Compare commits

..

19 Commits

Author SHA1 Message Date
filipi87
16133a2323 Removing the custom prompt. 2026-04-01 16:05:09 -03:00
filipi87
9d815cb5d2 Merge branch 'filipi/async_tools' into filipi/async_tools_structured_data 2026-04-01 15:50:35 -03:00
filipi87
2d87edac18 Merge branch 'main' into filipi/async_tools 2026-04-01 15:49:43 -03:00
filipi87
bce07e0c76 Merge branch 'filipi/async_tools' into filipi/async_tools_structured_data 2026-04-01 15:48:22 -03:00
filipi87
59092fe4fe Renaming the examples to match main. 2026-04-01 15:42:50 -03:00
filipi87
d515a81073 Updating the Anthropic example to use async function calls. 2026-04-01 15:31:32 -03:00
filipi87
e23cb46885 Trying to structure async tool responses and improve the LLM prompt to teach it how to handle them. 2026-04-01 14:48:09 -03:00
filipi87
72bbad51b7 Added group_parallel_tools parameter to LLMService. 2026-04-01 13:51:30 -03:00
filipi87
c066a913fe Adding changelogs for all the fixes. 2026-04-01 12:20:58 -03:00
filipi87
63bbfc3b27 Creating the concept of a group_id for the function calls. 2026-04-01 12:05:09 -03:00
filipi87
2458b9d42b Delaying the response for the get_current_weather in the openai example. 2026-04-01 10:47:29 -03:00
filipi87
4543aef3d9 Only pushing a context frame when we receive the function call result if the user is not speaking. 2026-04-01 10:45:00 -03:00
filipi87
260368b6f4 Fixing an issue where the BotOutputTransport was discarding the UninterruptibleFrames. 2026-04-01 10:32:11 -03:00
filipi87
3ad2675b24 Creating UninterruptibleProcessQueue. 2026-04-01 10:28:52 -03:00
filipi87
970d713d7a Using a JSON to send the result. 2026-04-01 10:28:03 -03:00
filipi87
f7012c570c Fixed an issue in the FrameProcessor where only the current frame was checked for being an UninterruptibleFrame, not other frames in the queue. 2026-03-31 18:38:11 -03:00
filipi87
4bfa084f77 Updating the openai example to be async. 2026-03-31 17:37:39 -03:00
filipi87
780d6c476d Merge branch 'main' into filipi/async_tools 2026-03-31 17:36:40 -03:00
filipi87
dfdb92958b Fix async tool handling for compatibility with all LLMs. 2026-03-31 17:26:06 -03:00
830 changed files with 15895 additions and 44092 deletions

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -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**.

View File

@@ -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>`.

30
.dockerignore Normal file
View File

@@ -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

View File

@@ -42,7 +42,6 @@ jobs:
--extra langchain \
--extra livekit \
--extra piper \
--extra runner \
--extra sagemaker \
--extra tracing \
--extra websocket

View File

@@ -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

View File

@@ -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:

View File

@@ -46,7 +46,6 @@ jobs:
--extra langchain \
--extra livekit \
--extra piper \
--extra runner \
--extra sagemaker \
--extra tracing \
--extra websocket

View File

@@ -114,7 +114,6 @@ jobs:
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 }}).

View File

@@ -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 gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
sphinx:
configuration: docs/api/conf.py

174
AGENTS.md
View File

@@ -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.

File diff suppressed because it is too large Load Diff

62
CHANGELOG.md.template Normal file
View File

@@ -0,0 +1,62 @@
# Changelog
All notable changes to the **&lt;project name&gt;** 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.

158
CLAUDE.md
View File

@@ -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
# 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.

