads": {}}'
+                    )
+                    self.send_header("Content-Length", str(len(body)))
+                    self.end_headers()
+                    self.wfile.write(body)
+
+            def log_message(self, format, *args):
+                pass  # Suppress logging
+
+        # Use ThreadingMixIn for cleaner shutdown
+        class ThreadedHTTPServer(ThreadingMixIn, HTTPServer):
+            daemon_threads = True
+
+        # Start server on a random available port
+        server = ThreadedHTTPServer(("127.0.0.1", 0), RetryTestHandler)
+        port = server.server_address[1]
+        server_thread = threading.Thread(target=server.serve_forever)
+        server_thread.daemon = True
+        server_thread.start()
+
+        try:
+            # Build session with same retry config as _build_flags_session
+            # but mounted on http:// for local testing
+            adapter = HTTPAdapterWithSocketOptions(
+                max_retries=Retry(
+                    total=2,
+                    connect=2,
+                    read=2,
+                    backoff_factor=0.01,  # Fast backoff for testing
+                    status_forcelist=RETRY_STATUS_FORCELIST,
+                    allowed_methods=["POST"],
+                ),
+            )
+            session = requests.Session()
+            session.mount("http://", adapter)
+
+            response = session.post(
+                f"http://127.0.0.1:{port}/flags/?v=2",
+                json={"distinct_id": "user123"},
+                timeout=5,
+            )
+
+            # Should succeed on 3rd attempt
+            self.assertEqual(response.status_code, 200)
+            self.assertEqual(request_count, 3)  # 1 initial + 2 retries
+        finally:
+            server.shutdown()
+            server.server_close()
+
+    def test_connection_errors_are_retried(self):
+        """
+        Verify that connection errors (no server) trigger retries.
+
+        Binds a socket to get a guaranteed available port, then closes it
+        so connection attempts fail with ConnectionError.
+        """
+        import socket
+        import time
+        from urllib3.util.retry import Retry
+        from posthog.request import HTTPAdapterWithSocketOptions, RETRY_STATUS_FORCELIST
+
+        # Get an available port by binding then closing a socket
+        sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        sock.bind(("127.0.0.1", 0))
+        port = sock.getsockname()[1]
+        sock.close()  # Port is now available but nothing is listening
+
+        adapter = HTTPAdapterWithSocketOptions(
+            max_retries=Retry(
+                total=2,
+                connect=2,
+                read=2,
+                backoff_factor=0.05,  # Very fast for testing
+                status_forcelist=RETRY_STATUS_FORCELIST,
+                allowed_methods=["POST"],
+            ),
+        )
+        session = requests.Session()
+        session.mount("http://", adapter)
+
+        start = time.time()
+        with self.assertRaises(requests.exceptions.ConnectionError):
+            session.post(
+                f"http://127.0.0.1:{port}/flags/?v=2",
+                json={"distinct_id": "user123"},
+                timeout=1,
+            )
+        elapsed = time.time() - start
+
+        # With 3 attempts and backoff, should take more than instant
+        # but less than timeout (confirms retries happened)
+        self.assertGreater(elapsed, 0.05, "Should have some delay from retries")

posthog/test/test_utils.py

@@ -1,3 +1,5 @@
+import sys
+import time
 import unittest
 from dataclasses import dataclass
 from datetime import date, datetime, timedelta
@@ -12,6 +14,7 @@ from pydantic import BaseModel
 from pydantic.v1 import BaseModel as BaseModelV1
 
