Add changelog for PR #3851

Processing metrics were an early addition that predated a clear
understanding of what timing measurements matter in real-time pipelines.
They were inconsistently implemented across services, often broken, and
overlapped with the better-defined TTFB metric.

- Remove ProcessingMetricsData class and all start/stop_processing_metrics
  methods from FrameProcessorMetrics, FrameProcessor, and SentryMetrics
- Remove all processing metrics calls from 31 service files (LLM, TTS,
  STT, image, vision, realtime)
- Clean up empty _start_metrics() stubs left in STT services
- Remove processing metrics handling from RTVI, metrics log observer,
  pipeline task initial metrics, and strands agents framework
- Update tests and examples

Remaining metrics (TTFB, LLM token usage, TTS character usage, text
aggregation time) are well-defined and consistently implemented.

.agents/skills/changelog

@@ -1 +0,0 @@
-../../.claude/skills/changelog

.agents/skills/cleanup

@@ -1 +0,0 @@
-../../.claude/skills/cleanup

.agents/skills/code-review

@@ -1 +0,0 @@
-../../.claude/skills/code-review

.agents/skills/docstring

@@ -1 +0,0 @@
-../../.claude/skills/docstring

.agents/skills/pr-description

@@ -1 +0,0 @@
-../../.claude/skills/pr-description

.agents/skills/pr-submit

@@ -1 +0,0 @@
-../../.claude/skills/pr-submit

.agents/skills/update-docs

@@ -1 +0,0 @@
-../../.claude/skills/update-docs

.claude/skills/changelog/SKILL.md

@@ -32,20 +32,6 @@ Create changelog files for the important commits in this PR. The PR number is pr
 
 6. Use ⚠️ emoji prefix for breaking changes.
 
-7. **Write changes in user-facing terms first.** Lead with what users of the framework will notice: new APIs, changed behavior, new parameters, fixed bugs they might have hit, etc. Implementation details (internal refactoring, how something is wired up under the hood) can be included as secondary context after the user-facing description, but should never be the *only* content of a changelog entry when there is a user-visible effect.
-
-   **Good** (user-facing first, implementation detail as context):
-   ```
-   - Turn completion instructions now persist correctly across full context updates when using `system_instruction`. Previously they were injected as a context system message, which caused warning spam and didn't survive context updates.
-   ```
-
-   **Bad** (implementation detail only, no user-facing framing):
-   ```
-   - Fixed turn completion instructions being injected as a context system message instead of using `system_instruction`.
-   ```
-
-   Ask yourself: "If I'm a developer building on Pipecat, what would I notice changed?" Start there.
-
 ## Example
 
 For PR #3519 with a new feature and a bug fix:
@@ -57,5 +43,5 @@ For PR #3519 with a new feature and a bug fix:
 
 `changelog/3519.fixed.md`:
 ```
-- Fixed an issue where something was not working correctly in some user-visible scenario. The root cause was an internal implementation detail.
+- Fixed an issue where something was not working correctly.
 ```

.claude/skills/cleanup/SKILL.md

@@ -1,8 +1,3 @@
----
-name: cleanup
-description: Review, refactor, document, and validate code changes in the current branch
----
-
 # Code Cleanup Skill
 
 The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecat's architecture, coding standards, and example patterns**.
@@ -149,7 +144,7 @@ class InputParams(BaseModel):
 
 #### Examples
 
-Validated against `examples/07-interruptible.py`:
+Validated against `examples/foundational/07-interruptible.py`:
 
 - Proper `create_transport()` usage
 - Correct pipeline structure

.claude/skills/squash-commits/SKILL.md

@@ -1,91 +0,0 @@
----
-name: squash-commits
-description: Reorganize messy branch commits into a small set of logical, meaningful commits without changing any content. Drops merge-from-main commits. Safe: creates a backup branch first.
----
-
-Reorganize the commits on the current branch into a small number of logical commits. Do NOT change any file content — only the commit structure changes.
-
-## Instructions
-
-### 1. Safety check
-
-```bash
-git status --short
-```
-
-If there are uncommitted changes, stop and tell the user to commit or stash them first.
-
-### 2. Inspect the branch
-
-```bash
-git log main..HEAD --oneline
-git diff main..HEAD --name-only
-```
-
-List every file changed vs `main` and every commit on the branch (excluding merge commits from main).
-
-### 3. Create a backup branch
-
-```bash
-git branch backup/<current-branch-name>
-```
-
-Tell the user the backup exists so they can recover if needed.
-
-### 4. Soft-reset to main and unstage everything
-
-```bash
-git reset --soft main
-git restore --staged .
-```
-
-All branch changes are now in the working tree, unstaged. No content has changed.
-
-### 5. Plan the logical groups
-
-Read the changed files and the original commit messages to understand what the work covers. Group related files into logical commits. Typical groups:
-
-- Core feature or fix (new source files + modified core files)
-- Secondary features or fixes (each as its own commit if distinct)
-- Refactoring or renames
-- Tests
-- Changelogs / docs
-
-Use the changelog files (if any) as a strong hint — each changelog entry often maps to one commit.
-
-Present the proposed grouping to the user and ask for confirmation before committing.
-
-### 6. Commit in logical groups
-
-For each group, stage only the relevant files and commit with a clear message following the project's conventions:
-
-```bash
-git add <file1> <file2> ...
-git commit -m "..."
-```
-
-Use conventional commit prefixes if the project uses them (`feat:`, `fix:`, `refactor:`, `test:`, `chore:`).
-
-### 7. Verify
-
-```bash
-git log main..HEAD --oneline
-git diff main..HEAD --name-only
-git status --short
-```
-
-Confirm:
-- Commit count is small and each message is meaningful
-- The set of changed files vs `main` is identical to before
-- Working tree is clean
-
-### 8. Remind about force-push
-
-The branch history has been rewritten. Tell the user they will need to `git push --force-with-lease` when they are ready to update the remote. Do NOT push automatically.
-
-## Rules
-
-- Never change file contents. If you find yourself editing a file, stop.
-- Never skip the backup branch step.
-- Never force-push without explicit user instruction.
-- If any step fails or the result looks wrong, tell the user and suggest restoring from the backup: `git reset --hard backup/<branch-name>`.

.claude/skills/update-docs/SKILL.md

@@ -157,11 +157,7 @@ After processing all mapped pairs, check for two kinds of gaps:
 
 **Missing sections**: Mapped doc pages that are missing standard sections compared to the source. For example, a transport page with no Configuration section, or a service page with no InputParams table when the source defines `InputParams(BaseModel)`. Flag these and offer to add the missing sections.
 
-If the user wants a new page, do all three of the following:
-
-#### 8a: Create the doc page
-
-Create the new `.mdx` file using this template structure:
+If the user wants a new page, create it using this template structure:
 ```
 ---
 title: "Service Name"
@@ -211,53 +207,6 @@ pip install "pipecat-ai[package-name]"
 [Event table and example code]
 ```
 
-#### 8b: Add to docs.json
-
-Add the new page path to `DOCS_PATH/docs.json` in the correct navigation group. The path format is `server/services/{category}/{provider}` (without the `.mdx` extension).
-
-Find the matching group in the navigation structure:
-- **STT** → `"group": "Speech-to-Text"` under Services
-- **TTS** → `"group": "Text-to-Speech"` under Services
-- **LLM** → `"group": "LLM"` under Services
-- **S2S** → `"group": "Speech-to-Speech"` under Services
-- **Transport** → `"group": "Transport"` under Services
-- **Serializer** → `"group": "Serializers"` under Services
-- **Image generation** → `"group": "Image Generation"` under Services
-- **Video** → `"group": "Video"` under Services
-- **Memory** → `"group": "Memory"` under Services
-- **Vision** → `"group": "Vision"` under Services
-- **Analytics** → `"group": "Analytics & Monitoring"` under Services
-
-Insert the new entry **alphabetically** within the group's `pages` array. For example, adding a new STT service "foo":
-```json
-{
-  "group": "Speech-to-Text",
-  "pages": [
-    "server/services/stt/assemblyai",
-    "server/services/stt/aws",
-    ...
-    "server/services/stt/foo",
-    ...
-  ]
-}
-```
-
-#### 8c: Add to supported-services.mdx
-
-Add a new row to the correct category table in `DOCS_PATH/server/services/supported-services.mdx`.
-
-Use this format:
-```
-| [DisplayName](/server/services/{category}/{provider}) | `pip install "pipecat-ai[package]"` |
-```
-
-To determine the correct values:
-- **DisplayName**: Use the service's human-readable name (e.g., "ElevenLabs", "AWS Polly", "Google Gemini")
-- **package**: Look at the service's `pyproject.toml` extras or the import pattern in the source code. For example, if the service is in `src/pipecat/services/foo/`, the package is typically `foo`.
-- If no pip dependencies are required, use `No dependencies required` instead.
-
-Insert the new row **alphabetically** within the table. Match the column alignment of the existing rows.
-
 ### Step 9: Output summary
 
 After all edits are complete, print a summary:
@@ -272,9 +221,6 @@ After all edits are complete, print a summary:
 ### Updated guides
 - `guides/learn/speech-to-text.mdx` — Updated code example (renamed `old_param` → `new_param`)
 
-### New service pages
-- `server/services/tts/newprovider.mdx` — Created page, added to docs.json (Text-to-Speech), added to supported-services.mdx
-
 ### Unmapped source files
 - `src/pipecat/services/newprovider/tts.py` — NewProviderTTSService (no doc page exists)
 
@@ -301,6 +247,4 @@ Before finishing, verify:
 - [ ] New parameters have accurate types and defaults from source
 - [ ] Formatting matches the existing page style
 - [ ] Guides referencing changed APIs were checked and updated
-- [ ] New service pages were added to `docs.json` in the correct group, alphabetically
-- [ ] New service pages were added to `supported-services.mdx` in the correct table, alphabetically
 - [ ] Unmapped files were reported to the user

.dockerignore

@@ -0,0 +1,30 @@
+# flyctl launch added from .gitignore
+**/.vscode
+**/env
+**/__pycache__
+**/*~
+**/venv
+#*#
+
+# Distribution / packaging
+**/.Python
+**/build
+**/develop-eggs
+**/dist
+**/downloads
+**/eggs
+**/.eggs
+**/lib
+**/lib64
+**/parts
+**/sdist
+**/var
+**/wheels
+**/share/python-wheels
+**/*.egg-info
+**/.installed.cfg
+**/*.egg
+**/MANIFEST
+**/.DS_Store
+**/.env
+fly.toml

.github/workflows/coverage.yaml

@@ -41,10 +41,7 @@ jobs:
             --extra google \
             --extra langchain \
             --extra livekit \
-            --extra pgmq \
             --extra piper \
-            --extra redis \
-            --extra runner \
             --extra sagemaker \
             --extra tracing \
             --extra websocket

.github/workflows/format.yaml

@@ -32,9 +32,7 @@ jobs:
         run: uv python install 3.12
 
       - name: Install development dependencies
-        # `--all-extras` (matching the dev setup in README.md) so pyright can
-        # resolve types from various optional dependencies.
-        run: uv sync --group dev --all-extras --no-extra gstreamer --no-extra local
+        run: uv sync --group dev
 
       - name: Ruff formatter
         id: ruff-format
@@ -43,7 +41,3 @@ jobs:
       - name: Ruff linter (all rules)
         id: ruff-check
         run: uv run ruff check
-
-      - name: Type check (pyright)
-        id: pyright
-        run: uv run pyright

.github/workflows/python-compatibility.yaml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ['3.11.15', '3.12.13', '3.13.12', '3.14.3']
+        python-version: ['3.10.19', '3.11.14', '3.12.12', '3.13.12']
 
     name: Python ${{ matrix.python-version }}
     steps:
@@ -42,7 +42,7 @@ jobs:
 
       - name: Test uv sync with all extras
         run: |
-          uv sync --group dev --all-extras
+          uv sync --group dev --all-extras --no-extra krisp
 
       - name: Verify installation
         run: |

.github/workflows/sync-quickstart.yaml

@@ -0,0 +1,51 @@
+name: Sync Quickstart to pipecat-quickstart repo
+
+on:
+  push:
+    branches: [main]
+    paths:
+      - 'examples/quickstart/**'
+  workflow_dispatch: # Manual trigger
+
+jobs:
+  sync-quickstart:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout main repo
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Checkout quickstart repo
+        uses: actions/checkout@v4
+        with:
+          repository: pipecat-ai/pipecat-quickstart
+          token: ${{ secrets.QUICKSTART_SYNC_TOKEN }}
+          path: quickstart-repo
+
+      - name: Sync files (excluding uv.lock and README.md)
+        run: |
+          # Copy all files except uv.lock and README.md
+          find examples/quickstart -type f \
+            -not -name "README.md" \
+            -not -name "uv.lock" \
+            -exec cp {} quickstart-repo/ \;
+
+      - name: Commit and push changes
+        run: |
+          cd quickstart-repo
+          git config user.name "GitHub Action"
+          git config user.email "action@github.com"
+          git add .
+
+          # Only commit if there are changes
+          if ! git diff --staged --quiet; then
+            git commit -m "Sync from pipecat main repo
+            
+            Updated files from examples/quickstart/
+            Commit: ${{ github.sha }}
+            "
+            git push
+          else
+            echo "No changes to sync"
+          fi

.github/workflows/tests.yaml

@@ -45,10 +45,7 @@ jobs:
             --extra google \
             --extra langchain \
             --extra livekit \
-            --extra pgmq \
             --extra piper \
-            --extra redis \
-            --extra runner \
             --extra sagemaker \
             --extra tracing \
             --extra websocket