View File

@@ -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:
@@ -71,7 +67,7 @@ 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.
Build and share your own Pipecat service integrations! Browse existing [community integrations](https://docs.pipecat.ai/server/services/community-integrations) or check out our [guide](COMMUNITY_INTEGRATIONS.md) to create your own.
### 📺️ Pipecat TV Channel
@@ -83,28 +79,28 @@ 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-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/vision/vision-moondream.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [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), [Nebius](https://docs.pipecat.ai/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nvidia), [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), [Sarvam](https://docs.pipecat.ai/server/services/llm/sarvam), [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), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [Kokoro](https://docs.pipecat.ai/server/services/tts/kokoro), [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), [Smallest](https://docs.pipecat.ai/server/services/tts/smallest), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [xAI](https://docs.pipecat.ai/server/services/tts/xai), [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), [LiveKit (WebRTC)](https://docs.pipecat.ai/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/server/services/transport/whatsapp), Local |
| Serializers | [Exotel](https://docs.pipecat.ai/server/services/serializers/exotel), [Genesys](https://docs.pipecat.ai/server/services/serializers/genesys), [Plivo](https://docs.pipecat.ai/server/services/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/services/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/services/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/services/serializers/vonage) |
| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/transport/lemonslice), [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 Viva](https://docs.pipecat.ai/guides/features/krisp-viva), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter), [RNNoise](https://docs.pipecat.ai/server/utilities/audio/rnnoise-filter) |
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
| Community | [Browse community integrations →](https://docs.pipecat.ai/server/services/community-integrations) |
📚 [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
@@ -153,8 +149,8 @@ You can get started with Pipecat running on your local machine, then move your a
### Prerequisites
**Minimum Python Version:** 3.11
**Recommended Python Version:** >= 3.12
**Minimum Python Version:** 3.10
**Recommended Python Version:** 3.12
### Setup Steps

View File

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

1
changelog/4141.added.md Normal file
View File

@@ -0,0 +1 @@
- ⚠️ Added WebSocket-based `OpenAIResponsesLLMService` as the new default for the OpenAI Responses API. It maintains a persistent connection to `wss://api.openai.com/v1/responses` and automatically uses `previous_response_id` to send only incremental context, falling back to full context on reconnection or cache miss. The previous HTTP-based implementation is now available as `OpenAIResponsesHttpLLMService`.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `OpenPipeLLMService` and the `openpipe` extra. OpenPipe was acquired by CoreWeave and the package is no longer maintained. If you were using `openpipe` as an LLM provider, switch to the underlying provider directly (e.g. `openai`). The OpenPipe interface can still be used with `OpenAILLMService` by specifying a `base_url`.

View File

@@ -0,0 +1 @@
- ⚠️ Updated `langchain` extra to require langchain 1.x (from 0.3.x), langchain-community 0.4.x (from 0.3.x), and langchain-openai 1.x (from 0.3.x). If you pin these packages in your project, update your pins accordingly.

1
changelog/4202.fixed.md Normal file
View File

@@ -0,0 +1 @@
- Fixed `InworldHttpTTSService` streaming responses crashing with `UnicodeDecodeError` when multi-byte UTF-8 characters were split across chunk boundaries. This caused TTS audio to cut off mid-sentence intermittently.

