pipecat README

The project's README from github.com/pipecat-ai/pipecat. As one markdown file: README.md.

pipecat

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🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents

Pipecat is an open-source Python framework for building real-time voice and multimodal conversational agents. Build a single voice agent or a full multi-agent system where specialists hand off, fan out in parallel, and coordinate over a shared bus, locally or distributed across processes and machines. Orchestrate audio and video, AI services, transports, and conversation pipelines effortlessly, so you can focus on what makes your agents unique.

Want to dive right in? Run pipecat init quickstart or follow the quickstart guide.

🚀 What you can build

🧠 Why Pipecat?

🌐 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

Need predefined or dynamic conversation paths with state management? Pipecat Flows is built into Pipecat. Browse the examples to see it in action.

🪄 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

The Pipecat CLI ships with pipecat-ai — install it with uv tool install "pipecat-ai[cli]". Run pipecat init to start a project: it sets you up so an AI coding assistant (Claude Code, Codex) builds it for you, and can scaffold a runnable bot in under a minute. 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

Category Services
Speech-to-Text AssemblyAI, AWS, Azure, Cartesia, Deepgram, ElevenLabs, Fal Wizper, FunASR, Gladia, Google, Gradium, Groq (Whisper), Meta, Mistral, Moonshine, NVIDIA, OpenAI (Whisper), Sarvam, Soniox, Speechmatics, Together, Whisper, xAI
LLMs Anthropic, AWS, Azure, Baseten, Cerebras, Crusoe, DeepSeek, Fireworks AI, Gemini, Grok, Groq, Inception, Mistral, Nebius, Novita, NVIDIA NIM, Ollama, OpenAI, OpenAI Responses, OpenRouter, Perplexity, Qwen, SambaNova, Sarvam, Together AI
Text-to-Speech Async, AWS, Azure, Bland, Camb AI, Cartesia, Deepgram, ElevenLabs, Fish, Google, Gradium, Groq, Hume, Inworld, Kokoro, MiniMax, Mistral, Neuphonic, NVIDIA, OpenAI, Piper, Resemble, Rime, Sarvam, Smallest, Soniox, Speechify, Speechmatics, Together, xAI, XTTS
Speech-to-Speech AWS Nova Sonic, Gemini Multimodal Live, Grok Voice Agent, OpenAI Realtime, Ultravox,

pipecat (pipecat-ai/pipecat)

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这是什么?Pipecat 是一个开源的 Python 框架,用于构建实时的语音和多模态对话智能体——从单个语音机器人到分布式多智能体系统都可以,由 Daily 和社区共同维护。
所以它是我写代码时用的框架,不是一个装好就能用的现成应用?它是一个代码优先的 Python 框架:你可以用模块化的组件(语音、AI 服务、传输层)组装出智能体流水线,并在服务器端运行。
怎么让我的第一个智能体跑起来?运行 pipecat init quickstart 就能得到一个能跑的智能体,也可以按照 README 里链接的快速入门指南操作。
我可以接入哪些语音和 AI 服务?它内置了几十种服务的适配器:语音转文字(Deepgram、AssemblyAI、Whisper)、大语言模型(OpenAI、Anthropic、Gemini、Ollama)、文字转语音(ElevenLabs、Cartesia、Piper),以及语音到语音(OpenAI Realtime、Gemini Multimodal Live)。
这是给写代码的开发者用的,还是有免代码的可视化编辑器?面向开发者:你通过编写 Python 流水线来构建智能体;README 里没有提到任何可视化或免代码的构建工具。
我的应用或设备怎么连接到 Pipecat 智能体?客户端通过 WebSocket 或 WebRTC 这类超低延迟的实时传输方式连接,官方客户端 SDK 让你可以从任何平台接入。
我到底能用它做出什么?README 重点提到的应用包括:语音助手、多智能体系统、AI 伙伴(比如教练或会议助手)、带语音和视频的多模态界面、结合生成媒体的互动叙事、面向客服和信息登记的业务智能体,以及结构化的对话系统。
它能运行多个相互配合的智能体吗?可以。每条流水线就是一个智能体,Pipecat 支持多个专职智能体相互转接、并行分发、作为 sidecar 工作进程运行,或通过共享总线协同——既可以在本地,也可以分布在不同进程和机器上。
我必须用付费的云服务 API,还是也能跑本地模型?本地方案也在支持的适配器之列:大语言模型可用 Ollama,文字转语音可用 Piper 和 Kokoro,语音转文字可用 Whisper 或 FunASR。
它快不快?能不能支撑自然的来回对话?Pipecat 就是为实时场景打造的:它以超低延迟交互为目标,并支持 WebSocket 和 WebRTC 等传输方式。
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