.github/workflows/update-docs.yml

@@ -1,148 +0,0 @@
-name: Update Documentation on PR Merge
-
-on:
-  pull_request_target:
-    types: [closed]
-    branches: [main]
-    paths:
-      - "src/pipecat/services/**"
-      - "src/pipecat/transports/**"
-      - "src/pipecat/serializers/**"
-      - "src/pipecat/processors/**"
-      - "src/pipecat/audio/**"
-      - "src/pipecat/turns/**"
-      - "src/pipecat/observers/**"
-      - "src/pipecat/pipeline/**"
-  workflow_dispatch:
-    inputs:
-      pr_number:
-        description: "PR number to generate docs for"
-        required: true
-        type: string
-
-jobs:
-  update-docs:
-    if: >-
-      github.event_name == 'workflow_dispatch' ||
-      github.event.pull_request.merged == true
-    runs-on: ubuntu-latest
-    timeout-minutes: 15
-    permissions:
-      contents: read
-      pull-requests: read
-      id-token: write
-    steps:
-      - name: Checkout pipecat
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Checkout docs
-        uses: actions/checkout@v4
-        with:
-          repository: pipecat-ai/docs
-          token: ${{ secrets.DOCS_SYNC_TOKEN }}
-          path: _docs
-
-      - name: Resolve PR number
-        id: pr
-        run: |
-          if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
-            echo "number=${{ inputs.pr_number }}" >> "$GITHUB_OUTPUT"
-          else
-            echo "number=${{ github.event.pull_request.number }}" >> "$GITHUB_OUTPUT"
-          fi
-
-      - name: Update documentation
-        uses: anthropics/claude-code-action@v1
-        env:
-          DOCS_SYNC_TOKEN: ${{ secrets.DOCS_SYNC_TOKEN }}
-        with:
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          prompt: |
-            You are updating documentation for the pipecat-ai/docs repository based on
-            changes merged in PR #${{ steps.pr.outputs.number }} of pipecat-ai/pipecat.
-
-            ## Setup
-
-            1. Read the skill instructions at `.claude/skills/update-docs/SKILL.md`
-            2. Read the source-to-doc mapping at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md`
-            3. The docs repository is checked out at `./_docs/`
-
-            ## Get the diff
-
-            Run `gh pr diff ${{ steps.pr.outputs.number }}` to see what changed in the PR.
-            Also run `gh pr diff ${{ steps.pr.outputs.number }} --name-only` to get the list of changed files.
-            Filter to source files matching the directories listed in SKILL.md Step 3.
-
-            If no relevant source files were changed, exit with "No documentation changes needed."
-
-            ## Follow the skill instructions
-
-            Apply the SKILL.md workflow (Steps 3-9) with these adaptations for automation:
-
-            ### Docs path
-            Use `./_docs/` — it's already checked out. Do not ask for a path.
-
-            ### Branch management
-            - Branch name: `docs/pr-${{ steps.pr.outputs.number }}`
-            - Work inside `./_docs/` for all doc edits and git operations
-            - Check if the branch already exists on the remote:
-              ```bash
-              cd _docs && git fetch origin docs/pr-${{ steps.pr.outputs.number }} 2>/dev/null
-              ```
-              - If it exists: check it out (supports workflow re-runs)
-              - If not: create it from main
-
-            ### Git config
-            Before committing in `_docs`, set:
-            ```bash
-            git config user.name "github-actions[bot]"
-            git config user.email "github-actions[bot]@users.noreply.github.com"
-            ```
-
-            ### No interactive questions
-            Do not ask questions. If you encounter gaps (unmapped files, missing sections,
-            ambiguous changes), note them in the PR body under "## Gaps identified".
-
-            ### Creating the docs PR
-            After committing all changes in `_docs`, push and create a PR:
-            ```bash
-            cd _docs
-            git push -u origin docs/pr-${{ steps.pr.outputs.number }}
-            GH_TOKEN=$DOCS_SYNC_TOKEN gh pr create \
-              --repo pipecat-ai/docs \
-              --label auto-docs \
-              --label pipecat \
-              --title "docs: update for pipecat PR #${{ steps.pr.outputs.number }}" \
-              --body "$(cat <<'BODY'
-            Automated documentation update for [pipecat PR #${{ steps.pr.outputs.number }}](https://github.com/pipecat-ai/pipecat/pull/${{ steps.pr.outputs.number }}).
-
-            ## Changes
-            <summarize each doc page updated and what changed>
-
-            ## Gaps identified
-            <any unmapped files, missing doc pages, or missing sections — or "None">
-            BODY
-            )"
-            ```
-
-            ### Re-run handling
-            If `gh pr create` fails because a PR from that branch already exists,
-            push the updated commits and use `gh pr edit` to update the body instead.
-
-            ### No-op
-            If after analyzing the diff you determine no documentation changes are needed
-            (e.g., only skip-listed files changed, or changes don't affect public API docs),
-            exit cleanly without creating a branch or PR. Output "No documentation changes needed."
-
-            ## Important rules
-            - Only modify files inside `./_docs/` — never modify pipecat source code
-            - Follow the conservative editing rules from SKILL.md Step 6
-            - Read each doc page fully before editing (SKILL.md Guidelines)
-            - Use `GH_TOKEN=$DOCS_SYNC_TOKEN` for all `gh` commands targeting pipecat-ai/docs
-          claude_args: |
-            --model claude-sonnet-4-5-20250929
-            --max-turns 30
-            --allowedTools "Read,Write,Edit,Glob,Grep,Bash"

.pre-commit-config.yaml

@@ -1,13 +1,8 @@
 repos:
-  - repo: local
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.12.1
     hooks:
       - id: ruff
-        name: ruff
-        entry: uv run ruff check --fix
-        language: system
-        types: [python]
+        language_version: python3
+        args: [--fix]
       - id: ruff-format
-        name: ruff-format
-        entry: uv run ruff format
-        language: system
-        types: [python]

.readthedocs.yaml

@@ -11,7 +11,7 @@ build:
   jobs:
     post_install:
       - pip install uv
-      - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra mlx-whisper
+      - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
 
 sphinx:
   configuration: docs/api/conf.py

AGENTS.md

@@ -1,174 +0,0 @@
-# AGENTS.md
-
-This file provides guidance to AI coding agents when working with code in this repository.
-
-## Project Overview
-
-Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. It orchestrates audio/video, AI services, transports, and conversation pipelines using a frame-based architecture.
-
-## Common Commands
-
-```bash
-# Setup development environment
-uv sync --group dev --all-extras --no-extra gstreamer --no-extra local
-
-# Install pre-commit hooks
-uv run pre-commit install
-
-# Run all tests
-uv run pytest
-
-# Run a single test file
-uv run pytest tests/test_name.py
-
-# Run a specific test
-uv run pytest tests/test_name.py::test_function_name
-
-# Preview changelog
-uv run towncrier build --draft --version Unreleased
-
-# Lint and format check
-uv run ruff check
-uv run ruff format --check
-
-# Update dependencies (after editing pyproject.toml)
-uv lock && uv sync
-```
-
-## Architecture
-
-### Frame-Based Pipeline Processing
-
-All data flows as **Frame** objects through a pipeline of **FrameProcessors**:
-
-```
-[Processor1] → [Processor2] → ... → [ProcessorN]
-```
-
-**Key components:**
-
-- **Frames** (`src/pipecat/frames/frames.py`): Data units (audio, text, video) and control signals. Flow DOWNSTREAM (input→output) or UPSTREAM (acknowledgments/errors).
-
-- **FrameProcessor** (`src/pipecat/processors/frame_processor.py`): Base processing unit. Each processor receives frames, processes them, and pushes results downstream.
-
-- **Pipeline** (`src/pipecat/pipeline/pipeline.py`): Chains processors together.
-
-- **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel.
-
-- **Transports** (`src/pipecat/transports/`): Transports are frame processors used for external I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`, `BaseInputTransport` and `BaseOutputTransport`.
-
-- **Pipeline Task (`src/pipecat/pipeline/task.py`)**: Runs and manages a pipeline. Pipeline tasks send the first frame, `StartFrame`, to the pipeline in order for processors to know they can start processing and pushing frames. Pipeline tasks internally create a pipeline with two additional processors, a source processor before the user-defined pipeline and a sink processor at the end. Those are used for multiple things: error handling, pipeline task level events, heartbeat monitoring, etc.
-
-- **Pipeline Runner (`src/pipecat/pipeline/runner.py`)**: High-level entry point for executing pipeline tasks. Handles signal management (SIGINT/SIGTERM) for graceful shutdown and optional garbage collection. Run a single pipeline task with `await runner.run(task)` or multiple concurrently with `await asyncio.gather(runner.run(task1), runner.run(task2))`.
-
-- **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`.
-
-- **Serializers** (`src/pipecat/serializers/`): Convert frames to/from wire formats for WebSocket transports. `FrameSerializer` base class defines `serialize()` and `deserialize()`. Telephony serializers (Twilio, Plivo, Vonage, Telnyx, Exotel, Genesys) handle provider-specific protocols and audio encoding (e.g., μ-law).
-
-- **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels.
-
-- **Observers** (`src/pipecat/observers/`): Monitor frame flow without modifying the pipeline. Passed to `PipelineTask` via the `observers` parameter. Implement `on_process_frame()` and `on_push_frame()` callbacks.
-
-### Important Patterns
-
-- **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input
-
-- **Turn Management**: Turn management is done through `LLMUserAggregator` and
-  `LLMAssistantAggregator`, created with `LLMContextAggregatorPair`
-
-- **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively.
-
-- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. An `InterruptionFrame` carries an optional `asyncio.Event` that is set when the frame reaches the pipeline sink. If a processor stops an `InterruptionFrame` from propagating downstream (i.e., doesn't push it), it **must** call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()` callers.
-
-- **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`.
-
-- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to execute fast.
-
-- **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation.
-
-- **Error Handling**: Use `await self.push_error(msg, exception, fatal)` to push errors upstream. Services should use `fatal=False` (the default) so application code can handle errors and take action (e.g. switch to another service).
-
-### Key Directories
-
-| Directory                  | Purpose                                            |
-| -------------------------- | -------------------------------------------------- |
-| `src/pipecat/frames/`      | Frame definitions (100+ types)                     |
-| `src/pipecat/processors/`  | FrameProcessor base + aggregators, filters, audio  |
-| `src/pipecat/pipeline/`    | Pipeline orchestration                             |
-| `src/pipecat/services/`    | AI service integrations (60+ providers)            |
-| `src/pipecat/transports/`  | Transport layer (Daily, LiveKit, WebSocket, Local) |
-| `src/pipecat/serializers/` | Frame serialization for WebSocket protocols        |
-| `src/pipecat/observers/`   | Pipeline observers for monitoring frame flow       |
-| `src/pipecat/audio/`       | VAD, filters, mixers, turn detection, DTMF         |
-| `src/pipecat/turns/`       | User turn management                               |
-
-## Code Style
-
-- **Docstrings**: Google-style. Classes describe purpose; `__init__` has `Args:` section; dataclasses use `Parameters:` section.
-- **Deprecations**: Use the `.. deprecated:: <version>` Sphinx directive in docstrings (never inline tags like `[DEPRECATED]`), and pair it with a runtime `warnings.warn(..., DeprecationWarning)` at the call site. See `CONTRIBUTING.md` for full conventions.
-- **Linting**: Ruff (line length 100). Pre-commit hooks enforce formatting.
-- **Type hints**: Required for complex async code.
-- **Dataclass vs Pydantic**: Use `@dataclass` for frames and internal pipeline data (high-frequency, no validation needed). Use Pydantic `BaseModel` for configuration, parameters, metrics, and external API data (benefits from validation and serialization). Specifically:
-  - `@dataclass`: Frame types, context aggregator pairs, internal data containers
-  - `BaseModel`: Service `InputParams`, transport/VAD/turn params, metrics data, API request/response models, serializer params
-
-### Docstring Example
-
-```python
-class MyService(LLMService):
-    """Description of what the service does.
-
-    More detailed description.
-
-    Event handlers available:
-
-    - on_connected: Called when we are connected
-
-    Example::
-
-        @service.event_handler("on_connected")
-        async def on_connected(service, frame):
-            ...
-    """
-
-    def __init__(self, param1: str, **kwargs):
-        """Initialize the service.
-
-        Args:
-            param1: Description of param1.
-            **kwargs: Additional arguments passed to parent.
-        """
-        super().__init__(**kwargs)
-
-
-# Pydantic params class with a deprecated field
-class MyParams(BaseModel):
-    """Configuration parameters for MyService.
-
-    Parameters:
-        new_setting: Replacement for ``old_setting``.
-        old_setting: Legacy setting, no longer used.
-
-            .. deprecated:: 1.2.0
-                Use ``new_setting`` instead. Will be removed in 2.0.0.
-    """
-
-    new_setting: str = "default"
-    old_setting: str | None = None
-```
-
-## Service Implementation
-
-When adding a new service:
-
-1. Extend the appropriate base class (`STTService`, `TTSService`, `LLMService`, etc.)
-2. Implement required abstract methods
-3. Handle necessary frames
-4. By default, all frames should be pushed in the direction they came
-5. Push `ErrorFrame` on failures
-6. Add metrics tracking via `MetricsData` if relevant
-7. Follow the pattern of existing services in `src/pipecat/services/`
-
-## Testing
-
-Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames.

CHANGELOG.md.template

@@ -0,0 +1,62 @@
+# Changelog
+
+All notable changes to the **<project name>** SDK will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+Please make sure to add your changes to the appropriate categories:
+
+## [Unreleased]
+
+### Added
+
+<!-- for new functionality -->
+
+- n/a
+
+### Changed
+
+<!-- for changed functionality -->
+
+- n/a
+
+### Deprecated
+
+<!-- for soon-to-be removed functionality -->
+
+- n/a
+
+### Removed
+
+<!-- for removed functionality -->
+
+- n/a
+
+### Fixed
+
+<!-- for fixed bugs -->
+
+- n/a
+
+### Performance
+
+<!-- for performance-relevant changes -->
+
+- n/a
+
+### Security
+
+<!-- for security-relevant changes -->
+
+- n/a
+
+### Other
+
+<!-- for everything else -->
+
+- n/a
+
+## [0.1.0] - YYYY-MM-DD
+
+Initial release.

