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Author SHA1 Message Date
James Hush
dddfd791e1 Replace hello with banana 2025-04-18 14:18:32 +08:00
James Hush
e721c2086c Add banana processor 2025-04-18 14:14:22 +08:00
19 changed files with 202 additions and 828 deletions

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name: Bug report
description: Report a bug or unexpected behavior
type: Bug
body:
- type: markdown
attributes:
value: |
## Bug Report
Thank you for taking the time to fill out this bug report.
- type: markdown
attributes:
value: |
### Environment
- type: input
id: pipecat-version
attributes:
label: pipecat version
description: Which version are you using?
placeholder: e.g., 0.0.63
validations:
required: true
- type: input
id: python-version
attributes:
label: Python version
description: Which Python version are you using?
placeholder: e.g., 3.12.8
validations:
required: true
- type: input
id: os
attributes:
label: Operating System
description: Which OS are you using?
placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
validations:
required: true
- type: textarea
id: description
attributes:
label: Issue description
description: Provide a clear description of the issue.
validations:
required: true
- type: textarea
id: repro
attributes:
label: Reproduction steps
description: List the steps to reproduce the issue.
placeholder: |
1. Do this...
2. Then do that...
3. Observe the error...
validations:
required: true
- type: textarea
id: expected
attributes:
label: Expected behavior
description: What did you expect to happen?
validations:
required: true
- type: textarea
id: actual
attributes:
label: Actual behavior
description: What actually happened?
validations:
required: true
- type: textarea
id: logs
attributes:
label: Logs
description: If applicable, include any relevant logs or error messages
render: shell
validations:
required: false

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name: Question
description: Ask a question or get help
type: Question
body:
- type: markdown
attributes:
value: |
## Question
Use this form to ask a question about pipecat.
- type: markdown
attributes:
value: |
### Environment (if applicable)
- type: input
id: pipecat-version
attributes:
label: pipecat version
description: Which version are you using? (if applicable)
placeholder: e.g., 0.0.63
validations:
required: false
- type: input
id: python-version
attributes:
label: Python version
description: Which Python version are you using? (if applicable)
placeholder: e.g., 3.12.8
validations:
required: false
- type: input
id: os
attributes:
label: Operating System
description: Which OS are you using? (if applicable)
placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
validations:
required: false
- type: textarea
id: question
attributes:
label: Question
description: Provide your question in detail here.
validations:
required: true
- type: textarea
id: tried
attributes:
label: What I've tried
description: Describe what you've already tried or research you've done.
placeholder: I've looked at the documentation and tried...
validations:
required: false
- type: textarea
id: context
attributes:
label: Context
description: Any additional context or information that might help others understand your question better.
validations:
required: false

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name: Feature request
description: Suggest an enhancement or new feature
type: Enhancement
body:
- type: markdown
attributes:
value: |
## Feature Request
Thank you for suggesting an enhancement to pipecat.
- type: textarea
id: problem
attributes:
label: Problem Statement
description: A clear description of the problem this feature would solve.
placeholder: I'm always frustrated when...
validations:
required: true
- type: textarea
id: solution
attributes:
label: Proposed Solution
description: A clear and concise description of what you want to happen.
validations:
required: true
- type: textarea
id: alternatives
attributes:
label: Alternative Solutions
description: Any alternative solutions or features you've considered.
validations:
required: false
- type: textarea
id: context
attributes:
label: Additional Context
description: Add any other context, mockups, or screenshots about the feature request here.
placeholder: You can drag and drop images here to include them.
validations:
required: false
- type: checkboxes
id: contribution
attributes:
label: Would you be willing to help implement this feature?
options:
- label: Yes, I'd like to contribute
- label: No, I'm just suggesting

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name: Service Issue
description: An issue with a third-party service
type: Service Issue
body:
- type: markdown
attributes:
value: |
## Service Issue
Use this form to report an issue with a third-party service integration.
- type: input
id: pipecat-version
attributes:
label: pipecat version
description: Which version are you using?
placeholder: e.g., 0.0.63
validations:
required: true
- type: input
id: service-name
attributes:
label: Service Name
description: Which third-party service is having issues?
placeholder: e.g., OpenAI, ElevenLabs, Anthropic
validations:
required: true
- type: input
id: service-version
attributes:
label: Service or model version
description: Which version of the service API or model are you using?
placeholder: e.g., v1, gpt-4.1
validations:
required: false
- type: textarea
id: description
attributes:
label: Issue Description
description: Provide a clear description of the service issue.
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: Reproduction Steps
description: Provide steps to reproduce the issue.
placeholder: |
1. Configure service X
2. Call method Y
3. See error Z
validations:
required: true
- type: textarea
id: expected
attributes:
label: Expected Behavior
description: What did you expect to happen?
validations:
required: true
- type: textarea
id: actual
attributes:
label: Actual Behavior
description: What actually happened?
validations:
required: true
- type: textarea
id: logs
attributes:
label: Error Logs
description: If available, include any error messages or logs.
render: shell
validations:
required: false