 from posthog import utils
+from posthog.types import FeatureFlagResult
 
 TEST_API_KEY = "kOOlRy2QlMY9jHZQv0bKz0FZyazBUoY8Arj0lFVNjs4"
 FAKE_TEST_API_KEY = "random_key"
@@ -120,7 +123,9 @@ class TestUtils(unittest.TestCase):
             "bar": 2,
             "baz": None,
         }
-        assert utils.clean(ModelV1(foo=1, bar="2")) == {"foo": 1, "bar": "2"}
+        # Pydantic V1 is not compatible with Python 3.14+
+        if sys.version_info < (3, 14):
+            assert utils.clean(ModelV1(foo=1, bar="2")) == {"foo": 1, "bar": "2"}
         assert utils.clean(NestedModel(foo=ModelV2(foo="1", bar=2, baz="3"))) == {
             "foo": {"foo": "1", "bar": 2, "baz": "3"}
         }
@@ -173,3 +178,124 @@ class TestUtils(unittest.TestCase):
                 "inner_optional": None,
             },
         }
+
+
+class TestFlagCache(unittest.TestCase):
+    def setUp(self):
+        self.cache = utils.FlagCache(max_size=3, default_ttl=1)
+        self.flag_result = FeatureFlagResult.from_value_and_payload(
+            "test-flag", True, None
+        )
+
+    def test_cache_basic_operations(self):
+        distinct_id = "user123"
+        flag_key = "test-flag"
+        flag_version = 1
+
+        # Test cache miss
+        result = self.cache.get_cached_flag(distinct_id, flag_key, flag_version)
+        assert result is None
+
+        # Test cache set and hit
+        self.cache.set_cached_flag(
+            distinct_id, flag_key, self.flag_result, flag_version
+        )
+        result = self.cache.get_cached_flag(distinct_id, flag_key, flag_version)
+        assert result is not None
+        assert result.get_value()
+
+    def test_cache_ttl_expiration(self):
+        distinct_id = "user123"
+        flag_key = "test-flag"
+        flag_version = 1
+
+        # Set flag in cache
+        self.cache.set_cached_flag(
+            distinct_id, flag_key, self.flag_result, flag_version
+        )
+
+        # Should be available immediately
+        result = self.cache.get_cached_flag(distinct_id, flag_key, flag_version)
+        assert result is not None
+
+        # Wait for TTL to expire (1 second + buffer)
+        time.sleep(1.1)
+
+        # Should be expired
+        result = self.cache.get_cached_flag(distinct_id, flag_key, flag_version)
+        assert result is None
+
+    def test_cache_version_invalidation(self):
+        distinct_id = "user123"
+        flag_key = "test-flag"
+        old_version = 1
+        new_version = 2
+
+        # Set flag with old version
+        self.cache.set_cached_flag(distinct_id, flag_key, self.flag_result, old_version)
+
+        # Should hit with old version
+        result = self.cache.get_cached_flag(distinct_id, flag_key, old_version)
+        assert result is not None
+
+        # Should miss with new version
+        result = self.cache.get_cached_flag(distinct_id, flag_key, new_version)
+        assert result is None
+
+        # Invalidate old version
+        self.cache.invalidate_version(old_version)
+
+        # Should miss even with old version after invalidation
+        result = self.cache.get_cached_flag(distinct_id, flag_key, old_version)
+        assert result is None
+
+    def test_stale_cache_functionality(self):
+        distinct_id = "user123"
+        flag_key = "test-flag"
+        flag_version = 1
+
+        # Set flag in cache
+        self.cache.set_cached_flag(
+            distinct_id, flag_key, self.flag_result, flag_version
+        )
+
+        # Wait for TTL to expire
+        time.sleep(1.1)
+
+        # Should not get fresh cache
+        result = self.cache.get_cached_flag(distinct_id, flag_key, flag_version)
+        assert result is None
+
+        # Should get stale cache (within 1 hour default)
+        stale_result = self.cache.get_stale_cached_flag(distinct_id, flag_key)
+        assert stale_result is not None
+        assert stale_result.get_value()
+
+    def test_lru_eviction(self):
+        # Cache has max_size=3, so adding 4 users should evict the LRU one
+        flag_version = 1
+
+        # Add 3 users
+        for i in range(3):
+            user_id = f"user{i}"
+            self.cache.set_cached_flag(
+                user_id, "test-flag", self.flag_result, flag_version
+            )
+
+        # Access user0 to make it recently used
+        self.cache.get_cached_flag("user0", "test-flag", flag_version)
+
+        # Add 4th user, should evict user1 (least recently used)
+        self.cache.set_cached_flag("user3", "test-flag", self.flag_result, flag_version)
+
+        # user0 should still be there (was recently accessed)
+        result = self.cache.get_cached_flag("user0", "test-flag", flag_version)
+        assert result is not None
+
+        # user2 should still be there (was recently added)
+        result = self.cache.get_cached_flag("user2", "test-flag", flag_version)
+        assert result is not None
+
+        # user3 should be there (just added)
+        result = self.cache.get_cached_flag("user3", "test-flag", flag_version)
+        assert result is not None

posthog/types.py

@@ -9,6 +9,27 @@ FlagValue = Union[bool, str]
 BeforeSendCallback = Callable[[dict[str, Any]], Optional[dict[str, Any]]]
 