CLAUDE.md

@@ -1 +1,157 @@
-@AGENTS.md
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. It orchestrates audio/video, AI services, transports, and conversation pipelines using a frame-based architecture.
+
+## Common Commands
+
+```bash
+# Setup development environment
+uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp
+
+# Install pre-commit hooks
+uv run pre-commit install
+
+# Run all tests
+uv run pytest
+
+# Run a single test file
+uv run pytest tests/test_name.py
+
+# Run a specific test
+uv run pytest tests/test_name.py::test_function_name
+
+# Preview changelog
+uv run towncrier build --draft --version Unreleased
+
+# Lint and format check
+uv run ruff check
+uv run ruff format --check
+
+# Update dependencies (after editing pyproject.toml)
+uv lock && uv sync
+```
+
+## Architecture
+
+### Frame-Based Pipeline Processing
+
+All data flows as **Frame** objects through a pipeline of **FrameProcessors**:
+
+```
+[Processor1] → [Processor2] → ... → [ProcessorN]
+```
+
+**Key components:**
+
+- **Frames** (`src/pipecat/frames/frames.py`): Data units (audio, text, video) and control signals. Flow DOWNSTREAM (input→output) or UPSTREAM (acknowledgments/errors).
+
+- **FrameProcessor** (`src/pipecat/processors/frame_processor.py`): Base processing unit. Each processor receives frames, processes them, and pushes results downstream.
+
+- **Pipeline** (`src/pipecat/pipeline/pipeline.py`): Chains processors together.
+
+- **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel.
+
+- **Transports** (`src/pipecat/transports/`): Transports are frame processors used for external I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`, `BaseInputTransport` and `BaseOutputTransport`.
+
+- **Pipeline Task (`src/pipecat/pipeline/task.py`)**: Runs and manages a pipeline. Pipeline tasks send the first frame, `StartFrame`, to the pipeline in order for processors to know they can start processing and pushing frames. Pipeline tasks internally create a pipeline with two additional processors, a source processor before the user-defined pipeline and a sink processor at the end. Those are used for multiple things: error handling, pipeline task level events, heartbeat monitoring, etc.
+
+- **Pipeline Runner (`src/pipecat/pipeline/runner.py`)**: High-level entry point for executing pipeline tasks. Handles signal management (SIGINT/SIGTERM) for graceful shutdown and optional garbage collection. Run a single pipeline task with `await runner.run(task)` or multiple concurrently with `await asyncio.gather(runner.run(task1), runner.run(task2))`.
+
+- **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`.
+
+- **Serializers** (`src/pipecat/serializers/`): Convert frames to/from wire formats for WebSocket transports. `FrameSerializer` base class defines `serialize()` and `deserialize()`. Telephony serializers (Twilio, Plivo, Vonage, Telnyx, Exotel, Genesys) handle provider-specific protocols and audio encoding (e.g., μ-law).
+
+- **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels.
+
+- **Observers** (`src/pipecat/observers/`): Monitor frame flow without modifying the pipeline. Passed to `PipelineTask` via the `observers` parameter. Implement `on_process_frame()` and `on_push_frame()` callbacks.
+
+### Important Patterns
+
+- **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input
+
+- **Turn Management**: Turn management is done through `LLMUserAggregator` and
+  `LLMAssistantAggregator`, created with `LLMContextAggregatorPair`
+
+- **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively.
+
+- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. An `InterruptionFrame` carries an optional `asyncio.Event` that is set when the frame reaches the pipeline sink. If a processor stops an `InterruptionFrame` from propagating downstream (i.e., doesn't push it), it **must** call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()` callers.
+
+- **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`.
+
+- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to execute fast.
+
+- **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation.
+
+- **Error Handling**: Use `await self.push_error(msg, exception, fatal)` to push errors upstream. Services should use `fatal=False` (the default) so application code can handle errors and take action (e.g. switch to another service).
+
+### Key Directories
+
+| Directory                  | Purpose                                            |
+| -------------------------- | -------------------------------------------------- |
+| `src/pipecat/frames/`      | Frame definitions (100+ types)                     |
+| `src/pipecat/processors/`  | FrameProcessor base + aggregators, filters, audio  |
+| `src/pipecat/pipeline/`    | Pipeline orchestration                             |
+| `src/pipecat/services/`    | AI service integrations (60+ providers)            |
+| `src/pipecat/transports/`  | Transport layer (Daily, LiveKit, WebSocket, Local) |
+| `src/pipecat/serializers/` | Frame serialization for WebSocket protocols        |
+| `src/pipecat/observers/`   | Pipeline observers for monitoring frame flow       |
+| `src/pipecat/audio/`       | VAD, filters, mixers, turn detection, DTMF         |
+| `src/pipecat/turns/`       | User turn management                               |
+
+## Code Style
+
+- **Docstrings**: Google-style. Classes describe purpose; `__init__` has `Args:` section; dataclasses use `Parameters:` section.
+- **Linting**: Ruff (line length 100). Pre-commit hooks enforce formatting.
+- **Type hints**: Required for complex async code.
+- **Dataclass vs Pydantic**: Use `@dataclass` for frames and internal pipeline data (high-frequency, no validation needed). Use Pydantic `BaseModel` for configuration, parameters, metrics, and external API data (benefits from validation and serialization). Specifically:
+  - `@dataclass`: Frame types, context aggregator pairs, internal data containers
+  - `BaseModel`: Service `InputParams`, transport/VAD/turn params, metrics data, API request/response models, serializer params
+
+### Docstring Example
+
+```python
+class MyService(LLMService):
+    """Description of what the service does.
+
+    More detailed description.
+
+    Event handlers available:
+
+    - on_connected: Called when we are connected
+
+    Example::
+
+        @service.event_handler("on_connected")
+        async def on_connected(service, frame):
+            ...
+    """
+
+    def __init__(self, param1: str, **kwargs):
+        """Initialize the service.
+
+        Args:
+            param1: Description of param1.
+            **kwargs: Additional arguments passed to parent.
+        """
+        super().__init__(**kwargs)
+```
+
+## Service Implementation
+
+When adding a new service:
+
+1. Extend the appropriate base class (`STTService`, `TTSService`, `LLMService`, etc.)
+2. Implement required abstract methods
+3. Handle necessary frames
+4. By default, all frames should be pushed in the direction they came
+5. Push `ErrorFrame` on failures
+6. Add metrics tracking via `MetricsData` if relevant
+7. Follow the pattern of existing services in `src/pipecat/services/`
+
+## Testing
+
+Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames.

COMMUNITY_INTEGRATIONS.md

@@ -23,7 +23,7 @@ Create your integration following the patterns and examples shown in the "Integr
 Your repository must contain these components:
 
 - **Source code** - Complete implementation following Pipecat patterns
-- **Foundational example** - Single file example showing basic usage (see [Pipecat examples](https://github.com/pipecat-ai/pipecat/tree/main/examples))
+- **Foundational example** - Single file example showing basic usage (see [Pipecat examples](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational))
 - **README.md** - Must include:
   - Introduction and explanation of your integration
   - Installation instructions
@@ -65,25 +65,12 @@ Once your PR is submitted, post in the `#community-integrations` Discord channel
 
 #### Websocket-based Services
 
-**Base class:** `WebsocketSTTService`
-
-**Use for:** Services where you manage the websocket connection directly. Combines `STTService` with `WebsocketService` for automatic reconnection and keepalive support.
-
-**Examples:**
-
-- [CartesiaSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/cartesia/stt.py)
-- [ElevenLabsRealtimeSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/elevenlabs/stt.py)
-
-#### SDK-based Streaming Services
-
 **Base class:** `STTService`
 
-**Use for:** Streaming services where the provider's Python SDK manages the connection internally.
-
 **Examples:**
 
 - [DeepgramSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/deepgram/stt.py)
-- [GoogleSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/stt.py)
+- [SpeechmaticsSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/speechmatics/stt.py)
 
 #### File-based Services
 
@@ -121,59 +108,55 @@ Once your PR is submitted, post in the `#community-integrations` Discord channel
 
 #### Key requirements:
 
-- **`_process_context(self, context: LLMContext)`** — The main method that processes an LLM context and generates a response. Each LLM service overrides `process_frame` to extract context from `LLMContextFrame` and calls `_process_context`.
-
-- **`adapter_class`** — Class attribute pointing to a `BaseLLMAdapter` subclass. Defaults to `OpenAILLMAdapter`. Non-OpenAI services must implement their own adapter (see `src/pipecat/adapters/base_llm_adapter.py`) with methods:
-  - `get_llm_invocation_params(context)` — Extract provider-specific params from universal context
-  - `to_provider_tools_format(tools_schema)` — Convert standard tools to provider format
-  - `get_messages_for_logging(context)` — Format messages for logging
-  - Reference adapters: `src/pipecat/adapters/services/` (anthropic, gemini, bedrock, etc.)
-
 - **Frame sequence:** Output must follow this frame sequence pattern:
-  - `LLMFullResponseStartFrame` — Signals the start of an LLM response
-  - `LLMTextFrame` — Contains LLM content, typically streamed as tokens
-  - `LLMFullResponseEndFrame` — Signals the end of an LLM response
+  - `LLMFullResponseStartFrame` - Signals the start of an LLM response
+  - `LLMTextFrame` - Contains LLM content, typically streamed as tokens
+  - `LLMFullResponseEndFrame` - Signals the end of an LLM response
 
-- **Thought frames (reasoning models):** If the model supports extended thinking / chain-of-thought, emit thought frames alongside the response:
-  - `LLMThoughtStartFrame` — Signals the start of a thought
-  - `LLMThoughtTextFrame` — Contains thought content, streamed as tokens
-  - `LLMThoughtEndFrame` — Signals the end of a thought
-
-- **Context aggregation** is handled by the framework via `LLMContext` + `LLMContextAggregatorPair`. The LLM service just processes context it receives — no need to implement aggregators.
+- **Context aggregation:** Implement context aggregation to collect user and assistant content:
+  - Aggregators come in pairs with a `user()` instance and `assistant()` instance
+  - Context must adhere to the `LLMContext` universal format
+  - Aggregators should handle adding messages, function calls, and images to the context
 
 ### TTS (Text-to-Speech) Services
 
-#### WebsocketTTSService
+#### AudioContextWordTTSService
 
-**Use for:** Websocket-based streaming services (with or without word timestamps)
+**Use for:** Websocket-based services supporting word/timestamp alignment
 
-**Examples:**
+**Example:**
 
 - [CartesiaTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/cartesia/tts.py)
-- [ElevenLabsTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/elevenlabs/tts.py)
 
 #### InterruptibleTTSService
 
-**Use for:** Websocket-based services without word timestamps that reconnect on interruption (e.g. don't support a context ID or interruption message)
+**Use for:** Websocket-based services without word/timestamp alignment, requiring disconnection on interruption
 
 **Example:**
 
 - [SarvamTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/sarvam/tts.py)
 
+#### WordTTSService
+
+**Use for:** HTTP-based services supporting word/timestamp alignment
+
+**Example:**
+
+- [ElevenLabsHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/elevenlabs/tts.py)
+
 #### TTSService
 
-**Use for:** HTTP-based services (word timestamps are supported in the base class)
+**Use for:** HTTP-based services without word/timestamp alignment
 
-**Examples:**
+**Example:**
 
 - [GoogleHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/tts.py)
-- [OpenAITTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/openai/tts.py)
 
 #### Key requirements:
 
-- For websocket services, use asyncio WebSocket implementation
+- For websocket services, use asyncio WebSocket implementation (required for v13+ support)
 - Handle idle service timeouts with keepalives
-- TTS services push both audio (`TTSAudioRawFrame`) and text (`TTSTextFrame`) frames
+- TTSServices push both audio (`TTSRawAudioFrame`) and text (`TTSTextFrame`) frames
 
 ### Telephony Serializers
 
@@ -217,25 +200,14 @@ Vision services process images and provide analysis such as descriptions, object
 
 #### Key requirements:
 
-- Must implement `run_vision` method that takes a `UserImageRawFrame` and returns an `AsyncGenerator[Frame, None]`
-- The method processes the image frame and yields frames with analysis results
-- Must yield the frame sequence: `VisionFullResponseStartFrame`, `VisionTextFrame`, `VisionFullResponseEndFrame`
+- Must implement `run_vision` method that takes an `LLMContext` and returns an `AsyncGenerator[Frame, None]`
+- The method processes the latest image in the context and yields frames with analysis results
+- Typically yields `TextFrame` objects containing descriptions or answers
 
 ## Implementation Guidelines
 
 ### Naming Conventions
 
-#### Package and Repository Naming
-
-Use the `pipecat-{vendor}` naming convention for your PyPI package and repository:
-
-- `pipecat-{vendor}` — for single-service integrations (e.g., `pipecat-deepdub`)
-- `pipecat-{vendor}-{type}` — when a vendor offers multiple service types (e.g., `pipecat-upliftai-stt`, `pipecat-upliftai-tts`)
-
-This convention makes community packages easily discoverable via PyPI search and clearly identifies them as part of the Pipecat ecosystem.
-
-#### Class Naming
-
 - **STT:** `VendorSTTService`
 - **LLM:** `VendorLLMService`
 - **TTS:**
@@ -259,105 +231,49 @@ def can_generate_metrics(self) -> bool:
     return True
 ```
 
-### Service Settings
+### Dynamic Settings Updates
 
-Every AI service (STT, LLM, TTS, image generation, etc.) exposes a **Settings dataclass** that serves two roles:
+STT, LLM, and TTS services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`).
 
-1. **Store mode** — the service's `self._settings` holds the current value of every runtime-updatable field.
-2. **Delta mode** — an update frame (e.g. `TTSUpdateSettingsFrame`) specifies only the fields that should change; unspecified fields remain `NOT_GIVEN`.
-
-#### Defining your Settings class
-
-Extend `STTSettings`, `TTSSettings`, `LLMSettings`, or `ImageGenSettings` (or, if your service directly subclasses `AIService`, `ServiceSettings`). The base classes already provide common fields (e.g. `model`, `voice`, `language`). You only need to add **service-specific knobs that should be runtime-updatable**:
+Each service declares a settings dataclass that extends the appropriate base (`STTSettings`, `TTSSettings`, `LLMSettings`). Fields default to `NOT_GIVEN` so that update objects can represent sparse deltas:
 
 ```python
 from dataclasses import dataclass, field
 
-from pipecat.services.settings import TTSSettings, NOT_GIVEN
+from pipecat.services.settings import STTSettings, NOT_GIVEN
 
 @dataclass
-class MyTTSSettings(TTSSettings):
-    """Settings for MyTTS service.
+class MySTTSettings(STTSettings):
+    """Settings for my STT service.
 
     Parameters:
-        speaking_rate: Speed multiplier (0.5–2.0).
+        region: Cloud region for the service.
     """
 
-    speaking_rate: float | None = field(default_factory=lambda: NOT_GIVEN)
+    region: str = field(default_factory=lambda: NOT_GIVEN)
 ```
 
-**What goes in Settings vs. `__init__` params:**
-
-| Belongs in Settings                                      | Stays as `__init__` params                |
-| -------------------------------------------------------- | ----------------------------------------- |
-| Model name, voice, language                              | API keys, auth tokens                     |
-| Service-specific tuning knobs (rate, pitch, temperature) | Base URLs, endpoint overrides             |
-| Anything users may want to change mid-session            | Audio encoding, sample format             |
-|                                                          | Connection parameters (timeouts, retries) |
-
-The rule of thumb: if a caller might send an update frame to change it at runtime, it belongs in Settings. Everything else is init-only config stored as `self._xxx`.
-
-#### Wiring settings into `__init__`
-
-Accept an **optional** `settings` parameter. Build a `default_settings` object with all fields set to real values, then merge any caller overrides with `apply_update`.
-
-Add a `Settings` **class attribute** that points to your settings dataclass. This lets callers access the settings class through the service itself (e.g. `MyTTSService.Settings(...)`) without a separate import:
+The service stores its current settings in `self._settings` and declares the type with a class-level annotation for editor support:
 
 ```python
-from typing import Optional
+class MySTTService(STTService):
+    _settings: MySTTSettings
 