1
changelog/4203.fixed.md Normal file
View File

@@ -0,0 +1 @@
- Fixed a crash (`JSONDecodeError`) when a user interruption occurs while the LLM is streaming function call arguments. Previously, the incomplete JSON arguments were passed directly to `json.loads()`, causing an unhandled exception. Affected services: OpenAI, Google (OpenAI-compatible), and SambaNova.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `observers` field from `PipelineParams`. Pass observers directly to `PipelineTask` constructor instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `on_pipeline_ended`, `on_pipeline_cancelled`, and `on_pipeline_stopped` events from `PipelineTask`. Use `on_pipeline_finished` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `AudioBufferProcessor.user_continuous_stream` parameter. Use `user_audio_passthrough` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `camera_in_enabled`, `camera_in_is_live`, `camera_in_width`, `camera_in_height`, `camera_out_enabled`, `camera_out_is_live`, `camera_out_width`, `camera_out_height`, and `camera_out_color` transport params. Use the `video_in_*` and `video_out_*` equivalents instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `RTVIObserver.errors_enabled` parameter.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `vad_enabled` and `vad_audio_passthrough` transport params.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `TTSService.say()`. Push a `TTSSpeakFrame` into the pipeline instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `DailyRunner.configure_with_args()`. Use `PipelineRunner` with `RunnerArguments` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated RTVI models, frames, and processor methods including `RTVIConfig`, `RTVIServiceConfig`, `RTVIServiceOptionConfig`, various `RTVI*Data` models, `RTVIActionFrame`, and `RTVIProcessor.handle_function_call`/`handle_function_call_start`. Use the updated RTVI processor API instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `FrameProcessor.wait_for_task()`. Use `create_task()` and manage tasks with the built-in `TaskManager` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `KrispFilter`. The `krisp` extra has been removed from `pyproject.toml`.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `LLMService.request_image_frame()`. Push a `UserImageRequestFrame` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `create_default_resampler()` from `pipecat.audio.utils`.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `FalSmartTurnAnalyzer` and `LocalSmartTurnAnalyzer`.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated transport frames: `TransportMessageFrame`, `TransportMessageUrgentFrame`, `InputTransportMessageUrgentFrame`, `DailyTransportMessageFrame`, and `DailyTransportMessageUrgentFrame`. Use `OutputTransportMessageFrame`, `OutputTransportMessageUrgentFrame`, `InputTransportMessageFrame`, `DailyOutputTransportMessageFrame`, and `DailyOutputTransportMessageUrgentFrame` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `KeypadEntryFrame` alias.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated interruption frames: `StartInterruptionFrame` and `BotInterruptionFrame`. Use `InterruptionFrame` and `InterruptionTaskFrame` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `LLMService.start_callback` parameter. Register an `on_llm_response_start` event handler instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed single-argument function call support from `LLMService`. Functions must use named parameters instead of a single `arguments` parameter.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `NoisereduceFilter`. Use system-level noise reduction or a service-based alternative instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.riva` package. Use `pipecat.services.nvidia.stt` and `pipecat.services.nvidia.tts` instead (`RivaSTTService``NvidiaSTTService`, `RivaTTSService``NvidiaTTSService`).

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.nim` package. Use `pipecat.services.nvidia.llm` instead (`NimLLMService``NvidiaLLMService`).

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.gemini_multimodal_live` package. Use `pipecat.services.google.gemini_live` instead. Note that class names no longer include "Multimodal" (e.g. `GeminiMultimodalLiveLLMService``GeminiLiveLLMService`).

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.aws_nova_sonic` package. Use `pipecat.services.aws.nova_sonic` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.openai_realtime` package. Use `pipecat.services.openai.realtime` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `OpenAIRealtimeBetaLLMService` and `AzureRealtimeBetaLLMService`. Use `OpenAIRealtimeLLMService` and `AzureRealtimeLLMService` from `pipecat.services.openai.realtime` and `pipecat.services.azure.realtime` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.deepgram.stt_sagemaker` and `pipecat.services.deepgram.tts_sagemaker` modules. Use `pipecat.services.deepgram.sagemaker.stt` and `pipecat.services.deepgram.sagemaker.tts` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `GoogleLLMOpenAIBetaService` from `pipecat.services.google.openai`. Use `GoogleLLMService` from `pipecat.services.google.llm` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.google.llm_vertex` module. Use `pipecat.services.google.vertex.llm` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.google.gemini_live.llm_vertex` module. Use `pipecat.services.google.gemini_live.vertex.llm` instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated `pipecat.services.ai_services` module. Import from `pipecat.services.ai_service`, `pipecat.services.llm_service`, `pipecat.services.stt_service`, `pipecat.services.tts_service`, etc. instead.

View File

@@ -0,0 +1 @@
- Changed `GrokLLMService` default model from `grok-3-beta` to `grok-3`, now that the model is generally available.

View File

@@ -0,0 +1 @@
- `GoogleImageGenService` now defaults to `imagen-4.0-generate-001` (previously `imagen-3.0-generate-002`).