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name: New Service
description: Request to support a new third-party service
type: New Service
body:
- type: markdown
attributes:
value: |
## New Service Request
Use this form to request support for a new third-party service in pipecat.
- type: input
id: service-name
attributes:
label: Service Name
description: What is the name of the third-party service?
placeholder: e.g., NewAPI, SomeService
validations:
required: true
- type: input
id: service-website
attributes:
label: Service Website
description: Link to the service's website or documentation
placeholder: e.g., https://newapi.com
validations:
required: true
- type: textarea
id: service-description
attributes:
label: Service Description
description: Briefly describe what this service does and how it works.
validations:
required: true
- type: textarea
id: api-info
attributes:
label: API Information
description: If available, provide details about the service's API.
placeholder: |
- API documentation link
- Authentication method
- Key endpoints you'd like supported
validations:
required: false
- type: checkboxes
id: contribution
attributes:
label: Would you be willing to help implement this service?
options:
- label: Yes, I'd like to contribute
- label: No, I'm just suggesting

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name: Dependency Issue
description: An issue with a Pipecat dependency (not a third-party service)
type: Dependency Issue
body:
- type: markdown
attributes:
value: |
## Dependency Issue
Use this form to report an issue with a Pipecat dependency.
- type: input
id: pipecat-version
attributes:
label: pipecat version
description: Which version are you using?
placeholder: e.g., 0.0.63
validations:
required: true
- type: input
id: dependency-name
attributes:
label: Dependency Name
description: Which Pipecat dependency is causing the issue?
placeholder: e.g., openai, anthropic, fastapi
validations:
required: true
- type: input
id: dependency-version
attributes:
label: Dependency Version
description: Which version of the dependency are you using?
placeholder: e.g., 1.2.3
validations:
required: true
- type: textarea
id: description
attributes:
label: Issue Description
description: Provide a clear description of the dependency issue.
validations:
required: true
- type: textarea
id: impact
attributes:
label: Impact
description: How is this dependency issue affecting your usage of pipecat?
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: Reproduction Steps
description: If applicable, provide steps to reproduce the issue.
placeholder: |
1. Install dependency X
2. Run command Y
3. See error Z
validations:
required: false
- type: textarea
id: logs
attributes:
label: Error Logs
description: If applicable, include any relevant error messages or logs.
render: shell
validations:
required: false

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name: Troubleshooting
description: Help with a specific use case
type: Troubleshooting
body:
- type: markdown
attributes:
value: |
## Troubleshooting Request
Use this form to get help with a specific use case or implementation.
- type: input
id: pipecat-version
attributes:
label: pipecat version
description: Which version are you using?
placeholder: e.g., 0.0.63
validations:
required: true
- type: input
id: python-version
attributes:
label: Python version
description: Which version of Python are you using?
placeholder: e.g., 3.12.8
validations:
required: true
- type: input
id: os
attributes:
label: Operating System
description: Which OS are you using?
placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
validations:
required: true
- type: textarea
id: use-case
attributes:
label: Use Case Description
description: Describe what you're trying to accomplish with pipecat.
validations:
required: true
- type: textarea
id: current-approach
attributes:
label: Current Approach
description: What have you tried so far? Include code snippets if relevant.
render: python
validations:
required: true
- type: textarea
id: errors
attributes:
label: Errors or Unexpected Behavior
description: Describe any errors or unexpected behavior you're encountering.
validations:
required: true
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Any other information that might help us understand your situation.
validations:
required: false

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blank_issues_enabled: false

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### Added
- Added support for Application Default Credentials in Google services,
`GoogleSTTService`, `GoogleTTSService`, and `GoogleVertexLLMService`.
- Added support for Smart Turn Detection via the `turn_analyzer` transport
parameter. You can now choose between `SmartTurnAnalyzer()` for remote
inference or `LocalCoreMLSmartTurnAnalyzer()` for on-device inference using
parameter. You can now choose between `SmartTurnAnalyzer()` for remote
inference or `LocalCoreMLSmartTurnAnalyzer()` for on-device inference using
Core ML.
- `DeepgramTTSService` accepts `base_url` argument again, allowing you to