-class MyTTSService(TTSService):
-    Settings = MyTTSSettings
-    _settings: Settings
-
-    def __init__(
-        self,
-        *,
-        api_key: str,
-        settings: Optional[Settings] = None,
-        **kwargs,
-    ):
-        # 1. Defaults — every field has a real value (store mode).
-        default_settings = self.Settings(
-            model="my-model-v1",
-            voice="default-voice",
-            language="en",
-            speaking_rate=1.0,
+    def __init__(self, *, model: str, language: str, region: str, **kwargs):
+        # An initial value should be provided for every settings field.
+        # This will be validated at service start.
+        # (If you track sample_rate, it can be a placeholder value like 0; see
+        # "Sample Rate Handling").
+        super().__init__(
+            settings=MySTTSettings(model=model, language=language, region=region), **kwargs
         )
-
-        # 2. Merge caller overrides (only given fields win).
-        if settings is not None:
-            default_settings.apply_update(settings)
-
-        # 3. Pass the fully-populated settings to the base class.
-        super().__init__(settings=default_settings, **kwargs)
-
-        # 4. Init-only config stored separately.
-        self._api_key = api_key
 ```
 
-This pattern lets callers override only what they care about:
-
-```python
-# Uses all defaults
-svc = MyTTSService(api_key="sk-xxx")
-
-# Overrides just the voice — access Settings through the service class
-svc = MyTTSService(
-    api_key="sk-xxx",
-    settings=MyTTSService.Settings(voice="custom-voice"),
-)
-```
-
-#### Reacting to runtime changes
-
-AI services support runtime configuration changes via `*UpdateSettingsFrame`s (e.g. `STTUpdateSettingsFrame`, `TTSUpdateSettingsFrame`, `LLMUpdateSettingsFrame`).
-
 To react to runtime setting changes, override `_update_settings`. The base implementation applies the delta to `self._settings` and returns a `dict` mapping each changed field name to its **pre-update** value. Your override should call `super()` first, then act on the changed fields. A common implementation might look like:
 
 ```python
-async def _update_settings(self, update: TTSSettings) -> dict[str, Any]:
-    """Apply a settings update, reconfiguring the connection if needed."""
+async def _update_settings(self, update: STTSettings) -> dict[str, Any]:
+    """Apply a settings update, reconfiguring the recognizer if needed."""
     changed = await super()._update_settings(update)
 
     if not changed:
@@ -376,7 +292,7 @@ Note that, in this example, the service requires a reconnect to apply the new la
 If your service can't yet apply certain settings at runtime, call `self._warn_unhandled_updated_settings(changed)` with any unhandled field names so users get a clear log message:
 
 ```python
-async def _update_settings(self, update: TTSSettings) -> dict[str, Any]:
+async def _update_settings(self, update: STTSettings) -> dict[str, Any]:
     changed = await super()._update_settings(update)
 
     if not changed:
@@ -409,7 +325,7 @@ Note that `self.sample_rate` is a `@property` set in the TTSService base class,
 
 Use Pipecat's tracing decorators:
 
-- **STT:** `@traced_stt` - decorate `_handle_transcription(self, transcript, is_final, language)` (the standard method name convention)
+- **STT:** `@traced_stt` - decorate a function that handles `transcript`, `is_final`, `language` as args
 - **LLM:** `@traced_llm` - decorate the `_process_context()` method
 - **TTS:** `@traced_tts` - decorate the `run_tts()` method
 
@@ -417,9 +333,8 @@ Use Pipecat's tracing decorators:
 
 ### Packaging and Distribution
 
-- Name your package `pipecat-{vendor}` (see [Naming Conventions](#naming-conventions))
 - Use [uv](https://docs.astral.sh/uv/) for packaging (encouraged)
-- Publish to PyPI for easier installation
+- Consider releasing to PyPI for easier installation
 - Follow semantic versioning principles
 - Maintain a changelog
 
@@ -432,15 +347,17 @@ For REST-based communication, use aiohttp. Pipecat includes this as a required d
 - Wrap API calls in appropriate try/catch blocks
 - Handle rate limits and network failures gracefully
 - Provide meaningful error messages
-- When errors occur, raise exceptions AND push errors to notify the pipeline:
+- When errors occur, raise exceptions AND push `ErrorFrame`s to notify the pipeline:
 
