Skip to main content

An open source framework for voice (and multimodal) assistants

Project description

pipecat

PyPI Tests codecov Docs Discord Ask DeepWiki

🎙️ 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? Try the quickstart.

🚀 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

📱 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.

📺️ Pipecat TV Channel

Catch new features, interviews, and how-tos on our Pipecat TV channel.

🎬 See it in action

 
 

🧩 Available services

Category Services
Speech-to-Text AssemblyAI, AWS, Azure, Cartesia, Deepgram, ElevenLabs, Fal Wizper, Gladia, Google, Groq (Whisper), NVIDIA Riva, OpenAI (Whisper), SambaNova (Whisper), Soniox, Speechmatics, Ultravox, Whisper
LLMs Anthropic, AWS, Azure, Cerebras, DeepSeek, Fireworks AI, Gemini, Grok, Groq, Mistral, NVIDIA NIM, Ollama, OpenAI, OpenRouter, Perplexity, Qwen, SambaNova Together AI
Text-to-Speech Async, AWS, Azure, Cartesia, Deepgram, ElevenLabs, Fish, Google, Groq, Hume, Inworld, LMNT, MiniMax, Neuphonic, NVIDIA Riva, OpenAI, Piper, PlayHT, Rime, Sarvam, XTTS
Speech-to-Speech AWS Nova Sonic, Gemini Multimodal Live, OpenAI Realtime
Transport Daily (WebRTC), FastAPI Websocket, SmallWebRTCTransport, WebSocket Server, Local
Serializers Plivo, Twilio, Telnyx
Video HeyGen, Tavus, Simli
Memory mem0
Vision & Image fal, Google Imagen, Moondream
Audio Processing Silero VAD, Krisp, Koala, ai-coustics
Analytics & Metrics OpenTelemetry, Sentry

📚 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.

  1. Install uv

    curl -LsSf https://astral.sh/uv/install.sh | sh
    

    Need help? Refer to the uv install documentation.

  2. 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
    
  3. Set up your environment

    cp env.example .env
    
  4. 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-ai and pip 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: 3.10 Recommended Python Version: 3.12

Setup Steps

  1. Clone the repository and navigate to it:

    git clone https://github.com/pipecat-ai/pipecat.git
    cd pipecat
    
  2. Install development and testing dependencies:

    uv sync --group dev --all-extras \
      --no-extra gstreamer \
      --no-extra krisp \
      --no-extra local \
      --no-extra ultravox # (ultravox not fully supported on macOS)
    
  3. 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.

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.

🛟 Getting help

➡️ Join our Discord

➡️ Read the docs

➡️ Reach us on X

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dv_pipecat_ai-0.0.85.dev882.tar.gz (12.7 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dv_pipecat_ai-0.0.85.dev882-py3-none-any.whl (12.4 MB view details)

Uploaded Python 3

File details

Details for the file dv_pipecat_ai-0.0.85.dev882.tar.gz.

File metadata

  • Download URL: dv_pipecat_ai-0.0.85.dev882.tar.gz
  • Upload date:
  • Size: 12.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for dv_pipecat_ai-0.0.85.dev882.tar.gz
Algorithm Hash digest
SHA256 e2b705cbec41ea906c062e560ec38fd0c1abea9f8ece3afe27c956b44dceebb8
MD5 8612b230b8c20894ea6c586dcabe19b8
BLAKE2b-256 c3ab99a18ce48aa7ee3db22740d23f1140f7db833787187c97306810bd0c8bf9

See more details on using hashes here.

File details

Details for the file dv_pipecat_ai-0.0.85.dev882-py3-none-any.whl.

File metadata

File hashes

Hashes for dv_pipecat_ai-0.0.85.dev882-py3-none-any.whl
Algorithm Hash digest
SHA256 efb9bc77e5d347e3171c5323ca169eb40230407971a737618cff37d6773b61fd
MD5 1aaceb0f915c78decc9ab97822081e6b
BLAKE2b-256 14de4360ef4d4fae17e590932f71abd4fccdace2f98b7682b7d42824bcb8d54d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page