e5941926be
* VIVA SDK TT v3 support * Format fix. * Renamed the API naming, removed '3' from the name. * Implementation of User turn start strategy using Krisp VIVA Interruption Prediction in scope of TT v3 support. * TT demo tool * Some improvements for demo scripts, audio recordin, etc. * Enhance demo scripts with VAD selection and audio embedding features. Updated HTML report to include annotated audio players and improved response time metrics in summary formatting. Added README for setup and usage instructions. * Refactor interrupt prediction demo to compare multiple interruption strategies (Krisp IP vs VAD). Updated README with usage instructions and output details. Enhanced audio processing with new helper functions for generating beeps and mixing audio. * Refactor demo scripts to improve latency metrics by introducing total_delay property in TurnEvent. Update formatting in reports and visualizations to reflect accurate speech end times, including VAD wait times. Enhance HTML report with detailed latency information and adjust audio processing to account for VAD stop seconds. * Add audio resampling functionality and update demo scripts for improved audio processing - Introduced `resample_audio` function to handle audio resampling with linear interpolation. - Updated `demo_audio_recorder.py` to utilize the new resampling feature, ensuring audio is saved at the requested sample rate. - Modified `demo_interrupt_prediction.py` and `demo_turn_taking.py` to resample audio to 16 kHz for compatibility with Silero VAD. - Adjusted imports in demo scripts to include the new resampling function. - Enhanced error handling for sample rate discrepancies in audio recording. * Enhance demo_interrupt_prediction.py with VAD type selection and improved processing logic - Added support for selecting between "silero" and "krisp" VAD engines in the demo script. - Introduced a new create_vad function to configure VAD analyzers based on the selected type. - Updated audio processing logic to handle VAD type-specific resampling and state management. - Modified the KrispVivaIPUserTurnStartStrategy to utilize a separate vad_flag for per-frame VAD input, improving interruption detection accuracy. * Refactor audio processing scripts for improved readability and consistency - Updated type hinting in `resample_audio` function to use `tuple` instead of `Tuple`. - Simplified print statements in `demo_audio_recorder.py`, `demo_formatting.py`, and `demo_interrupt_prediction.py` for better readability. - Adjusted argument formatting in `demo_audio_recorder.py` and `demo_formatting.py` for consistency. - Cleaned up list comprehensions in `demo_formatting.py`, `demo_html_report.py`, and `demo_interrupt_prediction.py` for clarity. - Enhanced error handling in `__init__.py` for the KrispVivaIPUserTurnStartStrategy import. * Refactor VAD handling in KrispVivaIPUserTurnStartStrategy and update tests for clarity - Simplified the argument formatting in the _handle_vad_started method for improved readability. - Updated test assertions to reflect changes in VAD processing logic, ensuring that the vad_flag is correctly set to False during continuous state processing. - Enhanced test cases to verify that the process method is called appropriately under different conditions. * more format fixes. * removed demo scripts. * reverted wrongly removed file. * Corrected the IP integration logic. * style fix. * Refactor audio processing and state management in KrispVivaIPUserTurnStartStrategy - Removed the unused _vad_flag attribute to streamline state tracking. - Updated the reset method to clear the audio buffer instead of resetting the vad_flag. - Adjusted the process_frame method to use _speech_active for VAD input, enhancing clarity in the logic. - Modified tests to reflect changes in state management and ensure proper functionality of the reset method and audio buffer handling. * FIxed formatting --------- Co-authored-by: Aram Poghosyan <apoghosyan@krisp.ai>
🎙️ 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.