 ```python
+from pipecat.frames.frames import ErrorFrame
+
 try:
     # Your API call
     result = await self._make_api_call()
 except Exception as e:
-    # Push error upstream to notify the pipeline
-    await self.push_error(f"{self} error: {e}", exception=e)
+    # Push error frame to pipeline
+    await self.push_error(ErrorFrame(error=f"{self} error: {e}"))
     # Raise or handle as appropriate
     raise
 ```

README.md

@@ -8,7 +8,7 @@
 
 **Pipecat** is an open-source Python framework for building real-time voice and multimodal conversational agents. Orchestrate audio and video, AI services, different transports, and conversation pipelines effortlessly—so you can focus on what makes your agent unique.
 
-> Want to dive right in? Run `pipecat init quickstart` or follow the [quickstart guide](https://docs.pipecat.ai/getting-started/quickstart).
+> Want to dive right in? Try the [quickstart](https://docs.pipecat.ai/getting-started/quickstart).
 
 ## 🚀 What You Can Build
 
@@ -28,10 +28,6 @@
 
 ## 🌐 Pipecat Ecosystem
 
-### 🧩 Multi-agent systems
-
-Need multiple AI agents working together? [Pipecat Subagents](https://github.com/pipecat-ai/pipecat-subagents) lets you build distributed multi-agent systems where each agent runs its own pipeline and communicates through a shared message bus. Hand off conversations between specialists, dispatch background tasks, and scale agents across processes or machines.
-
 ### 📱 Client SDKs
 
 Building client applications? You can connect to Pipecat from any platform using our official SDKs:
@@ -69,10 +65,6 @@ claude plugin marketplace add pipecat-ai/skills
 
 and install any of the available plugins.
 
-### 🧩 Community Integrations
-
-Build and share your own Pipecat service integrations! Browse existing [community integrations](https://docs.pipecat.ai/api-reference/server/services/community-integrations) or check out our [guide](COMMUNITY_INTEGRATIONS.md) to create your own.
-
 ### 📺️ Pipecat TV Channel
 
 Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.youtube.com/playlist?list=PLzU2zoMTQIHjqC3v4q2XVSR3hGSzwKFwH) channel.
@@ -83,28 +75,27 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
     <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/simple-chatbot/image.png" width="400" /></a>&nbsp;
     <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/storytelling-chatbot/image.png" width="400" /></a>
     <br/>
-    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/daily-multi-translation"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/daily-multi-translation/image.png" width="400" /></a>&nbsp;
-    <a href="https://github.com/pipecat-ai/pipecat/blob/main/examples/vision/vision-moondream.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/assets/moondream.png" width="400" /></a>
+    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>&nbsp;
+    <a href="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/12-describe-video.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/assets/moondream.png" width="400" /></a>
 </p>
 
 ## 🧩 Available services
 
-| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
-| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/api-reference/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/api-reference/server/services/stt/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/api-reference/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/api-reference/server/services/stt/gladia), [Google](https://docs.pipecat.ai/api-reference/server/services/stt/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/groq), [Mistral](https://docs.pipecat.ai/api-reference/server/services/stt/mistral), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/stt/nvidia), [OpenAI (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/openai), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/api-reference/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/api-reference/server/services/stt/whisper), [xAI](https://docs.pipecat.ai/api-reference/server/services/stt/xai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/api-reference/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/api-reference/server/services/llm/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/api-reference/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/api-reference/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/api-reference/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/api-reference/server/services/llm/grok), [Groq](https://docs.pipecat.ai/api-reference/server/services/llm/groq), [Inception](https://docs.pipecat.ai/api-reference/server/services/llm/inception), [Mistral](https://docs.pipecat.ai/api-reference/server/services/llm/mistral), [Nebius](https://docs.pipecat.ai/api-reference/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/api-reference/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/api-reference/server/services/llm/nvidia), [Ollama](https://docs.pipecat.ai/api-reference/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/llm/openai), [OpenAI Responses](https://docs.pipecat.ai/api-reference/server/services/llm/openai-responses), [OpenRouter](https://docs.pipecat.ai/api-reference/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/api-reference/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/api-reference/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/api-reference/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/api-reference/server/services/llm/together)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| Text-to-Speech      | [Async](https://docs.pipecat.ai/api-reference/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/api-reference/server/services/tts/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/api-reference/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/api-reference/server/services/tts/fish), [Google](https://docs.pipecat.ai/api-reference/server/services/tts/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/api-reference/server/services/tts/groq), [Hume](https://docs.pipecat.ai/api-reference/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/api-reference/server/services/tts/inworld), [Kokoro](https://docs.pipecat.ai/api-reference/server/services/tts/kokoro), [LMNT](https://docs.pipecat.ai/api-reference/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/api-reference/server/services/tts/minimax), [Mistral](https://docs.pipecat.ai/api-reference/server/services/tts/mistral), [Neuphonic](https://docs.pipecat.ai/api-reference/server/services/tts/neuphonic), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/tts/nvidia), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/tts/openai), [Piper](https://docs.pipecat.ai/api-reference/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/api-reference/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/api-reference/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/tts/sarvam), [Smallest](https://docs.pipecat.ai/api-reference/server/services/tts/smallest), [Soniox](https://docs.pipecat.ai/api-reference/server/services/tts/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/tts/speechmatics), [xAI](https://docs.pipecat.ai/api-reference/server/services/tts/xai), [XTTS](https://docs.pipecat.ai/api-reference/server/services/tts/xtts) |
-| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/api-reference/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/api-reference/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/api-reference/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/api-reference/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/api-reference/server/services/s2s/ultravox),                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
-| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/api-reference/server/services/transport/fastapi-websocket), [LiveKit (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc), [Vonage (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/vonage), [WebSocket Server](https://docs.pipecat.ai/api-reference/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/api-reference/server/services/transport/whatsapp), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
-| Serializers         | [Exotel](https://docs.pipecat.ai/api-reference/server/services/serializers/exotel), [Genesys](https://docs.pipecat.ai/api-reference/server/services/serializers/genesys), [Plivo](https://docs.pipecat.ai/api-reference/server/services/serializers/plivo), [Twilio](https://docs.pipecat.ai/api-reference/server/services/serializers/twilio), [Telnyx](https://docs.pipecat.ai/api-reference/server/services/serializers/telnyx), [Vonage](https://docs.pipecat.ai/api-reference/server/services/serializers/vonage)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
-| Video               | [HeyGen](https://docs.pipecat.ai/api-reference/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/api-reference/server/services/transport/lemonslice), [Tavus](https://docs.pipecat.ai/api-reference/server/services/video/tavus), [Simli](https://docs.pipecat.ai/api-reference/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
-| Memory              | [mem0](https://docs.pipecat.ai/api-reference/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
-| Vision & Image      | [fal](https://docs.pipecat.ai/api-reference/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/api-reference/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/api-reference/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
-| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/api-reference/server/utilities/audio/silero-vad-analyzer), [Krisp Viva](https://docs.pipecat.ai/guides/features/krisp-viva), [Koala](https://docs.pipecat.ai/api-reference/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/api-reference/server/utilities/audio/aic-filter), [RNNoise](https://docs.pipecat.ai/api-reference/server/utilities/audio/rnnoise-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
-| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/api-reference/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/api-reference/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
-| Community           | [Browse community integrations →](https://docs.pipecat.ai/api-reference/server/services/community-integrations)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                                                                                                                                                             |
+| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                                                                                                                                                                                                                                                                                                                                                                                               |
+| Text-to-Speech      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
+| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox),                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+| Serializers         | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| Video               | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+| Memory              | [mem0](https://docs.pipecat.ai/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| Vision & Image      | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
 
-📚 [View full services documentation →](https://docs.pipecat.ai/api-reference/server/services/supported-services)
+📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
 
 ## ⚡ Getting started
 
@@ -146,15 +137,15 @@ You can get started with Pipecat running on your local machine, then move your a
 
 ## 🧪 Code examples
 
-- [Foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples) — small snippets that build on each other, introducing one or two concepts at a time
+- [Foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational) — small snippets that build on each other, introducing one or two concepts at a time
 - [Example apps](https://github.com/pipecat-ai/pipecat-examples) — complete applications that you can use as starting points for development
 
 ## 🛠️ Contributing to the framework
 
 ### Prerequisites
 
-**Minimum Python Version:** 3.11
-**Recommended Python Version:** >= 3.12
+**Minimum Python Version:** 3.10
+**Recommended Python Version:** 3.12
 
 ### Setup Steps
 
@@ -170,6 +161,7 @@ You can get started with Pipecat running on your local machine, then move your a
    ```bash
    uv sync --group dev --all-extras \
      --no-extra gstreamer \
+     --no-extra krisp \
      --no-extra local \
    ```
 

changelog/3696.added.md

@@ -0,0 +1 @@
+- Added `TextAggregationMetricsData` metric measuring the time from the first LLM token to the first complete sentence, representing the latency cost of sentence aggregation in the TTS pipeline.

changelog/3696.changed.md

@@ -0,0 +1 @@
+- Added `text_aggregation_mode` parameter to `TTSService` and all TTS subclasses with a new `TextAggregationMode` enum (`SENTENCE`, `TOKEN`). All text now flows through text aggregators regardless of mode, enabling pattern detection and tag handling in TOKEN mode.

changelog/3696.deprecated.md

@@ -0,0 +1 @@
+- ⚠️ Deprecated `aggregate_sentences` parameter on `TTSService` and all TTS subclasses. Use `text_aggregation_mode=TextAggregationMode.SENTENCE` or `text_aggregation_mode=TextAggregationMode.TOKEN` instead.

changelog/3714.added.md

@@ -0,0 +1,19 @@
+- Added support for using strongly-typed objects instead of dicts for updating service settings at runtime.
+
+  Instead of, say:
+
+  ```python
+  await task.queue_frame(
+      STTUpdateSettingsFrame(settings={"language": Language.ES})
+  )
+  ```
+
+  you'd do:
+
+  ```python
+  await task.queue_frame(
+      STTUpdateSettingsFrame(delta=DeepgramSTTSettings(language=Language.ES))
+  )
+  ```
+
+  Each service now vends strongly-typed classes like `DeepgramSTTSettings` representing the service's runtime-updatable settings.

changelog/3714.changed.md

@@ -0,0 +1 @@
+- ⚠️ Refactored runtime-updatable service settings to use strongly-typed classes (`TTSSettings`, `STTSettings`, `LLMSettings`, and service-specific subclasses) instead of plain dicts. Each service's `_settings` now holds these strongly-typed objects. For service maintainers, see changes in COMMUNITY_INTEGRATIONS.md.

changelog/3714.deprecated.2.md

@@ -0,0 +1 @@
+- Dict-based `*UpdateSettingsFrame(settings={...})` is deprecated in favor of passing typed settings delta objects with `*UpdateSettingsFrame(delta={...})`.

changelog/3714.deprecated.md

@@ -0,0 +1,3 @@
+- Deprecated `set_model()`, `set_voice()`, and `set_language()` on AI services in favor of runtime updates via `TTSUpdateSettingsFrame`, `STTUpdateSettingsFrame`, and `LLMUpdateSettingsFrame`.
+
+  ⚠️ Note, too, a subtle behavior change in these deprecated methods. Whereas previously only `set_language()` caused the service to actually react to the update (e.g. by reconnecting to a remote service so it an pick up the change), now all these methods do. This change was made as part of a refactor making them all work the same way under the hood.

changelog/3759.performance.md

@@ -0,0 +1 @@
+- Switched `GradiumTTSService` from `InterruptibleWordTTSService` to `AudioContextWordTTSService`, eliminating websocket disconnect/reconnect on every interruption by using `client_req_id`-based multiplexing.

changelog/3786.changed.md

@@ -0,0 +1 @@
+- Word timestamp support has been moved from `WordTTSService` into `TTSService` via a new `supports_word_timestamps` parameter. Services that previously extended `WordTTSService`, `AudioContextWordTTSService`, or `WebsocketWordTTSService` now pass `supports_word_timestamps=True` to their parent `__init__` instead.

changelog/3786.deprecated.md

@@ -0,0 +1,5 @@
+- Deprecated `WordTTSService`, `WebsocketWordTTSService`, `AudioContextWordTTSService`, and `InterruptibleWordTTSService`. Use their non-word counterparts with `supports_word_timestamps=True` instead:
+  - `WordTTSService` → `TTSService(supports_word_timestamps=True)`
+  - `WebsocketWordTTSService` → `WebsocketTTSService(supports_word_timestamps=True)`
+  - `AudioContextWordTTSService` → `AudioContextTTSService(supports_word_timestamps=True)`
+  - `InterruptibleWordTTSService` → `InterruptibleTTSService(supports_word_timestamps=True)`

changelog/3803.fixed.md

@@ -0,0 +1 @@
+- Fixed Poetry compatibility by inlining `local-smart-turn-v3` dependencies (`transformers`, `onnxruntime`) into core dependencies instead of using a self-referential extra.

changelog/3803.removed.md

@@ -0,0 +1 @@
+- Removed `local-smart-turn-v3` optional extra from `pyproject.toml`. The `transformers` and `onnxruntime` packages are now always installed as core dependencies since they are required by the default turn stop strategy, `TurnAnalyzerUserTurnStopStrategy` which uses `LocalSmartTurnAnalyzerV3`.

changelog/3806.added.md

@@ -0,0 +1 @@
+- Added `output_medium` parameter to `AgentInputParams` and `OneShotInputParams` in Ultravox service to control initial output medium (text or voice) at call creation time.

changelog/3806.changed.2.md

@@ -0,0 +1 @@
+- Improved Ultravox TTFB measurement accuracy by using VAD speech end time instead of `UserStoppedSpeakingFrame` timing.

changelog/3806.changed.md

@@ -0,0 +1 @@
+- Aligned `UltravoxRealtimeLLMService` frame handling with OpenAI/Gemini realtime services: added `InterruptionFrame` handling with metrics cleanup, processing metrics at response boundaries, and improved agent transcript handling for both voice and text output modalities.

changelog/3807.changed.md

@@ -0,0 +1 @@
+- Updated `OpenAIRealtimeLLMService` default model to `gpt-realtime-1.5`.

changelog/3808.fixed.md

@@ -0,0 +1 @@
+- Fixed `SentryMetrics` method signatures to match updated `FrameProcessorMetrics` base class, resolving `TypeError` when using `start_time`/`end_time` keyword arguments.

changelog/3809.added.md

@@ -0,0 +1 @@
+- Added `TurnMetricsData` as a generic metrics class for turn detection, with e2e processing time measurement. `KrispVivaTurn` now emits `TurnMetricsData` with `e2e_processing_time_ms` tracking the interval from VAD speech-to-silence transition to turn completion.

changelog/3809.changed.md

@@ -0,0 +1 @@
+- Added `api_key` parameter to `KrispVivaSDKManager`, `KrispVivaTurn`, and `KrispVivaFilter` for Krisp SDK v1.6.1+ licensing. Falls back to `KRISP_VIVA_API_KEY` environment variable.

changelog/3809.deprecated.md

@@ -0,0 +1 @@
+- Deprecated `SmartTurnMetricsData` in favor of `TurnMetricsData`. `BaseSmartTurn` now emits `TurnMetricsData` directly.

changelog/3811.changed.md

@@ -0,0 +1 @@
+- Bumped `nltk` minimum version from 3.9.1 to 3.9.3 to resolve a security vulnerability.

changelog/3813.fixed.md

@@ -0,0 +1 @@
+- Fixed STT TTFB metrics not being reported for `SonioxSTTService` and `AWSTranscribeSTTService` due to missing `can_generate_metrics()` override.

changelog/3814.added.md

@@ -0,0 +1 @@
+- Added `on_audio_context_interrupted()` and `on_audio_context_completed()` callbacks to `AudioContextTTSService`. Subclasses can override these to perform provider-specific cleanup instead of overriding `_handle_interruption()`.

changelog/3814.fixed.md

@@ -0,0 +1 @@
+- Fixed an issue where `AudioContextTTSService`-based providers (AsyncAI, ElevenLabs, Inworld, Rime) did not close or clean up their server-side audio contexts after normal speech completion, only on interruption.

changelog/3819.changed.md

@@ -0,0 +1,4 @@
+- `ServiceSettingsUpdateFrame`s are now `UninterruptibleFrame`s. Generally speaking, you don't want a user interruption to prevent a service setting change from going into effect. Note that you usually don't use `ServiceSettingsUpdateFrame` directly, you use one of its subclasses:
+  - `LLMUpdateSettingsFrame`
+  - `TTSUpdateSettingsFrame`
+  - `STTUpdateSettingsFrame`

changelog/3822.fixed.md

@@ -0,0 +1 @@
+- Fixed STT TTFB metrics measuring timeout expiry time instead of actual transcript arrival time.

changelog/3825.fixed.md

@@ -0,0 +1 @@
+- Fixed `InterimTranscriptionFrame` and `TranslationFrame` being unintentionally pushed downstream in `LLMUserAggregator`. They are now consumed like `TranscriptionFrame`.

changelog/3828.fixed.md

@@ -0,0 +1 @@
+- Fixed misleading "Empty audio frame received for STT service" warnings when using audio filters (e.g. `RNNoiseFilter`, `KrispVivaFilter`, `AICFilter`) that buffer audio internally.

changelog/3837.fixed.md

@@ -0,0 +1 @@
+- Fixed issues with `RimeNonJsonTTSService` where trailing punctuation is sometimes vocalized

changelog/3838.removed.md

@@ -0,0 +1 @@
+- ⚠️ Removed `PlayHTTTSService` and `PlayHTHttpTTSService`. PlayHT has been shut down and is no longer available.

changelog/3851.removed.md

@@ -0,0 +1 @@
+- ⚠️ Removed `ProcessingMetricsData` and all `start_processing_metrics()`/`stop_processing_metrics()` methods from `FrameProcessor` and `FrameProcessorMetrics`. These metrics were inconsistently implemented across services and overlapped with the better-defined TTFB metric. TTFB, LLM token usage, TTS character usage, and text aggregation metrics are unaffected.

changelog/4052.added.md

@@ -1 +0,0 @@
-- Added `VonageVideoConnectorTransport`, a new transport integration for real-time Vonage WebRTC sessions using the Vonage Video Connector library.

changelog/4306.fixed.md

@@ -1 +0,0 @@
-- Fixed Azure TTS last word being missed by observers and RTVI UI. The completion signal was racing with word timestamp processing, causing the final word's `TTSTextFrame` to arrive after `TTSStoppedFrame`. Completion is now routed through the word boundary queue to ensure all words are processed before signaling stream end.

changelog/4380.fixed.2.md

@@ -1 +0,0 @@
-- Fixed `BaseOutputTransport` reordering frames that share the same presentation timestamp. Frames with equal PTS values are now emitted in insertion order, preventing subtle audio/text sequencing bugs when multiple frames arrive at the same time.

changelog/4380.fixed.3.md

@@ -1 +0,0 @@
-- Fixed Cartesia word timestamps leaking SSML tag text (e.g. `<spell>`, `<emotion>`, `<break>`) into word entries. Tags are now stripped before processing, so word-to-text attribution remains accurate when SSML markup is present in the TTS input.

changelog/4380.fixed.4.md

@@ -1 +0,0 @@
-- Fixed `TTSTextFrame` entries losing their original text structure when word timestamps are enabled. Each `TTSTextFrame` now carries a `raw_text` field containing the corresponding span of the original LLM-produced text (including pattern delimiters such as `<card>4111 1111 1111 1111</card>`), so the assistant context receives properly-tagged content rather than the cleaned words returned by the TTS provider. Also handles words that straddle two sentence boundaries by splitting them and attributing each part to its correct source frame.

changelog/4380.fixed.md

@@ -1 +0,0 @@
-- Fixed skipped TTS frames (e.g. code blocks filtered via `skip_aggregator_types`) being emitted to the assistant context immediately instead of waiting for preceding spoken frames to finish. They now hold their position in the frame sequence and are flushed only after all earlier spoken sentences are complete, keeping context ordering correct.

changelog/4423.added.md

@@ -1 +0,0 @@
-- Added `InceptionLLMService` for Inception's Mercury 2 diffusion reasoning model, with support for `reasoning_effort` and `realtime` settings.

changelog/4442.added.2.md

@@ -1 +0,0 @@
-- Added `GET /status` endpoint to the development runner that reports which transports the running instance accepts (all by default, or the single transport passed via `-t`).

changelog/4442.added.md

@@ -1 +0,0 @@
-- Added plain WebSocket transport support to the development runner. Bots can now accept connections from non-telephony WebSocket clients (e.g., browser apps using protobuf framing) via the `/ws-client` endpoint alongside other transports.

changelog/4442.changed.md

@@ -1 +0,0 @@
-- ⚠️ The development runner now supports all transports (WebRTC, Daily, telephony, plain WebSocket) simultaneously from a single server. The `/start` endpoint accepts a `"transport"` field to select the transport per-request; omitting `-t` at startup enables all transports instead of defaulting to WebRTC. The Daily browser-redirect route moved from `GET /` to `GET /daily`.

changelog/4493.added.md

@@ -1 +0,0 @@
-- Added `pipecat.workers`, a worker-based agent framework folded in from the standalone `pipecat-subagents` package. Workers inherit from `BaseWorker`, share a `WorkerBus`, register in a `WorkerRegistry`, and exchange typed work via `@job` handlers. `LLMWorker` and `LLMContextWorker` provide ready-made LLM-driven workers. `PipelineRunner.spawn(worker)` registers fire-and-forget workers alongside the main pipeline worker.

changelog/4493.changed.2.md

@@ -1 +0,0 @@
-- ⚠️ `FrameProcessorSetup.pipeline_worker` and `FunctionCallParams.pipeline_worker` are now mandatory fields, and `FrameProcessor.pipeline_worker` raises if read before `setup()` instead of returning `None`. Real-world code (frame processors set up by `PipelineWorker`, tool handlers invoked by `LLMService`) is unaffected; only callers that construct these dataclasses by hand (typically tests) now have to supply a `pipeline_worker` reference.

changelog/4493.changed.md

@@ -1 +0,0 @@
-- `PipelineWorker` now inherits from `BaseWorker`, so every pipeline worker is also a bus participant. It accepts a new optional `bridged=()` parameter that auto-wraps the pipeline with bus edge processors, letting the worker exchange frames with other bridged workers over the shared `WorkerBus`. The bus is supplied by `PipelineRunner` via `worker.attach(registry=..., bus=...)` instead of through the constructor.

changelog/4507.fixed.md

@@ -1 +0,0 @@
-- Fixed `ElevenLabsSTTService` crashing when `language` was passed as `None`. When `language` is not set, the service now lets ElevenLabs auto-detect the audio language.

changelog/4514.fixed.md

@@ -1 +0,0 @@
-- Fixed websocket STT connection setup failures so services clear stale websocket state and emit non-fatal error frames, allowing `ServiceSwitcher` failover to keep agents running.

changelog/4521.added.md

@@ -1 +0,0 @@
-- Added `max_endpoint_delay_ms` to `SonioxSTTService.Settings`, controlling the maximum delay (500-3000 ms) before endpoint detection finalizes a turn.

changelog/4521.changed.md

@@ -1 +0,0 @@
-- `SonioxSTTService` now applies settings updates (e.g. via `STTUpdateSettingsFrame`) using a graceful reconnect instead of a hard disconnect/reconnect, preserving the service's reconnect retry behavior.

changelog/4521.removed.md

@@ -1 +0,0 @@
-- Removed the unsupported Georgian (`Language.KA`) language mapping from `SonioxSTTService`.

changelog/4522.changed.md

@@ -1 +0,0 @@
-- Updated the default p99 TTFS latency values for Smallest AI, Mistral, and XAI STT so turn stop timing uses measured values instead of the conservative fallback.

changelog/4524.changed.md

@@ -1 +0,0 @@
-- Updated the development runner startup banner to show the prebuilt client URL once and list enabled or disabled transports with install hints.

changelog/4524.fixed.md

@@ -1 +0,0 @@
-- Fixed the development runner so missing optional transport dependencies disable only their related routes instead of failing startup in all-transport mode.

changelog/4527.fixed.md

@@ -1 +0,0 @@
-- Fixed a race in `ElevenLabsTTSService` where the periodic keepalive could be sent for a new turn's context before that context's `voice_settings` initialization message, causing ElevenLabs to close the WebSocket with a 1008 policy violation (`voice_settings field must be provided in the first message ...`). The keepalive now only targets a context once its context-init has been sent.

changelog/4531.changed.md

@@ -1 +0,0 @@
-- Bumped `pipecat-ai-prebuilt` to 1.0.1 in the `runner` extra, updating the prebuilt client UI served by the development runner.

changelog/_template.md.j2

@@ -5,7 +5,7 @@
 
 {% for text, values in sections[section][category].items() %}
 {{ text }}
-  (PR {{ values|join(', ') }})
+(PR {{ values|join(', ') }})
 
 {% endfor %}
 {% endfor %}

changelog/xxxx.added.2.md

@@ -1 +0,0 @@
-- Added `LLMService.append_system_instruction(...)`, which composes durable text onto a user-provided system instruction (alongside the turn-completion and async-tool-cancellation instructions) so it is prepended on every inference and survives context-message resets.

changelog/xxxx.added.md

@@ -1,3 +0,0 @@
-- Added `pipecat.workers.ui.UIWorker`, an `LLMContextWorker` that observes and drives a client GUI over the RTVI UI channel: it stores live accessibility snapshots, auto-injects `<ui_state>` into the LLM context before every inference (via the LLM's `on_before_process_frame` hook), dispatches client events to `@on_ui_event` handlers, and sends UI commands (`scroll_to`, `highlight`, `select_text`, `click`, `set_input_value`) back to the client. The optional `ReplyToolMixin` exposes a bundled `reply` tool, and `user_job_group(...)` surfaces fan-out work to the client as cancellable task cards. A native RTVI⇄bus UI bridge is built into `PipelineWorker` (active whenever RTVI is enabled), so no decorator or manual wiring is needed: inbound UI messages are broadcast on the bus as `BusUIEventMessage`, and outbound `BusUICommandMessage` / `BusUITask*` carriers are translated into RTVI frames for the client.
-
-- `UIWorker` auto-injects the UI wire-format guide (`UI_STATE_PROMPT_GUIDE`) into its LLM's system instruction by default, via a `prompt_guide` parameter — pass your own string to override the guide, or `None` to disable. Apps no longer need to concatenate `UI_STATE_PROMPT_GUIDE` into the LLM's `system_instruction` by hand.

docs/api/README.md

@@ -1,60 +1,108 @@
-# Pipecat API Documentation
+# Pipecat Documentation
 
-This directory contains the source files for auto-generating Pipecat's API reference documentation.
+This directory contains the source files for auto-generating Pipecat's server API reference documentation.
+
+## Setup
+
+1. Install documentation dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+2. Make the build scripts executable:
+
+```bash
+chmod +x build-docs.sh rtd-test.py
+```
 
 ## Building Documentation
 
-From this directory:
+From this directory, you can build the documentation in several ways:
+
+### Local Build
 
