72d0fb418a
Before the new async-tool mechanism landed, AWSNovaSonicLLMService and OpenAIRealtimeLLMService honored cancel_on_interruption=False by simply not cancelling in-flight function calls on interruption — the eventual result then flowed through the same channel as any synchronous tool result. The new mechanism (which appends started/intermediate/final messages to the LLM context as the underlying task progresses) broke that path: the realtime services didn't know how to interpret those messages, and the eventual result was never delivered to the provider. Restore the flag's behavior by teaching both services to detect async-tool messages in the context and route them appropriately: - started → skipped silently. The provider already issued the tool call and natively awaits a result; nothing to send for the started marker. - final → delivered via the formal tool-result channel. Same path as a synchronous tool result, just delayed. Streamed intermediate results (FunctionCallResultProperties(is_final= False)) are not supported on these realtime services. An intermediate result is logged as an error and surfaced via push_error, then dropped. Use a non-realtime LLM service if a tool needs to stream intermediate results. (Docstrings on register_function, register_direct_function, and FunctionCallResultProperties.is_final updated to call this out.) A new shared module pipecat.processors.aggregators.async_tool_messages is the single source of truth for the on-the-wire payload shape: the aggregator uses its build_*_message functions when injecting messages, and the realtime services use parse_message when scanning the context. Adds two example files exercising a network-delayed weather tool with each service. The plain realtime-aws-nova-sonic.py example is also reverted to a synchronous tool call now that the async variant lives in its own file. Similar fixes for other realtime services are forthcoming.
🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents
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 quickstartor follow the quickstart guide.
🚀 What You Can Build
- Voice Assistants – natural, streaming conversations with AI
- AI Companions – coaches, meeting assistants, characters
- Multimodal Interfaces – voice, video, images, and more
- Interactive Storytelling – creative tools with generative media
- Business Agents – customer intake, support bots, guided flows
- Complex Dialog Systems – design logic with structured conversations
🧠 Why Pipecat?
- Voice-first: Integrates speech recognition, text-to-speech, and conversation handling
- Pluggable: Supports many AI services and tools
- Composable Pipelines: Build complex behavior from modular components
- Real-Time: Ultra-low latency interaction with different transports (e.g. WebSockets or WebRTC)
🌐 Pipecat Ecosystem
🧩 Multi-agent systems
Need multiple AI agents working together? 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:
JavaScript | React | React Native | Swift | Kotlin | C++ | ESP32
🧭 Structured conversations
Looking to build structured conversations? Check out Pipecat Flows for managing complex conversational states and transitions.
🪄 Beautiful UIs
Want to build beautiful and engaging experiences? Checkout the Voice UI Kit, a collection of components, hooks and templates for building voice AI applications quickly.
🛠️ Create and deploy projects
Create a new project in under a minute with the Pipecat CLI. Then use the CLI to monitor and deploy your agent to production.
🔍 Debugging
Looking for help debugging your pipeline and processors? Check out Whisker, a real-time Pipecat debugger.
🖥️ Terminal
Love terminal applications? Check out Tail, a terminal dashboard for Pipecat.
🤖 Claude Code Skills
Use Pipecat Skills with Claude Code to scaffold projects, deploy to Pipecat Cloud, and more. Install the marketplace with:
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 or check out our guide to create your own.
📺️ Pipecat TV Channel
Catch new features, interviews, and how-tos on our Pipecat TV channel.
🎬 See it in action
🧩 Available services
📚 View full services documentation →
⚡ Getting started
You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you're ready.
-
Install uv
curl -LsSf https://astral.sh/uv/install.sh | shNeed help? Refer to the uv install documentation.
-
Install the module
# For new projects uv init my-pipecat-app cd my-pipecat-app uv add pipecat-ai # Or for existing projects uv add pipecat-ai -
Set up your environment
cp env.example .env -
To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
uv add "pipecat-ai[option,...]"
Using pip? You can still use
pip install pipecat-aiandpip install "pipecat-ai[option,...]"to get set up.
🧪 Code examples
- Foundational — small snippets that build on each other, introducing one or two concepts at a time
- Example apps — 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
Setup Steps
-
Clone the repository and navigate to it:
git clone https://github.com/pipecat-ai/pipecat.git cd pipecat -
Install development and testing dependencies:
uv sync --group dev --all-extras \ --no-extra gstreamer \ --no-extra local \ -
Install the git pre-commit hooks:
uv run pre-commit install
Note
: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
Claude Code Skills
Install development workflow skills for contributing to Pipecat with Claude Code:
claude plugin marketplace add pipecat-ai/pipecat
claude plugin install pipecat-dev@pipecat-dev-skills
Running tests
To run all tests, from the root directory:
uv run pytest
Run a specific test suite:
uv run pytest tests/test_name.py
🤝 Contributing
We welcome contributions from the community! Whether you're fixing bugs, improving documentation, or adding new features, here's how you can help:
- Found a bug? Open an issue
- Have a feature idea? Start a discussion
- Want to contribute code? Check our CONTRIBUTING.md guide
- Documentation improvements? Docs PRs are always welcome
Before submitting a pull request, please check existing issues and PRs to avoid duplicates.
We aim to review all contributions promptly and provide constructive feedback to help get your changes merged.