pipecat-ai/pipecat

Pipecat – Real‑time Voice & Multimodal AI Agent Framework

Pipecat is an open‑source Python library that lets you assemble conversational agents that talk, listen, see and act in real time. It provides a plug‑and‑play architecture for stitching together speech‑to‑text, large‑language‑model (LLM) back‑ends, text‑to‑speech, vision models, and custom processing steps into composable pipelines. Pipelines can be single‑agent bots or full multi‑agent systems where specialised agents hand‑off, run in parallel, or act as side‑cars, all coordinated over a shared bus that can be local or distributed across machines.

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What you can build with Pipecat

• Voice assistants – streaming, low‑latency conversations powered by any supported STT, LLM and TTS service.
• Multi‑agent systems – chains of specialist agents that hand‑off or fan‑out, useful for complex dialog flows.
• AI companions & business bots – coaches, meeting assistants, customer‑intake flows, etc.
• Multimodal interfaces – combine voice with video, images or other media.
• Interactive storytelling – generative media pipelines for games or creative tools.
• Structured dialog – Pipecat Flows give you state‑ful, predefined conversation paths.

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Core ideas

Idea	What it means
Voice‑first	Built‑in support for speech‑recognition, LLM reasoning, and text‑to‑speech in a single streaming pipeline.
Pluggable services	Over 30 STT, 30 LLM, and 30 TTS providers are supported out of the box (e.g., OpenAI Whisper, Anthropic, ElevenLabs, Azure, NVIDIA, etc.).
Composable pipelines	Pipelines are made from modular processors; you can mix‑and‑match any services you like.
Multi‑agent ready	Each pipeline can be an agent; a shared bus lets agents hand‑off, run side‑cars, or fan‑out in parallel, locally or across processes/machines.
Real‑time	Designed for ultra‑low latency transports such as WebSockets or WebRTC.

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Ecosystem & tooling

• Client SDKs – Official libraries for JavaScript, React, React‑Native, Swift, Kotlin, C++, and even ESP32, so front‑ends can talk to a Pipecat server.
• Pipecat CLI – pipecat init scaffolds a new project (using Claude Code for code generation) and provides commands to monitor and deploy agents.
• Pipecat Flows – Structured conversation framework with examples in the repo.
• Pipecat UI – A component library (shadcn‑style) for building beautiful voice‑AI front‑ends.
• Whisker – Real‑time debugger for pipelines.
• Tail – Terminal dashboard for observing agents.
• Skills marketplace – Claude Code plugins that can scaffold, deploy, or add new services.
• Community integrations – Docs and a guide for publishing your own service adapters.
• Pipecat TV – YouTube playlist with demos, interviews and tutorials.

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Getting started

# Install the library and CLI (uv is optional)
uv tool install "pipecat-ai[cli]"
# Scaffold a quick project
pipecat init quickstart

The quick‑start guide walks you through a runnable bot in under a minute.

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Documentation & resources

• Full docs: https://docs.pipecat.ai
• Examples repository: https://github.com/pipecat-ai/pipecat-examples (chatbot, storytelling, vision, translation, etc.)
• Discord community: https://discord.gg/pipecat
• PyPI package: pipecat-ai

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Who might use Pipecat?

• Developers building voice‑first consumer apps or enterprise bots.
• Researchers prototyping multimodal agent architectures.
• Teams needing a plug‑and‑play way to experiment with many STT/LLM/TTS providers without writing glue code.
• Anyone who wants a real‑time, extensible framework for orchestrating multiple AI services into coherent conversational experiences.

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TL;DR

Pipecat is a Python framework that lets you create streaming voice and multimodal AI agents quickly, with a rich library of supported speech, language, and vision services, composable pipelines, and a full ecosystem of client SDKs, CLI tools, UI components, and debugging utilities.

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Links

• Repo: https://github.com/pipecat-ai/pipecat
• Docs: https://docs.pipecar.ai (typo in original – actual link is https://docs.pipecat.ai)
• Discord: https://discord.gg/pipecat