 ```bash
-# Build docs (warnings shown but don't fail the build)
-cd docs/api && uv run ./build-docs.sh
+# Using the build script (automatically opens docs when done)
+./build-docs.sh
 
-# Build with strict mode (warnings treated as errors)
-cd docs/api && uv run ./build-docs.sh --strict
+# Or directly with sphinx-build
+sphinx-build -b html . _build/html -W --keep-going
 ```
 
-The build script will:
+### ReadTheDocs Test Build
 
-1. Install documentation dependencies via `uv sync --group docs`
-2. Clean previous build output
-3. Run `sphinx-build` to generate HTML documentation
-4. Open the result in your browser (macOS)
+To test the documentation build process exactly as it would run on ReadTheDocs:
+
+```bash
+./rtd-test.py
+```
+
+This script:
+
+- Creates a fresh virtual environment
+- Installs all dependencies as specified in requirements files
+- Handles conflicting dependencies (like grpcio versions for Riva)
+- Builds the documentation in an isolated environment
+- Provides detailed logging of the build process
+
+Use this script to verify your documentation will build correctly on ReadTheDocs before pushing changes.
+
+## Viewing Documentation
+
+The built documentation will be available at `_build/html/index.html`. To open:
+
+```bash
+# On MacOS
+open _build/html/index.html
+
+# On Linux
+xdg-open _build/html/index.html
+
+# On Windows
+start _build/html/index.html
+```
 
 ## Directory Structure
 
 ```
 .
-├── api/            # Auto-generated API documentation (created during build)
-├── _build/         # Built documentation output
-├── conf.py         # Sphinx configuration (mock imports, extensions, etc.)
+├── api/            # Auto-generated API documentation
+├── _build/         # Built documentation
+├── _static/        # Static files (images, css, etc.)
+├── conf.py         # Sphinx configuration
 ├── index.rst       # Main documentation entry point
+├── requirements-base.txt    # Base documentation dependencies
+├── requirements-riva.txt    # Riva-specific dependencies
 ├── build-docs.sh   # Local build script
-└── rtd-test.sh     # ReadTheDocs test build script (uses pip, not uv)
+└── rtd-test.py     # ReadTheDocs test build script
 ```
 
-## How It Works
+## Notes
 
-- `conf.py` runs `sphinx-apidoc` during Sphinx's `setup()` phase to generate `.rst` files from Python source
-- Sphinx autodoc imports each module to extract docstrings
-- Modules with unavailable dependencies are listed in `autodoc_mock_imports` in `conf.py`
-- Napoleon extension converts Google-style docstrings to reStructuredText
+- Documentation is auto-generated from Python docstrings
+- Service modules are automatically detected and included
+- The build process matches our ReadTheDocs configuration
+- Warnings are treated as errors (-W flag) to maintain consistency
+- The --keep-going flag ensures all errors are reported
+- Dependencies are split into multiple requirements files to handle version conflicts
 
 ## Troubleshooting
 
-**Module not appearing in docs:**
+If you encounter missing service modules:
 
-1. Check the build output for `autodoc: failed to import` warnings
-2. If the module has an unresolvable import dependency, add it to `autodoc_mock_imports` in `conf.py`
-3. Verify the module is importable: `uv run python -c "import pipecat.module.name"`
+1. Verify the service is installed with its extras: `pip install pipecat-ai[service-name]`
+2. Check the build logs for import errors
+3. Ensure the service module is properly initialized in the package
+4. Run `./rtd-test.py` to test in an isolated environment matching ReadTheDocs
 
-**Duplicate object warnings:**
+For dependency conflicts:
 
-These come from re-export modules or Sphinx discovering the same class through multiple import paths. Usually cosmetic.
+1. Check the requirements files for version specifications
+2. Use `rtd-test.py` to verify dependency resolution
+3. Consider adding service-specific requirements files if needed
 
-**Docstring formatting warnings:**
+For more information:
 
-Docstrings use reStructuredText, not Markdown. Common issues:
-- Use `Example::` with indented code blocks, not `` ```python ``
-- Ensure blank lines between directive content and subsequent sections
-- Use `Parameters:` (not `Attributes:`) for dataclass field documentation to avoid duplicate entries
+- [ReadTheDocs Configuration](.readthedocs.yaml)
+- [Sphinx Documentation](https://www.sphinx-doc.org/)

docs/api/build-docs.sh

@@ -1,16 +1,8 @@
 #!/bin/bash
 
-# Usage: ./build-docs.sh [--strict]
-#   --strict: Treat warnings as errors (default: warnings only)
-
-SPHINX_OPTS=""
-if [ "$1" = "--strict" ]; then
-    SPHINX_OPTS="-W --keep-going"
-fi
-
 # Build docs using uv
 echo "Installing dependencies with uv..."
-uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra mlx-whisper
+uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
 
 # Check if sphinx-build is available
 if ! uv run sphinx-build --version &> /dev/null; then
@@ -22,7 +14,8 @@ fi
 rm -rf _build
 
 echo "Building documentation..."
-uv run sphinx-build -b html -d _build/doctrees . _build/html $SPHINX_OPTS
+# Build docs matching ReadTheDocs configuration
+uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
 
 if [ $? -eq 0 ]; then
     echo "Documentation built successfully!"

docs/api/conf.py

@@ -4,19 +4,6 @@ import sys
 from datetime import datetime
 from pathlib import Path
 
-# Fix Pydantic v2 + Sphinx autodoc incompatibility: ConfigDict(extra="allow") fails
-# during Sphinx's import because __pydantic_extra__ annotation on BaseModel resolves to
-# `Dict[str, Any] | None` whose get_origin() is Union, not dict. Patch the check to
-# accept Union-wrapped dict types (i.e., Optional[Dict[str, Any]]).
-import pydantic._internal._generate_schema as _pydantic_gs
-
-_ORIG_DICT_TYPES = _pydantic_gs.DICT_TYPES
-# Expand the accepted types to include Union (Optional[Dict[str, Any]])
-import types
-import typing
-
-_pydantic_gs.DICT_TYPES = [*_ORIG_DICT_TYPES, typing.Union, types.UnionType]
-
 # Configure logging
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 logger = logging.getLogger("sphinx-build")
@@ -61,6 +48,8 @@ autodoc_default_options = {
 # Mock imports for optional dependencies
 autodoc_mock_imports = [
     # Krisp - has build issues on some platforms
+    "pipecat_ai_krisp",
+    "krisp",
     "krisp_audio",
     # System-specific GUI libraries
     "_tkinter",
@@ -89,6 +78,16 @@ autodoc_mock_imports = [
     "einops",
     "intel_extension_for_pytorch",
     "huggingface_hub",
+    # riva dependencies
+    "riva",
+    "riva.client",
+    "riva.client.Auth",
+    "riva.client.ASRService",
+    "riva.client.StreamingRecognitionConfig",
+    "riva.client.RecognitionConfig",
+    "riva.client.AudioEncoding",
+    "riva.client.proto.riva_tts_pb2",
+    "riva.client.SpeechSynthesisService",
     # MLX dependencies (Apple Silicon specific)
     "mlx",
     "mlx_whisper",  # Note: might need underscore format too
@@ -99,6 +98,7 @@ autodoc_mock_imports = [
     "cartesia",
     "camb",
     "sarvamai",
+    "openpipe",
     "openai.types.beta.realtime",
     "langchain_core",
     "langchain_core.messages",
@@ -110,8 +110,6 @@ autodoc_mock_imports = [
     "fastapi.middleware",
     "fastapi.responses",
     "uvicorn",
-    # Deepgram dependencies
-    "deepgram",
 ]
 
 # HTML output settings
@@ -138,8 +136,6 @@ def import_core_modules():
         "pipecat.runner",
         "pipecat.serializers",
         "pipecat.transcriptions",
-        "pipecat.turns",
-        "pipecat.extensions",
         "pipecat.utils",
     ]
 
@@ -184,6 +180,7 @@ def setup(app):
     logger.info(f"Source directory: {source_dir}")
 
     excludes = [
+        str(project_root / "src/pipecat/pipeline/to_be_updated"),
         str(project_root / "src/pipecat/examples"),
         str(project_root / "src/pipecat/tests"),
         "**/test_*.py",

docs/api/index.rst

@@ -32,5 +32,4 @@ Quick Links
    Services <api/pipecat.services>
    Transcriptions <api/pipecat.transcriptions>
    Transports <api/pipecat.transports>
-   Turns <api/pipecat.turns>
    Utils <api/pipecat.utils>

env.example

@@ -1,5 +1,5 @@
 # AI-COUSTICS
-AIC_LICENSE_KEY=...
+AICOUSTICS_LICENSE_KEY=...
 
 # Anthropic
 ANTHROPIC_API_KEY=...
@@ -80,9 +80,15 @@ GOOGLE_TEST_CREDENTIALS=...
 # Gradium
 GRAPDIUM_API_KEY=...
 
+# Grok
+GROK_API_KEY=...
+
 # Groq
 GROQ_API_KEY=...
 
+# Hathora
+HATHORA_API_KEY=...
+
 # Heygen
 HEYGEN_API_KEY=...
 HEYGEN_LIVE_AVATAR_API_KEY=...
@@ -91,9 +97,6 @@ HEYGEN_LIVE_AVATAR_API_KEY=...
 HUME_API_KEY=...
 HUME_VOICE_ID=...
 
-# Inception
-INCEPTION_API_KEY=...
-
 # Inworld
 INWORLD_API_KEY=...
 
@@ -105,10 +108,6 @@ KRISP_VIVA_API_KEY=...
 KRISP_VIVA_FILTER_MODEL_PATH=...
 KRISP_VIVA_TURN_MODEL_PATH=...
 
-# LemonSlice
-LEMONSLICE_API_KEY=...
-LEMONSLICE_AGENT_ID=...
-
 # LiveKit
 LIVEKIT_API_KEY=...
 LIVEKIT_API_SECRET=...
@@ -124,25 +123,18 @@ MINIMAX_GROUP_ID=...
 # Mistral
 MISTRAL_API_KEY=...
 
-# Nebius
-NEBIUS_API_KEY=...
-
 # Neuphonic
 NEUPHONIC_API_KEY=...
 
-# Novita
-NOVITA_API_KEY=...
-
 # NVIDIA
 NVIDIA_API_KEY=...
-# For a full example of how to deploy to SageMaker, see:
-# https://github.com/pipecat-ai/pipecat-examples/tree/main/nvidia_sagemaker_example/deployment/aws-sagemaker-nvidia
-SAGEMAKER_ASR_ENDPOINT_NAME=...
-SAGEMAKER_MAGPIE_ENDPOINT_NAME=...
 
 # OpenAI
 OPENAI_API_KEY=...
 
+# OpenPipe
+OPENPIPE_API_KEY=...
+
 # OpenRouter
 OPENROUTER_API_KEY=...
 
@@ -183,9 +175,6 @@ SENTRY_DSN=...
 SIMLI_API_KEY=...
 SIMLI_FACE_ID=...
 
-# Smallest
-SMALLEST_API_KEY=...
-
 # Smart turn
 LOCAL_SMART_TURN_MODEL_PATH=...
 FAL_SMART_TURN_API_KEY=...
@@ -214,22 +203,8 @@ TWILIO_AUTH_TOKEN=...
 # Ultravox Realtime
 ULTRAVOX_API_KEY=...
 
-# Vonage
-VONAGE_APPLICATION_ID=...
-VONAGE_SESSION_ID=...
-VONAGE_TOKEN=...
-
 # WhatsApp
 WHATSAPP_TOKEN=...
 WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...
 WHATSAPP_PHONE_NUMBER_ID=...
 WHATSAPP_APP_SECRET=...
-
-# xAI / Grok
-XAI_API_KEY=...
-
-# PIPECAT_SCTP_MAX_CHUNK_SIZE controls the maximum SCTP DATA-chunk payload
-# size (bytes) used by aiortc's data channel. The default is 1100.
-# All the details here:
-# https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc#pipecat_sctp_max_chunk_size
-#PIPECAT_SCTP_MAX_CHUNK_SIZE=1100

examples/README.md

@@ -1,150 +1,31 @@
 # Pipecat Examples
 
-This directory contains examples showing how to build voice and multimodal agents with Pipecat.
+This directory contains examples to help you learn how to build with Pipecat.
 
-## Setup
+## Getting Started
 
-1. Follow the [README](https://github.com/pipecat-ai/pipecat/blob/main/README.md#%EF%B8%8F-contributing-to-the-framework) steps to get your local environment configured.
+New to Pipecat? Start here:
 
-   > **Run from root directory**: Make sure you are running the steps from the root directory.
+- **[Quickstart](quickstart/)** - Get your first voice AI bot running in 5 minutes _(coming soon)_
+- **[Client/Server Web](client-server-web/)** - Learn to build web applications with Pipecat's client SDKs _(coming soon)_
+- **[Phone Bot with Twilio](phone-bot-twilio/)** - Connect your bot to a phone number _(coming soon)_
 
-   > **Using local audio?**: The `LocalAudioTransport` requires a system dependency for `portaudio`. Install the dependency to use the transport.
+## Foundational Examples
 
-2. Copy the [`env.example`](../env.example) file and add API keys for services you plan to use:
+Single-file examples that introduce core Pipecat concepts one at a time. These examples:
 
-   ```bash
-   cp env.example .env
-   # Edit .env with your API keys
-   ```
+- Build on each other progressively
+- Focus on specific features or integrations
+- Are used for testing with every Pipecat release
 
-3. Run any example:
+See the **[Foundational Examples README](foundational/)** for the complete list.
 