View File

@@ -0,0 +1 @@
- ⚠️ `BaseOpenAILLMService.get_chat_completions()` now accepts an `LLMContext` instead of `OpenAILLMInvocationParams`. If you override this method, update your signature accordingly.

View File

@@ -0,0 +1,22 @@
- ⚠️ Removed deprecated service-specific context and aggregator machinery, which was superseded by the universal `LLMContext` system.
Service-specific classes removed: `AnthropicLLMContext`, `AnthropicContextAggregatorPair`, `AWSBedrockLLMContext`, `AWSBedrockContextAggregatorPair`, `OpenAIContextAggregatorPair`, and their user/assistant aggregators. Also removed `create_context_aggregator()` from `LLMService`, `OpenAILLMService`, `AnthropicLLMService`, and `AWSBedrockLLMService`.
Base aggregator classes removed (from `pipecat.processors.aggregators.llm_response`): `BaseLLMResponseAggregator`, `LLMContextResponseAggregator`, `LLMUserContextAggregator`, `LLMAssistantContextAggregator`, `LLMUserResponseAggregator`, `LLMAssistantResponseAggregator`.
From the developer's point of view, migrating will usually be a matter of going from this:
```python
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
```
To this:
```python
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
context = LLMContext(messages, tools)
context_aggregator = LLMContextAggregatorPair(context)
```

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated frame types `LLMMessagesFrame` and `OpenAILLMContextAssistantTimestampFrame` from `pipecat.frames.frames`. Instead of `LLMMessagesFrame`, use `LLMContextFrame` with the new messages, or `LLMMessagesUpdateFrame` with `run_llm=True`.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `GatedOpenAILLMContextAggregator` (from `pipecat.processors.aggregators.gated_open_ai_llm_context`). Use `GatedLLMContextAggregator` (from `pipecat.processors.aggregators.gated_llm_context`) instead.

View File

@@ -0,0 +1 @@
- ⚠️ Removed `VisionImageFrameAggregator` (from `pipecat.processors.aggregators.vision_image_frame`). Vision/image handling is now built into `LLMContext` (from `pipecat.processors.aggregators.llm_context`). See the `12*` examples for the recommended replacement pattern.

View File

@@ -0,0 +1 @@
- ⚠️ Removed deprecated compatibility modules: `pipecat.services.openai_realtime_beta` (use `pipecat.services.openai.realtime`), `pipecat.services.openai_realtime.context`, `pipecat.services.openai_realtime.frames`, `pipecat.services.openai.realtime.context`, `pipecat.services.openai.realtime.frames`, `pipecat.services.gemini_multimodal_live` (use `pipecat.services.google.gemini_live`), `pipecat.services.aws_nova_sonic.context` (use `pipecat.services.aws.nova_sonic`), `pipecat.services.google.openai` and `pipecat.services.google.llm_openai` (use `pipecat.services.google.llm`).

18
changelog/4215.removed.md Normal file
View File

@@ -0,0 +1,18 @@
- ⚠️ Removed `OpenAILLMContext`, `OpenAILLMContextFrame`, and `OpenAILLMContext.from_messages()`. Use `LLMContext` (from `pipecat.processors.aggregators.llm_context`) and `LLMContextFrame` (from `pipecat.frames.frames`) instead. All services now exclusively use the universal `LLMContext`.
From the developer's point of view, migrating will usually be a matter of going from this:
```python
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
```
To this:
```python
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
context = LLMContext(messages, tools)
context_aggregator = LLMContextAggregatorPair(context)
```

View File

@@ -0,0 +1 @@
- Added `group_parallel_tools` parameter to `LLMService` (default `True`). When `True`, all function calls from the same LLM response batch share a group ID and the LLM is triggered exactly once after the last call completes. Set to `False` to trigger inference independently for each function call result as it arrives.

1
changelog/4217.added.md Normal file
View File

@@ -0,0 +1 @@
- Added `is_async=True` support to `register_function()` and `register_direct_function()`. When enabled, the LLM continues the conversation immediately without waiting for the function result. The result is injected back into the context as a `developer` message once available, triggering a new LLM inference at that point.