 
+# Type alias for the send_feature_flags parameter
+class SendFeatureFlagsOptions(TypedDict, total=False):
+    """Options for sending feature flags with capture events.
+
+    Args:
+        only_evaluate_locally: Whether to only use local evaluation for feature flags.
+            If True, only flags that can be evaluated locally will be included.
+            If False, remote evaluation via /flags API will be used when needed.
+        person_properties: Properties to use for feature flag evaluation specific to this event.
+            These properties will be merged with any existing person properties.
+        group_properties: Group properties to use for feature flag evaluation specific to this event.
+            Format: { group_type_name: { group_properties } }
+    """
+
+    should_send: bool
+    only_evaluate_locally: Optional[bool]
+    person_properties: Optional[dict[str, Any]]
+    group_properties: Optional[dict[str, dict[str, Any]]]
+    flag_keys_filter: Optional[list[str]]
+
+
 @dataclass(frozen=True)
 class FlagReason:
     code: str
@@ -92,7 +113,7 @@ class FeatureFlag:
             variant=variant,
             reason=None,
             metadata=LegacyFlagMetadata(
-                payload=payload if payload else None,
+                payload=payload,
             ),
         )
 
@@ -102,6 +123,7 @@ class FlagsResponse(TypedDict, total=False):
     errorsWhileComputingFlags: bool
     requestId: str
     quotaLimit: Optional[List[str]]
+    evaluatedAt: Optional[int]
 
 
 class FlagsAndPayloads(TypedDict, total=True):
@@ -160,7 +182,9 @@ class FeatureFlagResult:
             key=key,
             enabled=enabled,
             variant=variant,
-            payload=json.loads(payload) if isinstance(payload, str) else payload,
+            payload=json.loads(payload)
+            if isinstance(payload, str) and payload
+            else payload,
             reason=None,
         )
 
@@ -201,6 +225,7 @@ class FeatureFlagResult:
             payload=(
                 json.loads(details.metadata.payload)
                 if isinstance(details.metadata.payload, str)
+                and details.metadata.payload
                 else details.metadata.payload
             ),
             reason=details.reason.description if details.reason else None,
@@ -278,5 +303,46 @@ def to_payloads(response: FlagsResponse) -> Optional[dict[str, str]]:
     return {
         key: value.metadata.payload
         for key, value in response.get("flags", {}).items()
-        if isinstance(value, FeatureFlag) and value.enabled and value.metadata.payload
+        if isinstance(value, FeatureFlag)
+        and value.enabled
+        and value.metadata.payload is not None
     }
+
+
+class FeatureFlagError:
+    """Error type constants for the $feature_flag_error property.
+
+    These values are sent in analytics events to track flag evaluation failures.
+    They should not be changed without considering impact on existing dashboards
+    and queries that filter on these values.
+
+    Error values:
+        ERRORS_WHILE_COMPUTING: Server returned errorsWhileComputingFlags=true
+        FLAG_MISSING: Requested flag not in API response
+        QUOTA_LIMITED: Rate/quota limit exceeded
+        TIMEOUT: Request timed out
+        CONNECTION_ERROR: Network connectivity issue
+        UNKNOWN_ERROR: Unexpected exceptions
+
+    For API errors with status codes, use the api_error() method which returns
+    a string like "api_error_500".
+    """
+
+    ERRORS_WHILE_COMPUTING = "errors_while_computing_flags"
+    FLAG_MISSING = "flag_missing"
+    QUOTA_LIMITED = "quota_limited"
+    TIMEOUT = "timeout"
+    CONNECTION_ERROR = "connection_error"
+    UNKNOWN_ERROR = "unknown_error"
+
+    @staticmethod
+    def api_error(status: Union[int, str]) -> str:
+        """Generate API error string with status code.
+
+        Args:
+            status: HTTP status code from the API error
+
+        Returns:
+            Error string like "api_error_500"
+        """
+        return f"api_error_{status}"

posthog/utils.py

@@ -1,12 +1,17 @@
+import json
 import logging
 import numbers
 import re
+import time
 from collections import defaultdict
 from dataclasses import asdict, is_dataclass
 from datetime import date, datetime, timezone
 from decimal import Decimal
 from typing import Any, Optional
 from uuid import UUID
+import sys
+import platform
+import distro  # For Linux OS detection
 
 import six
 from dateutil.tz import tzlocal, tzutc
@@ -154,6 +159,266 @@ class SizeLimitedDict(defaultdict):
         super().__setitem__(key, value)
 