-   ```bash
-   uv run python getting-started/01-say-one-thing.py
-   ```
+## More Advanced Examples
 
-4. Open the web interface at http://localhost:7860/client/ and click "Connect"
+Ready to explore complex use cases? Visit **[pipecat-examples](https://github.com/pipecat-ai/pipecat-examples)** for:
 
-## Running examples with other transports
-
-Most examples support running with other transports, like Twilio or Daily.
-
-### Daily
-
-You need to create a Daily account at https://dashboard.daily.co/u/signup. Once signed up, you can create your own room from the dashboard and set the environment variables `DAILY_ROOM_URL` and `DAILY_API_KEY`. Alternatively, you can let the example create a room for you (still needs `DAILY_API_KEY` environment variable). Then, start any example with `-t daily`:
-
-```bash
-uv run getting-started/06-voice-agent.py -t daily
-```
-
-### Twilio
-
-It is also possible to run the example through a Twilio phone number. You will need to setup a few things:
-
-1. Install and run [ngrok](https://ngrok.com/download).
-
-```bash
-ngrok http 7860
-```
-
-2. Configure your Twilio phone number. One way is to setup a TwiML app and set the request URL to the ngrok URL from step (1). Then, set your phone number to use the new TwiML app.
-
-Then, run the example with:
-
-```bash
-uv run getting-started/06-voice-agent.py -t twilio -x NGROK_HOST_NAME
-```
-
-## Directory Structure
-
-### [`getting-started/`](./getting-started/)
-
-Progressive introduction to Pipecat, from minimal TTS to a full voice agent with function calling.
-
-### [`voice/`](./voice/)
-
-Full STT + LLM + TTS voice agent pipelines showcasing different speech service providers (Deepgram, ElevenLabs, Cartesia, etc.)
-
-### [`function-calling/`](./function-calling/)
-
-Function calling with different LLM providers (OpenAI, Anthropic, Google, etc.)
-
-### [`transcription/`](./transcription/)
-
-Speech-to-text examples with various STT providers.
-
-### [`vision/`](./vision/)
-
-Image description and vision capabilities with different multimodal LLMs.
-
-### [`realtime/`](./realtime/)
-
-Realtime and multimodal live APIs (OpenAI Realtime, Gemini Live, AWS Nova Sonic, Ultravox, Grok).
-
-### [`persistent-context/`](./persistent-context/)
-
-Maintaining conversation context across sessions with different providers.
-
-### [`context-summarization/`](./context-summarization/)
-
-Summarizing conversation context to manage token limits.
-
-### [`update-settings/`](./update-settings/)
-
-Changing service settings at runtime, organized by service type:
-
-- **[`stt/`](./update-settings/stt/)** — Speech-to-text settings
-- **[`tts/`](./update-settings/tts/)** — Text-to-speech settings
-- **[`llm/`](./update-settings/llm/)** — LLM settings
-
-### [`turn-management/`](./turn-management/)
-
-Turn detection, interruption handling, and user input management.
-
-### [`thinking-and-mcp/`](./thinking-and-mcp/)
-
-LLM thinking/reasoning modes and MCP (Model Context Protocol) tool server integration.
-
-### [`transports/`](./transports/)
-
-Transport layer examples (WebRTC, Daily, LiveKit).
-
-### [`video-avatar/`](./video-avatar/)
-
-Video avatar integrations (Tavus, HeyGen, Simli, LemonSlice).
-
-### [`video-processing/`](./video-processing/)
-
-Video processing, mirroring, GStreamer, and custom video tracks.
-
-### [`audio/`](./audio/)
-
-Audio recording, background sounds, and sound effects.
-
-### [`observability/`](./observability/)
-
-Pipeline monitoring: observers, heartbeats, and Sentry metrics.
-
-### [`rag/`](./rag/)
-
-Retrieval-augmented generation, grounding, and long-term memory (Mem0, Gemini).
-
-### [`features/`](./features/)
-
-Miscellaneous features: wake phrases, live translation, service switching, voice switching, and more.
-
-## Advanced Usage
-
-### Customizing Network Settings
-
-```bash
-uv run python <example-name> --host 0.0.0.0 --port 8080
-```
-
-### Troubleshooting
-
-- **No audio/video**: Check browser permissions for microphone and camera
-- **Connection errors**: Verify API keys in `.env` file
-- **Port conflicts**: Use `--port` to change the port
-
-For more examples, visit the [pipecat-examples repository](https://github.com/pipecat-ai/pipecat-examples).
+- Production-ready applications
+- Multi-platform client implementations
+- Telephony integrations
+- Multimodal and creative applications
+- Deployment and monitoring examples

examples/context-summarization/context-summarization-dedicated-llm.py

@@ -1,238 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""Example demonstrating advanced context summarization configuration.
-
-This example shows how to customize context summarization with:
-- A dedicated cheap/fast LLM for generating summaries (Gemini Flash)
-- A custom summary message template (XML tags)
-- A custom summarization prompt
-- A summarization timeout
-- The on_summary_applied event for observability
-"""
-
-import asyncio
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent
-from pipecat.processors.aggregators.llm_response_universal import (
-    LLMAssistantAggregatorParams,
-    LLMContextAggregatorPair,
-    LLMUserAggregatorParams,
-)
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.google.llm import GoogleLLMService
-from pipecat.services.llm_service import FunctionCallParams
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-from pipecat.utils.context.llm_context_summarization import (
-    LLMAutoContextSummarizationConfig,
-    LLMContextSummaryConfig,
-)
-
-load_dotenv(override=True)
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-# Custom summarization prompt tailored to the application
-CUSTOM_SUMMARIZATION_PROMPT = """Summarize this conversation, preserving:
-- Key decisions and agreements
-- Important facts and user preferences
-- Any pending action items or unresolved questions
-
-Be concise. Use clear, factual statements grouped by topic.
-Omit greetings, small talk, and resolved tangents."""
-
-
-# Tool functions for the LLM
-async def get_current_weather(params: FunctionCallParams):
-    """Get the current weather."""
-    logger.info("Tool called: get_current_weather")
-    await asyncio.sleep(1)  # Simulate some processing
-    await params.result_callback({"conditions": "nice", "temperature": "75"})
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info("Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
-
-    tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
-    system_prompt = """You are a helpful LLM in a voice call. Your goal is to demonstrate your
-                    capabilities in a succinct way. Your output will be spoken aloud, so avoid
-                    special characters that can't easily be spoken, such as emojis or bullet points.
-                    Respond to what the user said in a creative and helpful way.
-                    You have access to tools to get the current weather - use them when relevant.
-                    When you see a <context_summary> block, it contains a compressed summary
-                    of earlier conversation. Use it as reference but don't mention it to the user.
-                    """
-
-    # Primary LLM for conversation (could be any provider)
-    llm = OpenAILLMService(
-        api_key=os.environ["OPENAI_API_KEY"],
-        settings=OpenAILLMService.Settings(
-            system_instruction=system_prompt,
-        ),
-    )
-
-    # Dedicated cheap/fast LLM for summarization only
-    summarization_llm = GoogleLLMService(
-        api_key=os.environ["GOOGLE_API_KEY"],
-        settings=GoogleLLMService.Settings(
-            model="gemini-2.5-flash",
-        ),
-    )
-
-    # Register tool functions
-    llm.register_function("get_current_weather", get_current_weather)
-
-    weather_function = FunctionSchema(
-        name="get_current_weather",
-        description="Get the current weather",
-        properties={
-            "location": {
-                "type": "string",
-                "description": "The city and state, e.g. San Francisco, CA",
-            },
-            "format": {
-                "type": "string",
-                "enum": ["celsius", "fahrenheit"],
-                "description": "The temperature unit to use. Infer this from the user's location.",
-            },
-        },
-        required=["location", "format"],
-    )
-    tools = ToolsSchema(standard_tools=[weather_function])
-
-    context = LLMContext(tools=tools)
-
-    # Create aggregators with custom summarization
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
-        context,
-        user_params=LLMUserAggregatorParams(
-            vad_analyzer=SileroVADAnalyzer(),
-        ),
-        assistant_params=LLMAssistantAggregatorParams(
-            enable_auto_context_summarization=True,
-            auto_context_summarization_config=LLMAutoContextSummarizationConfig(
-                # Trigger thresholds (low values to demonstrate quickly)
-                max_context_tokens=1000,
-                max_unsummarized_messages=10,
-                summary_config=LLMContextSummaryConfig(
-                    # Summary generation
-                    target_context_tokens=800,
-                    min_messages_after_summary=2,
-                    summarization_prompt=CUSTOM_SUMMARIZATION_PROMPT,
-                    # Custom summary format - wrap in XML tags so the system
-                    # prompt can identify summaries vs. live conversation
-                    summary_message_template="<context_summary>\n{summary}\n</context_summary>",
-                    # Use a dedicated cheap LLM for summarization instead of
-                    # the primary conversation model
-                    llm=summarization_llm,
-                    # Cancel summarization if it takes longer than 60 seconds
-                    summarization_timeout=60.0,
-                ),
-            ),
-        ),
-    )
-
-    # Listen for summarization events
-    @assistant_aggregator.event_handler("on_summary_applied")
-    async def on_summary_applied(aggregator, summarizer, event: SummaryAppliedEvent):
-        logger.info(
-            f"Context summarized: {event.original_message_count} messages -> "
-            f"{event.new_message_count} messages "
-            f"({event.summarized_message_count} summarized, "
-            f"{event.preserved_message_count} preserved)"
-        )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,
-            user_aggregator,  # User responses
-            llm,  # LLM
-            tts,  # TTS
-            transport.output(),  # Transport bot output
-            assistant_aggregator,  # Assistant spoken responses
-        ]
-    )
-
-    worker = PipelineWorker(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info("Client connected")
-        # Kick off the conversation.
-        context.add_message(
-            {"role": "developer", "content": "Please introduce yourself to the user."}
-        )
-        await worker.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info("Client disconnected")
-        await worker.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(worker)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/context-summarization/context-summarization-manual-openai.py

@@ -1,173 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""Example demonstrating manual context summarization via a function call.
-
-This example shows how to trigger context summarization on demand rather than
-automatically. The user can ask the bot to "summarize the conversation" and the
-bot will call a function that pushes an LLMSummarizeContextFrame into the
-pipeline, causing the LLM service to compress the conversation history.
-
-Unlike example 54, automatic summarization is NOT enabled here. Summarization
-only happens when the user explicitly requests it through the function call.
-"""
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMRunFrame, LLMSummarizeContextFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import (
-    LLMContextAggregatorPair,
-    LLMUserAggregatorParams,
-)
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.llm_service import FunctionCallParams
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-
-async def summarize_conversation(params: FunctionCallParams):
-    """Trigger manual context summarization via a pipeline frame."""
-    logger.info("Tool called: summarize_conversation")
-    await params.result_callback({"status": "summarization_requested"})
-    await params.llm.queue_frame(LLMSummarizeContextFrame())
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info("Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
-
-    tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
-    system_prompt = """You are a helpful LLM in a voice call. Your goal is to demonstrate your
-                    capabilities in a succinct way. Your output will be spoken aloud, so avoid
-                    special characters that can't easily be spoken, such as emojis or bullet points.
-                    Respond to what the user said in a creative and helpful way.
-                    If the user asks you to summarize the conversation, call the
-                    summarize_conversation function. After summarization, briefly acknowledge
-                    that the conversation history has been compressed.
-                    """
-
-    llm = OpenAILLMService(
-        api_key=os.environ["OPENAI_API_KEY"],
-        settings=OpenAILLMService.Settings(
-            system_instruction=system_prompt,
-        ),
-    )
-
-    llm.register_function("summarize_conversation", summarize_conversation)
-
-    summarize_function = FunctionSchema(
-        name="summarize_conversation",
-        description=(
-            "Summarize and compress the conversation history. "
-            "Call this when the user asks you to summarize the conversation "
-            "or when you want to free up context space."
-        ),
-        properties={},
-        required=[],
-    )
-    tools = ToolsSchema(standard_tools=[summarize_function])
-
-    context = LLMContext(tools=tools)
-
-    # Automatic summarization is NOT enabled here (enable_auto_context_summarization
-    # defaults to False). The summarizer is still created internally so that
-    # LLMSummarizeContextFrame frames pushed via the function call are handled.
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
-        context,
-        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
-    )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,
-            user_aggregator,  # User responses
-            llm,  # LLM
-            tts,  # TTS
-            transport.output(),  # Transport bot output
-            assistant_aggregator,  # Assistant spoken responses
-        ]
-    )
-
-    worker = PipelineWorker(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info("Client connected")
-        # Kick off the conversation.
-        context.add_message(
-            {"role": "developer", "content": "Please introduce yourself to the user."}
-        )
-        await worker.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info("Client disconnected")
-        await worker.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(worker)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/features/features-add-tool-change-messages.py

@@ -1,232 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""Manual validation harness for the ``add_tool_change_messages`` feature.
-
-When tools change mid-conversation, LLMs can produce a few different
-flavors of tool-call-related hallucination:
-
-- **Forward hallucination** — calling a tool that has been removed.
-- **Negative hallucination** — refusing to call a tool that has been
-  re-added (because recent context is full of "I can't" responses).
-- **Hallucinated output when tools are unavailable** — making up an
-  answer rather than declining gracefully, or producing JSON that
-  *looks* like a tool call but is actually just an assistant text
-  response.
-
-The ``add_tool_change_messages`` feature mitigates these by appending a
-developer-role message to the conversation whenever ``LLMSetToolsFrame``
-changes the set of advertised tools, so the LLM stays in sync with what's
-actually available.
-
-This harness exercises all of those flavors by flipping the advertised
-tool set on a turn counter:
-
-    Phase 0 (turns 1–4):   weather tool ACTIVE — confirm baseline.
-    Phase 1 (turns 5–8):   tool REMOVED — keep asking for weather.
-    Phase 2 (turn 9+):     tool RE-ADDED — does the LLM call it again?
-
-Set ``ADD_TOOL_CHANGE_MESSAGES=0`` to disable the mitigation and see the
-unmitigated behavior. The default is ON so a fresh run shows the feature
-working.
-
-Defaults to Llama 3.1 8B Instruct via a locally-running Ollama —
-anecdotally one of the more hallucination-prone of the easily accessible
-models. Pull the model once with ``ollama pull llama3.1:8b`` and make
-sure ``ollama serve`` is running. Swap the LLM service to validate other
-providers.
-
-Run with::
-
-    uv run examples/features/features-add-tool-change-messages.py
-    ADD_TOOL_CHANGE_MESSAGES=0 uv run examples/features/features-add-tool-change-messages.py
-"""
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMRunFrame, LLMSetToolsFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
-from pipecat.processors.aggregators.llm_context import NOT_GIVEN, LLMContext
-from pipecat.processors.aggregators.llm_response_universal import (
-    LLMContextAggregatorPair,
-    LLMUserAggregatorParams,
-)
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.llm_service import FunctionCallParams
-from pipecat.services.ollama.llm import OLLamaLLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-# Default ON so a fresh run shows the feature working. Set to "0" to A/B
-# against the unmitigated behavior.
-ADD_TOOL_CHANGE_MESSAGES = os.environ.get("ADD_TOOL_CHANGE_MESSAGES", "1") == "1"
-
-
-async def fetch_weather_from_api(params: FunctionCallParams):
-    await params.result_callback({"conditions": "nice", "temperature": "75"})
-
-
-weather_function = FunctionSchema(
-    name="get_current_weather",
-    description="Get the current weather",
-    properties={
-        "location": {
-            "type": "string",
-            "description": "The city and state, e.g. San Francisco, CA",
-        },
-        "format": {
-            "type": "string",
-            "enum": ["celsius", "fahrenheit"],
-            "description": "The temperature unit to use. Infer this from the user's location.",
-        },
-    },
-    required=["location", "format"],
-)
-weather_tools = ToolsSchema(standard_tools=[weather_function])
-
-
-transport_params = {
-    "daily": lambda: DailyParams(audio_in_enabled=True, audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True, audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_in_enabled=True, audio_out_enabled=True),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(
-        f"Starting add_tool_change_messages demo bot "
-        f"(ADD_TOOL_CHANGE_MESSAGES={ADD_TOOL_CHANGE_MESSAGES})"