233
README.md
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<h1><div align="center">
<img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
 <img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
</div></h1>
[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat)
# 🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents
Pipecat is an open source Python framework for building voice and multimodal conversational agents. It handles the complex orchestration of AI services, network transport, audio processing, and multimodal interactions, letting you focus on creating engaging experiences.
**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.
## What you can build
## 🚀 What You Can Build
- **Voice Assistants**: [Natural, real-time conversations with AI](https://demo.dailybots.ai/)
- **Interactive Agents**: Personal coaches and meeting assistants
- **Multimodal Apps**: Combine voice, video, images, and text
- **Creative Tools**: [Story-telling experiences](https://storytelling-chatbot.fly.dev/) and social companions
- **Business Solutions**: [Customer intake flows](https://www.youtube.com/watch?v=lDevgsp9vn0) and support bots
- **Complex conversational flows**: [Refer to Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) to learn more
- **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
🧭 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
## 🧠 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)
## 🎬 See it in action
## See it in action
<p float="left">
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/simple-chatbot/image.png" width="400" /></a>&nbsp;
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/storytelling-chatbot/image.png" width="400" /></a>
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/simple-chatbot/image.png" width="280" /></a>&nbsp;
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/storytelling-chatbot/image.png" width="280" /></a>
<br/>
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/translation-chatbot/image.png" width="400" /></a>&nbsp;
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/moondream-chatbot/image.png" width="400" /></a>
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/translation-chatbot/image.png" width="280" /></a>&nbsp;
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/moondream-chatbot/image.png" width="280" /></a>
</p>
## 📱 Client SDKs
## Key features
You can connect to Pipecat from any platform using our official SDKs:
- **Voice-first Design**: Built-in speech recognition, TTS, and conversation handling
- **Flexible Integration**: Works with popular AI services (OpenAI, ElevenLabs, etc.)
- **Pipeline Architecture**: Build complex apps from simple, reusable components
- **Real-time Processing**: Frame-based pipeline architecture for fluid interactions
- **Production Ready**: Enterprise-grade WebRTC and Websocket support
| Platform | SDK Repo | Description |
| -------- | ------------------------------------------------------------------------------ | -------------------------------- |
| Web | [pipecat-client-web](https://github.com/pipecat-ai/pipecat-client-web) | JavaScript and React client SDKs |
| iOS | [pipecat-client-ios](https://github.com/pipecat-ai/pipecat-client-ios) | Swift SDK for iOS |
| Android | [pipecat-client-android](https://github.com/pipecat-ai/pipecat-client-android) | Kotlin SDK for Android |
| C++ | [pipecat-client-cxx](https://github.com/pipecat-ai/pipecat-client-cxx) | C++ client SDK |
💡 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
## 🧩 Available services
## Getting started
| Category | Services |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) |
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
## ⚡ Getting started
You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when youre ready.
You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when youre ready. You can also add a 📞 telephone number, 🖼️ image output, 📺 video input, use different LLMs, and more.
```shell
# Install the module
@@ -82,51 +53,141 @@ To keep things lightweight, only the core framework is included by default. If y
pip install "pipecat-ai[option,...]"
```
## 🧪 Code examples
### Available services
| Category | Services | Install Command Example |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[google]"` |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) | `pip install "pipecat-ai[mem0]"` |
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) | `pip install "pipecat-ai[moondream]"` |
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
## Code examples
- [Foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational) — small snippets that build on each other, introducing one or two concepts at a time
- [Example apps](https://github.com/pipecat-ai/pipecat/tree/main/examples/) — complete applications that you can use as starting points for development
## 🛠️ Hacking on the framework itself
## A simple voice agent running locally
1. Set up a virtual environment before following these instructions. From the root of the repo:
Here is a very basic Pipecat bot that greets a user when they join a real-time session. We'll use [Daily](https://daily.co) for real-time media transport, and [Cartesia](https://cartesia.ai/) for text-to-speech.
```shell
python3 -m venv venv
source venv/bin/activate
```
```python
import asyncio
2. Install the development dependencies:
from pipecat.frames.frames import TextFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.task import PipelineTask
from pipecat.pipeline.runner import PipelineRunner
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport
```shell
pip install -r dev-requirements.txt
```
async def main():
# Use Daily as a real-time media transport (WebRTC)
transport = DailyTransport(
room_url=...,
token="", # leave empty. Note: token is _not_ your api key
bot_name="Bot Name",
params=DailyParams(audio_out_enabled=True))
3. Install the git pre-commit hooks (these help ensure your code follows project rules):
# Use Cartesia for Text-to-Speech
tts = CartesiaTTSService(
api_key=...,
voice_id=...
)
```shell
pre-commit install
```
# Simple pipeline that will process text to speech and output the result
pipeline = Pipeline([tts, transport.output()])
4. Install the `pipecat-ai` package locally in editable mode:
# Create Pipecat processor that can run one or more pipelines tasks
runner = PipelineRunner()
```shell
pip install -e .
```
# Assign the task callable to run the pipeline
task = PipelineTask(pipeline)
> The `-e` or `--editable` option allows you to modify the code without reinstalling.
# Register an event handler to play audio when a
# participant joins the transport WebRTC session
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
participant_name = participant.get("info", {}).get("userName", "")
# Queue a TextFrame that will get spoken by the TTS service (Cartesia)
await task.queue_frame(TextFrame(f"Hello there, {participant_name}!"))
5. Include optional dependencies as needed. For example:
# Register an event handler to exit the application when the user leaves.
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.cancel()
```shell
pip install -e ".[daily,deepgram,cartesia,openai,silero]"
```
# Run the pipeline task
await runner.run(task)
6. (Optional) If you want to use this package from another directory:
if __name__ == "__main__":
asyncio.run(main())
```
```shell
pip install "path_to_this_repo[option,...]"
```
Run it with:
```shell
python app.py
```
Daily provides a prebuilt WebRTC user interface. While the app is running, you can visit at `https://<yourdomain>.daily.co/<room_url>` and listen to the bot say hello!
## WebRTC for production use
WebSockets are fine for server-to-server communication or for initial development. But for production use, youll need client-server audio to use a protocol designed for real-time media transport. (For an explanation of the difference between WebSockets and WebRTC, see [this post.](https://www.daily.co/blog/how-to-talk-to-an-llm-with-your-voice/#webrtc))
One way to get up and running quickly with WebRTC is to sign up for a Daily developer account. Daily gives you SDKs and global infrastructure for audio (and video) routing. Every account gets 10,000 audio/video/transcription minutes free each month.
Sign up [here](https://dashboard.daily.co/u/signup) and [create a room](https://docs.daily.co/reference/rest-api/rooms) in the developer Dashboard.
## Hacking on the framework itself
_Note: You may need to set up a virtual environment before following these instructions. From the root of the repo:_
```shell
python3 -m venv venv
source venv/bin/activate
```
Install the development dependencies:
```shell
pip install -r dev-requirements.txt
```
Install the git pre-commit hooks (these help ensure your code follows project rules):
```shell
pre-commit install
```
Install the `pipecat-ai` package locally in editable mode:
```shell
pip install -e .
```
The `-e` or `--editable` option allows you to modify the code without reinstalling.
To include optional dependencies, add them to the install command. For example:
```shell
pip install -e ".[daily,deepgram,cartesia,openai,silero]" # Updated for the services you're using
```
If you want to use this package from another directory:
```shell
pip install "path_to_this_repo[option,...]"
```
### Running tests
@@ -136,11 +197,11 @@ From the root directory, run:
pytest
```
### Setting up your editor
## Setting up your editor
This project uses strict [PEP 8](https://peps.python.org/pep-0008/) formatting via [Ruff](https://github.com/astral-sh/ruff).
#### Emacs
### Emacs
You can use [use-package](https://github.com/jwiegley/use-package) to install [emacs-lazy-ruff](https://github.com/christophermadsen/emacs-lazy-ruff) package and configure `ruff` arguments:
@@ -162,7 +223,7 @@ You can use [use-package](https://github.com/jwiegley/use-package) to install [e
:hook ((python-mode . pyvenv-auto-run)))
```
#### Visual Studio Code
### Visual Studio Code
Install the
[Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff) extension. Then edit the user settings (_Ctrl-Shift-P_ `Open User Settings (JSON)`) and set it as the default Python formatter, and enable formatting on save:
@@ -174,7 +235,7 @@ Install the
}
```
#### PyCharm
### PyCharm
`ruff` was installed in the `venv` environment described before, now to enable autoformatting on save, go to `File` -> `Settings` -> `Tools` -> `File Watchers` and add a new watcher with the following settings:
@@ -184,7 +245,7 @@ Install the
4. **Arguments**: `format $FilePath$`
5. **Program**: `$PyInterpreterDirectory$/ruff`
## 🤝 Contributing
## Contributing
We welcome contributions from the community! Whether you're fixing bugs, improving documentation, or adding new features, here's how you can help:
@@ -197,7 +258,7 @@ Before submitting a pull request, please check existing issues and PRs to avoid
We aim to review all contributions promptly and provide constructive feedback to help get your changes merged.
## 🛟 Getting help
## Getting help
➡️ [Join our Discord](https://discord.gg/pipecat)

22
docs/ISSUE_TEMPLATE.md Normal file
View File

@@ -0,0 +1,22 @@
# Description
Is this reporting a bug or feature request?