 
+class FlagCacheEntry:
+    def __init__(self, flag_result, flag_definition_version, timestamp=None):
+        self.flag_result = flag_result
+        self.flag_definition_version = flag_definition_version
+        self.timestamp = timestamp or time.time()
+
+    def is_valid(self, current_time, ttl, current_flag_version):
+        time_valid = (current_time - self.timestamp) < ttl
+        version_valid = self.flag_definition_version == current_flag_version
+        return time_valid and version_valid
+
+    def is_stale_but_usable(self, current_time, max_stale_age=3600):
+        return (current_time - self.timestamp) < max_stale_age
+
+
+class FlagCache:
+    def __init__(self, max_size=10000, default_ttl=300):
+        self.cache = {}  # distinct_id -> {flag_key: FlagCacheEntry}
+        self.access_times = {}  # distinct_id -> last_access_time
+        self.max_size = max_size
+        self.default_ttl = default_ttl
+
+    def get_cached_flag(self, distinct_id, flag_key, current_flag_version):
+        current_time = time.time()
+
+        if distinct_id not in self.cache:
+            return None
+
+        user_flags = self.cache[distinct_id]
+        if flag_key not in user_flags:
+            return None
+
+        entry = user_flags[flag_key]
+        if entry.is_valid(current_time, self.default_ttl, current_flag_version):
+            self.access_times[distinct_id] = current_time
+            return entry.flag_result
+
+        return None
+
+    def get_stale_cached_flag(self, distinct_id, flag_key, max_stale_age=3600):
+        current_time = time.time()
+
+        if distinct_id not in self.cache:
+            return None
+
+        user_flags = self.cache[distinct_id]
+        if flag_key not in user_flags:
+            return None
+
+        entry = user_flags[flag_key]
+        if entry.is_stale_but_usable(current_time, max_stale_age):
+            return entry.flag_result
+
+        return None
+
+    def set_cached_flag(
+        self, distinct_id, flag_key, flag_result, flag_definition_version
+    ):
+        current_time = time.time()
+
+        # Evict LRU users if we're at capacity
+        if distinct_id not in self.cache and len(self.cache) >= self.max_size:
+            self._evict_lru()
+
+        # Initialize user cache if needed
+        if distinct_id not in self.cache:
+            self.cache[distinct_id] = {}
+
+        # Store the flag result
+        self.cache[distinct_id][flag_key] = FlagCacheEntry(
+            flag_result, flag_definition_version, current_time
+        )
+        self.access_times[distinct_id] = current_time
+
+    def invalidate_version(self, old_version):
+        users_to_remove = []
+
+        for distinct_id, user_flags in self.cache.items():
+            flags_to_remove = []
+            for flag_key, entry in user_flags.items():
+                if entry.flag_definition_version == old_version:
+                    flags_to_remove.append(flag_key)
+
+            # Remove invalidated flags
+            for flag_key in flags_to_remove:
+                del user_flags[flag_key]
+
+            # Remove user entirely if no flags remain
+            if not user_flags:
+                users_to_remove.append(distinct_id)
+
+        # Clean up empty users
+        for distinct_id in users_to_remove:
+            del self.cache[distinct_id]
+            if distinct_id in self.access_times:
+                del self.access_times[distinct_id]
+
+    def _evict_lru(self):
+        if not self.access_times:
+            return
+
+        # Remove 20% of least recently used entries
+        sorted_users = sorted(self.access_times.items(), key=lambda x: x[1])
+        to_remove = max(1, len(sorted_users) // 5)
+
+        for distinct_id, _ in sorted_users[:to_remove]:
+            if distinct_id in self.cache:
+                del self.cache[distinct_id]
+            if distinct_id in self.access_times:
+                del self.access_times[distinct_id]
+
+    def clear(self):
+        self.cache.clear()
+        self.access_times.clear()
+
+
+class RedisFlagCache:
+    def __init__(
+        self, redis_client, default_ttl=300, stale_ttl=3600, key_prefix="posthog:flags:"
+    ):
+        self.redis = redis_client
+        self.default_ttl = default_ttl
+        self.stale_ttl = stale_ttl
+        self.key_prefix = key_prefix
+        self.version_key = f"{key_prefix}version"
+
+    def _get_cache_key(self, distinct_id, flag_key):
+        return f"{self.key_prefix}{distinct_id}:{flag_key}"
+
+    def _serialize_entry(self, flag_result, flag_definition_version, timestamp=None):
+        if timestamp is None:
+            timestamp = time.time()
+
+        # Use clean to make flag_result JSON-serializable for cross-platform compatibility
+        serialized_result = clean(flag_result)
+
+        entry = {
+            "flag_result": serialized_result,
+            "flag_version": flag_definition_version,
+            "timestamp": timestamp,
+        }
+        return json.dumps(entry)
+
+    def _deserialize_entry(self, data):
+        try:
+            entry = json.loads(data)
+            flag_result = entry["flag_result"]
+            return FlagCacheEntry(
+                flag_result=flag_result,
+                flag_definition_version=entry["flag_version"],
+                timestamp=entry["timestamp"],
+            )
+        except (json.JSONDecodeError, KeyError, ValueError):
+            # If deserialization fails, treat as cache miss