-    )
-
-    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
-
-    tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
-    llm = OLLamaLLMService(
-        settings=OLLamaLLMService.Settings(
-            # Llama 3.1 8B Instruct is anecdotally one of the more
-            # hallucination-prone of the easily accessible models — exactly
-            # what we want for this validation harness. Pull it with
-            # ``ollama pull llama3.1:8b`` and make sure ``ollama serve``
-            # is running.
-            model="llama3.1:8b",
-            system_instruction=(
-                "You are a helpful assistant in a voice conversation. Your responses "
-                "will be spoken aloud, so avoid emojis, bullet points, or other "
-                "formatting that can't be spoken. Respond briefly and naturally. "
-                "If the user asks for the current weather, use the `get_current_weather` "
-                "function if it's available. IMPORTANT: if you do not have access to the function, "
-                "say something along the lines of 'Sorry, I can't check the weather right now.'."
-            ),
-        ),
-    )
-    llm.register_function("get_current_weather", fetch_weather_from_api)
-
-    context = LLMContext(tools=weather_tools)
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
-        context,
-        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
-        add_tool_change_messages=ADD_TOOL_CHANGE_MESSAGES,
-    )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            stt,
-            user_aggregator,
-            llm,
-            tts,
-            transport.output(),
-            assistant_aggregator,
-        ]
-    )
-
-    worker = PipelineWorker(
-        pipeline,
-        params=PipelineParams(enable_metrics=True, enable_usage_metrics=True),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    # Phase controller: roughly 4 turns per phase.
-    user_turn_count = 0
-    REMOVE_AT_TURN = 5  # tool gone for turn N onward
-    READD_AT_TURN = 9  # tool back for turn N onward
-
-    @user_aggregator.event_handler("on_user_turn_stopped")
-    async def on_user_turn_stopped(aggregator, strategy, message):
-        nonlocal user_turn_count
-        user_turn_count += 1
-        logger.info(f"=== User turn {user_turn_count} complete ===")
-
-        if user_turn_count == REMOVE_AT_TURN - 1:
-            logger.info(
-                "=== Phase 1: weather tool REMOVED. Keep asking about the weather "
-                "to exercise hallucination scenarios. ==="
-            )
-            await worker.queue_frame(LLMSetToolsFrame(tools=NOT_GIVEN))
-        elif user_turn_count == READD_AT_TURN - 1:
-            logger.info(
-                "=== Phase 2: weather tool RE-ADDED. Ask for the weather again — "
-                "does the LLM call it, or keep refusing? (THIS IS THE TEST.) ==="
-            )
-            await worker.queue_frame(LLMSetToolsFrame(tools=weather_tools))
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info("Client connected")
-        logger.info(
-            "=== Phase 0: weather tool ACTIVE. Ask for the weather a few times "
-            "to confirm it's working. ==="
-        )
-        context.add_message(
-            {
-                "role": "developer",
-                "content": (
-                    "Please introduce yourself briefly to the user, then invite them "
-                    "to ask about the weather."
-                ),
-            }
-        )
-        await worker.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info("Client disconnected")
-        await worker.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/features/features-app-resources.py

@@ -1,327 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""Example demonstrating ``PipelineWorker(app_resources=...)``.
-
-``app_resources`` is an application-defined bag of anything your
-application code may want to share across a session: database handles,
-HTTP clients, feature flags, per-user state, observability clients,
-in-memory caches — whatever fits your app. Pipecat passes it through
-untouched and exposes it as ``worker.app_resources``, so any code with a
-handle on the worker can read or mutate it.
-
-Two of the convenience aliases exercised below:
-
-- Tool handlers read it from ``FunctionCallParams.app_resources``.
-- Custom ``FrameProcessor`` subclasses read it from
-  ``self.pipeline_worker.app_resources``.
-
-This example uses two small loggers as stand-ins for that "shared thing":
-``ToolCallLogger`` (written from tool handlers) and
-``TranscriptionLogger`` (written from a custom ``FrameProcessor`` that
-sits in the pipeline). A real app might just as easily pass a Postgres
-pool, a Redis client, a Stripe SDK instance, or any combination thereof.
-The mechanics shown here — construct once, hand to the worker, read it
-from each site, inspect it after the session — are the same regardless
-of what you put in.
-
-We bundle resources in a typed ``AppResources`` dataclass and cast back
-to it at each read site. Pipecat doesn't care what type you pass (a
-plain dict works too), but a typed container gives you autocomplete and
-refactor safety instead of dict-by-string-key lookups.
-"""
-
-import json
-import os
-from collections.abc import Mapping
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from typing import Any, cast
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, LLMRunFrame, TranscriptionFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import (
-    LLMContextAggregatorPair,
-    LLMUserAggregatorParams,
-)
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.llm_service import FunctionCallParams
-from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-class ToolCallLogger:
-    """Stand-in shared resource — swap for whatever your app actually needs."""
-
-    def __init__(self):
-        """Initialize the logger with an empty list of recorded calls."""
-        self._calls: list[dict[str, Any]] = []
-
-    def log_tool_call(self, function_name: str, arguments: Mapping[str, Any]) -> None:
-        """Record a tool call invocation.
-
-        Args:
-            function_name: The name of the tool being invoked.
-            arguments: The arguments passed to the tool.
-        """
-        entry = {
-            "timestamp": datetime.now(UTC).isoformat(),
-            "function_name": function_name,
-            "arguments": dict(arguments),
-        }
-        self._calls.append(entry)
-        logger.info(f"[ToolCallLogger] {function_name} called with {dict(arguments)}")
-
-    def dump(self) -> str:
-        """Return all recorded tool calls as a JSON string."""
-        return json.dumps(self._calls, indent=2)
-
-
-class TranscriptionLogger:
-    """Records final user transcriptions — written from a custom FrameProcessor."""
-
-    def __init__(self):
-        """Initialize the logger with an empty list of recorded transcriptions."""
-        self._entries: list[dict[str, Any]] = []
-
-    def log_transcription(self, text: str) -> None:
-        """Record a transcription.
-
-        Args:
-            text: The transcribed user utterance.
-        """
-        entry = {
-            "timestamp": datetime.now(UTC).isoformat(),
-            "text": text,
-        }
-        self._entries.append(entry)
-        logger.info(f"[TranscriptionLogger] {text!r}")
-
-    def dump(self) -> str:
-        """Return all recorded transcriptions as a JSON string."""
-        return json.dumps(self._entries, indent=2)
-
-
-@dataclass
-class AppResources:
-    """Typed container for everything the app shares across this session.
-
-    Add fields here as the app grows (e.g. ``db: AsyncConnection``,
-    ``http: httpx.AsyncClient``). Read sites ``cast()`` to this type to
-    get autocomplete and refactor safety:
-
-    - In tools: ``cast(AppResources, params.app_resources)``.
-    - In custom processors: ``cast(AppResources, self.pipeline_worker.app_resources)``.
-    """
-
-    tool_call_logger: ToolCallLogger
-    transcription_logger: TranscriptionLogger
-
-
-async def fetch_weather_from_api(params: FunctionCallParams):
-    resources = cast(AppResources, params.app_resources)
-    resources.tool_call_logger.log_tool_call(params.function_name, params.arguments)
-    await params.result_callback({"conditions": "nice", "temperature": "75"})
-
-
-async def fetch_restaurant_recommendation(params: FunctionCallParams):
-    resources = cast(AppResources, params.app_resources)
-    resources.tool_call_logger.log_tool_call(params.function_name, params.arguments)
-    await params.result_callback({"name": "The Golden Dragon"})
-
-
-class TranscriptionLoggingProcessor(FrameProcessor):
-    """Logs each final user transcription into the shared app resources.
-
-    Demonstrates the second read site for ``app_resources``: any custom
-    ``FrameProcessor`` can reach the same bag every tool handler sees by
-    going through ``self.pipeline_worker.app_resources``. ``pipeline_worker``
-    is ``None`` until the worker sets the processor up, so we guard against
-    that case.
-    """
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        """Forward all frames; log final user transcriptions on the way through."""
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, TranscriptionFrame) and self.pipeline_worker is not None:
-            resources = cast(AppResources, self.pipeline_worker.app_resources)
-            resources.transcription_logger.log_transcription(frame.text)
-
-        await self.push_frame(frame, direction)
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
-
-    tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
-    llm = OpenAIResponsesLLMService(
-        api_key=os.environ["OPENAI_API_KEY"],
-        settings=OpenAIResponsesLLMService.Settings(
-            system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
-        ),
-    )
-
-    # You can also register a function_name of None to get all functions
-    # sent to the same callback with an additional function_name parameter.
-    llm.register_function("get_current_weather", fetch_weather_from_api)
-    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
-
-    @llm.event_handler("on_connection_error")
-    async def on_connection_error(service, error):
-        logger.error(f"LLM connection error: {error}")
-
-    @llm.event_handler("on_function_calls_started")
-    async def on_function_calls_started(service, function_calls):
-        # Avoid appending this filler message to the LLM context — it would
-        # alter the conversation history and prevent
-        # OpenAIResponsesLLMService's previous_response_id optimization from
-        # matching, forcing a full context resend.
-        await tts.queue_frame(TTSSpeakFrame("Let me check on that.", append_to_context=False))
-
-    weather_function = FunctionSchema(
-        name="get_current_weather",
-        description="Get the current weather",
-        properties={
-            "location": {
-                "type": "string",
-                "description": "The city and state, e.g. San Francisco, CA",
-            },
-            "format": {
-                "type": "string",
-                "enum": ["celsius", "fahrenheit"],
-                "description": "The temperature unit to use. Infer this from the user's location.",
-            },
-        },
-        required=["location", "format"],
-    )
-    restaurant_function = FunctionSchema(
-        name="get_restaurant_recommendation",
-        description="Get a restaurant recommendation",
-        properties={
-            "location": {
-                "type": "string",
-                "description": "The city and state, e.g. San Francisco, CA",
-            },
-        },
-        required=["location"],
-    )
-    tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
-
-    context = LLMContext(tools=tools)
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
-        context,
-        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
-    )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            stt,
-            TranscriptionLoggingProcessor(),
-            user_aggregator,
-            llm,
-            tts,
-            transport.output(),
-            assistant_aggregator,
-        ]
-    )
-
-    # Keep local handles so we can read collected state after the session
-    # ends; Pipecat never copies or clears the object.
-    tool_call_logger = ToolCallLogger()
-    transcription_logger = TranscriptionLogger()
-    resources = AppResources(
-        tool_call_logger=tool_call_logger,
-        transcription_logger=transcription_logger,
-    )
-
-    worker = PipelineWorker(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        app_resources=resources,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation.
-        context.add_message(
-            {"role": "developer", "content": "Please introduce yourself to the user."}
-        )
-        await worker.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info(f"Client disconnected")
-        await worker.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(worker)
-
-    # The session has ended; read whatever state the handlers built up.
-    logger.info(f"Tool calls logged during session:\n{tool_call_logger.dump()}")
-    logger.info(f"Transcriptions logged during session:\n{transcription_logger.dump()}")
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/01-say-one-thing-piper.py

@@ -0,0 +1,69 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.piper.tts import PiperHttpTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+
+# We use lambdas to defer transport parameter creation until the transport
+# type is selected at runtime.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        tts = PiperHttpTTSService(
+            base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000
+        )
+
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
+
+        # Register an event handler so we can play the audio when the client joins
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+        await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/01-say-one-thing-rime.py

@@ -0,0 +1,70 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.rime.tts import RimeHttpTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+# We use lambdas to defer transport parameter creation until the transport
+# type is selected at runtime.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        tts = RimeHttpTTSService(
+            api_key=os.getenv("RIME_API_KEY", ""),
+            voice_id="rex",
+            aiohttp_session=session,
+        )
+
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
+
+        # Register an event handler so we can play the audio when the client joins
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+        await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/01-say-one-thing.py

@@ -12,7 +12,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -36,13 +36,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         Pipeline([tts, transport.output()]),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -50,11 +48,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await worker.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/foundational/01a-local-audio.py

@@ -14,7 +14,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
 
@@ -28,23 +28,21 @@ async def main():
     transport = LocalAudioTransport(LocalAudioTransportParams(audio_out_enabled=True))
 
     tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
     )
 
     pipeline = Pipeline([tts, transport.output()])
 
-    worker = PipelineWorker(pipeline)
+    task = PipelineTask(pipeline)
 
     async def say_something():
         await asyncio.sleep(1)
-        await worker.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
+        await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
 
-    await asyncio.gather(runner.run(worker), say_something())
+    await asyncio.gather(runner.run(task), say_something())
 
 
 if __name__ == "__main__":

examples/foundational/01b-livekit-audio.py

@@ -0,0 +1,62 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.livekit import configure
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    (url, token, room_name) = await configure()
+
+    transport = LiveKitTransport(
+        url=url,
+        token=token,
+        room_name=room_name,
+        params=LiveKitParams(audio_out_enabled=True),
+    )
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    runner = PipelineRunner()
+
+    task = PipelineTask(Pipeline([tts, transport.output()]))
+
+    # Register an event handler so we can play the audio when the
+    # participant joins.
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant_id):
+        await asyncio.sleep(1)
+        await task.queue_frame(
+            TTSSpeakFrame(
+                "Hello there! How are you doing today? Would you like to talk about the weather?"
+            )
+        )
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/01c-nvidia-riva-tts.py

@@ -0,0 +1,64 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.nvidia.tts import NvidiaTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+
+# We use lambdas to defer transport parameter creation until the transport
+# type is selected at runtime.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
+
+    task = PipelineTask(
+        Pipeline([tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    # Register an event handler so we can play the audio when the client joins
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+    await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/02-llm-say-one-thing.py

@@ -12,7 +12,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, LLMContextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -38,20 +38,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     logger.info(f"Starting bot")
 
     tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
     )
 
-    llm = OpenAILLMService(
-        api_key=os.environ["OPENAI_API_KEY"],
-        settings=OpenAILLMService.Settings(
-            system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
-        ),
-    )
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
-    worker = PipelineWorker(
+    messages = [
+        {
+            "role": "system",
+            "content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
+        }
+    ]
+
+    task = PipelineTask(
         Pipeline([llm, tts, transport.output()]),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -59,13 +59,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        context = LLMContext()
-        context.add_message({"role": "developer", "content": "Say hello to the world."})
-        await worker.queue_frames([LLMContextFrame(context), EndFrame()])
+        await task.queue_frames([LLMContextFrame(LLMContext(messages)), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):