View File

@@ -0,0 +1 @@
- When multiple function calls are returned in a single LLM response, the LLM is now triggered exactly once after the last call in the batch completes, rather than waiting for all function calls.

View File

@@ -0,0 +1 @@
- Fixed `BaseOutputTransport` discarding pending `UninterruptibleFrame` items (e.g. function-call context updates) when an interruption arrived. The audio task is now kept alive and only interruptible frames are drained when uninterruptible frames are present in the queue.

View File

@@ -0,0 +1 @@
- Fixed spurious LLM inference being triggered when a function call result arrived while the user was actively speaking. The context frame is now suppressed until the user stops speaking.

1
changelog/4217.fixed.md Normal file
View File

@@ -0,0 +1 @@
- Fixed an issue where `UninterruptibleFrame` items queued in `FrameProcessor` could be incorrectly dropped on interruption. Previously only the frame currently being processed was checked; now the entire process queue is scanned so pending uninterruptible frames are always delivered.

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

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

View File

@@ -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`).

View File

@@ -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.

View File

@@ -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`.

View File

@@ -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.

View File

@@ -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.

View File

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

View File

@@ -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.

View File

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

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

@@ -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.

View File

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

View File

@@ -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/)

View File

@@ -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 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!"

View File

@@ -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")
@@ -89,6 +76,16 @@ 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
@@ -110,8 +107,6 @@ autodoc_mock_imports = [
"fastapi.middleware",
"fastapi.responses",
"uvicorn",
# Deepgram dependencies
"deepgram",
]
# HTML output settings
@@ -138,8 +133,6 @@ def import_core_modules():
"pipecat.runner",
"pipecat.serializers",
"pipecat.transcriptions",
"pipecat.turns",
"pipecat.extensions",
"pipecat.utils",
]
@@ -184,6 +177,7 @@ 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",

View File

@@ -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>

View File

@@ -1,5 +1,5 @@
# AI-COUSTICS
AIC_LICENSE_KEY=...
AICOUSTICS_LICENSE_KEY=...
# Anthropic
ANTHROPIC_API_KEY=...
@@ -91,9 +91,6 @@ HEYGEN_LIVE_AVATAR_API_KEY=...
HUME_API_KEY=...
HUME_VOICE_ID=...
# Inception
INCEPTION_API_KEY=...
# Inworld
INWORLD_API_KEY=...
@@ -135,10 +132,6 @@ 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=...
@@ -214,11 +207,6 @@ TWILIO_AUTH_TOKEN=...
# Ultravox Realtime
ULTRAVOX_API_KEY=...
# Vonage
VONAGE_APPLICATION_ID=...
VONAGE_SESSION_ID=...
VONAGE_TOKEN=...
# WhatsApp
WHATSAPP_TOKEN=...
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...
@@ -226,10 +214,4 @@ 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
XAI_API_KEY=...

View File

@@ -34,7 +34,7 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
load_dotenv(override=True)
OFFICE_SOUND_FILE = os.path.join(
os.path.dirname(__file__), "../assets", "office-ambience-24000-mono.mp3"
os.path.dirname(__file__), "assets", "office-ambience-24000-mono.mp3"
)
# We use lambdas to defer transport parameter creation until the transport
@@ -71,17 +71,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.environ["CARTESIA_API_KEY"],
api_key=os.getenv("CARTESIA_API_KEY"),
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = OpenAILLMService(
api_key=os.environ["OPENAI_API_KEY"],
api_key=os.getenv("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.",
),

View File

@@ -108,17 +108,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"], audio_passthrough=True)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"), audio_passthrough=True)
tts = CartesiaTTSService(
api_key=os.environ["CARTESIA_API_KEY"],
api_key=os.getenv("CARTESIA_API_KEY"),
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121",
),
)
llm = OpenAILLMService(
api_key=os.environ["OPENAI_API_KEY"],
api_key=os.getenv("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.",
),

Some files were not shown because too many files have changed in this diff Show More