+            return None
+
+    def get_cached_flag(self, distinct_id, flag_key, current_flag_version):
+        try:
+            cache_key = self._get_cache_key(distinct_id, flag_key)
+            data = self.redis.get(cache_key)
+
+            if data:
+                entry = self._deserialize_entry(data)
+                if entry and entry.is_valid(
+                    time.time(), self.default_ttl, current_flag_version
+                ):
+                    return entry.flag_result
+
+            return None
+        except Exception:
+            # Redis error - return None to fall back to normal evaluation
+            return None
+
+    def get_stale_cached_flag(self, distinct_id, flag_key, max_stale_age=None):
+        try:
+            if max_stale_age is None:
+                max_stale_age = self.stale_ttl
+
+            cache_key = self._get_cache_key(distinct_id, flag_key)
+            data = self.redis.get(cache_key)
+
+            if data:
+                entry = self._deserialize_entry(data)
+                if entry and entry.is_stale_but_usable(time.time(), max_stale_age):
+                    return entry.flag_result
+
+            return None
+        except Exception:
+            # Redis error - return None
+            return None
+
+    def set_cached_flag(
+        self, distinct_id, flag_key, flag_result, flag_definition_version
+    ):
+        try:
+            cache_key = self._get_cache_key(distinct_id, flag_key)
+            serialized_entry = self._serialize_entry(
+                flag_result, flag_definition_version
+            )
+
+            # Set with TTL for automatic cleanup (use stale_ttl for total lifetime)
+            self.redis.setex(cache_key, self.stale_ttl, serialized_entry)
+
+            # Update the current version
+            self.redis.set(self.version_key, flag_definition_version)
+
+        except Exception:
+            # Redis error - silently fail, don't break flag evaluation
+            pass
+
+    def invalidate_version(self, old_version):
+        try:
+            # For Redis, we use a simple approach: scan for keys with old version
+            # and delete them. This could be expensive with many keys, but it's
+            # necessary for correctness.
+
+            cursor = 0
+            pattern = f"{self.key_prefix}*"
+
+            while True:
+                cursor, keys = self.redis.scan(cursor, match=pattern, count=100)
+
+                for key in keys:
+                    if key.decode() == self.version_key:
+                        continue
+
+                    try:
+                        data = self.redis.get(key)
+                        if data:
+                            entry_dict = json.loads(data)
+                            if entry_dict.get("flag_version") == old_version:
+                                self.redis.delete(key)
+                    except (json.JSONDecodeError, KeyError):
+                        # If we can't parse the entry, delete it to be safe
+                        self.redis.delete(key)
+
+                if cursor == 0:
+                    break
+
+        except Exception:
+            # Redis error - silently fail
+            pass
+
+    def clear(self):
+        try:
+            # Delete all keys matching our pattern
+            cursor = 0
+            pattern = f"{self.key_prefix}*"
+
+            while True:
+                cursor, keys = self.redis.scan(cursor, match=pattern, count=100)
+                if keys:
+                    self.redis.delete(*keys)
+                if cursor == 0:
+                    break
+        except Exception:
+            # Redis error - silently fail
+            pass
+
+
 def convert_to_datetime_aware(date_obj):
     if date_obj.tzinfo is None:
         date_obj = date_obj.replace(tzinfo=timezone.utc)
@@ -198,3 +463,57 @@ def str_iequals(value, comparand):
         False
     """
     return str(value).casefold() == str(comparand).casefold()
+
+
+def get_os_info():
+    """
+    Returns standardized OS name and version information.
+    Similar to how user agent parsing works in JS.
+    """
+    os_name = ""
+    os_version = ""
+
+    platform_name = sys.platform
+
+    if platform_name.startswith("win"):
+        os_name = "Windows"
+        if hasattr(platform, "win32_ver"):
+            win_version = platform.win32_ver()[0]
+            if win_version:
+                os_version = win_version
+
+    elif platform_name == "darwin":
+        os_name = "Mac OS X"
+        if hasattr(platform, "mac_ver"):
+            mac_version = platform.mac_ver()[0]
+            if mac_version:
+                os_version = mac_version
+
+    elif platform_name.startswith("linux"):
+        os_name = "Linux"
+        linux_info = distro.info()
+        if linux_info["version"]:
+            os_version = linux_info["version"]
+
+    elif platform_name.startswith("freebsd"):
+        os_name = "FreeBSD"
+        if hasattr(platform, "release"):
+            os_version = platform.release()
+
+    else:
+        os_name = platform_name
+        if hasattr(platform, "release"):
+            os_version = platform.release()
+
+    return os_name, os_version
+
+
+def system_context() -> dict[str, Any]:
+    os_name, os_version = get_os_info()
+
+    return {
+        "$python_runtime": platform.python_implementation(),
+        "$python_version": "%s.%s.%s" % (sys.version_info[:3]),
+        "$os": os_name,
+        "$os_version": os_version,
+    }

posthog/version.py

@@ -1,4 +1 @@
-VERSION = "5.3.0"
-
-if __name__ == "__main__":
-    print(VERSION, end="")  # noqa: T201
+VERSION = "7.9.6"

pyproject.toml

@@ -4,24 +4,24 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "posthog"
-dynamic = ["version"]
+version = "7.9.6"
 description = "Integrate PostHog into any python application."
 authors = [{ name = "PostHog", email = "hey@posthog.com" }]
 maintainers = [{ name = "PostHog", email = "hey@posthog.com" }]
 license = { text = "MIT" }
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 classifiers = [
     "Development Status :: 5 - Production/Stable",
     "Intended Audience :: Developers",
     "Operating System :: OS Independent",
     "License :: OSI Approved :: MIT License",
     "Programming Language :: Python",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
 ]
 dependencies = [
     "requests>=2.7,<3.0",
@@ -29,6 +29,7 @@ dependencies = [
     "python-dateutil>=2.2",
     "backoff>=1.10.0",
     "distro>=1.5.0",
+    "typing-extensions>=4.2.0",
 ]
 
 [project.urls]
@@ -65,13 +66,13 @@ test = [
     "pytest-timeout",
     "pytest-asyncio",
     "django",
-    "openai",
-    "anthropic",
-    "langgraph>=0.4.8",
-    "langchain-core>=0.3.65",
-    "langchain-community>=0.3.25",
-    "langchain-openai>=0.3.22",
-    "langchain-anthropic>=0.3.15",
+    "openai>=2.0",
+    "anthropic>=0.72",
+    "langgraph>=1.0",
+    "langchain-core>=1.0",
+    "langchain-community>=0.4",
+    "langchain-openai>=1.0",
+    "langchain-anthropic>=1.0",
     "google-genai",
     "pydantic",
     "parameterized>=0.8.1",
@@ -83,16 +84,17 @@ packages = [
     "posthog.ai",
     "posthog.ai.langchain",
     "posthog.ai.openai",
+    "posthog.ai.openai_agents",
     "posthog.ai.anthropic",
     "posthog.ai.gemini",
     "posthog.test",
-    "posthog.exception_integrations",
+    "posthog.test.ai",
+    "posthog.test.ai.openai_agents",
     "posthog.integrations",
 ]
 
-[tool.setuptools.dynamic]
-version = { attr = "posthog.version.VERSION" }
-
 [tool.pytest.ini_options]
 asyncio_mode = "auto"
 asyncio_default_fixture_loop_scope = "function"
+testpaths = ["posthog/test"]
+norecursedirs = ["integration_tests"]