If reporting a bug, please fill out the following:
### Environment
- pipecat-ai version:
- python version:
- OS:
### Issue description
Provide a clear description of the issue.
### Repro steps
List the steps to reproduce the issue.
### Expected behavior
### Actual behavior
### Logs

View File

@@ -9,10 +9,11 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
from pipecat.frames.frames import EndFrame, TranscriptionFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport

View File

@@ -10,7 +10,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import Frame, MetricsFrame
from pipecat.frames.frames import Frame, MetricsFrame, TranscriptionFrame, TTSSpeakFrame
from pipecat.metrics.metrics import (
LLMUsageMetricsData,
ProcessingMetricsData,
@@ -32,7 +32,30 @@ from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
load_dotenv(override=True)
# Custom processor that prints a message if it receives a TranscriptionFrame that says "banana"
class BananaProcessor(FrameProcessor):
"""A custom processor that listens for transcription frames containing the word 'banana'."""
def __init__(self):
super().__init__()
async def process_frame(self, frame: Frame, direction: FrameDirection):
# Ensure the super method is called first
await super().process_frame(frame, direction)
if isinstance(frame, TranscriptionFrame):
logger.debug(f"Received transcription frame: {frame.text}")
if "banana" in frame.text.lower():
logger.info("---- Received 'banana' in transcription frame")
# Push the frame after processing
await self.push_frame(frame)
class MetricsLogger(FrameProcessor):
def __init__(self):
super().__init__()
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
@@ -87,10 +110,13 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
banana = BananaProcessor()
pipeline = Pipeline(
[
transport.input(),
stt,
banana,
context_aggregator.user(),
llm,
tts,

View File

@@ -40,7 +40,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
stt = OpenAISTTService(
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o-transcribe",
model="gpt-4o-transcribe-latest",
prompt="Expect words related to dogs, such as breed names.",
)

View File

@@ -1,211 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import EndFrame, EndTaskFrame, Frame, TextFrame, TTSSpeakFrame
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.gated_openai_llm_context import GatedOpenAILLMContextAggregator
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.filters.null_filter import NullFilter
from pipecat.processors.filters.wake_notifier_filter import WakeNotifierFilter
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.processors.user_idle_processor import UserIdleProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.sync.event_notifier import EventNotifier
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
load_dotenv(override=True)
class KickParticipantProcessor(FrameProcessor):
"""This processor will kick the participant if they say something inappropriate.
This is a simple example of how to use the LLM to moderate
the conversation. In this case we are using the OpenAI LLM to determine if
the user is saying something inappropriate.
"""
def __init__(self):
"""Initialize the processor."""
super().__init__()
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
if isinstance(frame, TextFrame) and frame.text == "YES":
await self.push_frame(
TTSSpeakFrame(
"You are being kicked from the call because of content moderation. Have a nice day!"
)
)
# Signal that the task should end after processing this frame
await self.push_frame(EndTaskFrame(), FrameDirection.UPSTREAM)
else:
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
# This is the LLM that will be used to detect if the user has said
# something inappropriate.
moderator_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
moderator_messages = [
{
"role": "system",
"content": """
You are a helpful LLM that will be used to moderate a conversation
between a user and an assistant. Your goal is to determine if the user
is saying something inappropriate. You will be given the user
transcript and you will have to determine if the user is saying
something inappropriate. If you think the user is saying something
inappropriate please respond with "YES". If you think the user is
saying something appropriate please respond with "NO". Examples of inappropriate
content are: hate speech, racism, sexism, bullying, harassment,
violence, self-harm, and any other content that violates the
community guidelines.
""",
},
]
moderator_context = OpenAILLMContext(moderator_messages)
moderator_context_aggregator = moderator_llm.create_context_aggregator(moderator_context)
# This is the regular LLM.
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
},
]
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
# We have instructed the LLM to return 'YES' if it thinks the user
# completed a sentence. So, if it's 'YES' we will return true in this
# predicate which will wake up the notifier.
async def wake_check_filter(frame):
return frame.text == "YES"
# This is a notifier that we use to synchronize the two LLMs.
notifier = EventNotifier()
# This a filter that will wake up the notifier if the given predicate
# (wake_check_filter) returns true.
completeness_check = WakeNotifierFilter(notifier, types=(TextFrame,), filter=wake_check_filter)
# This processor keeps the last context and will let it through once the
# notifier is woken up. We start with the gate open because we send an
# initial context frame to start the conversation.
gated_context_aggregator = GatedOpenAILLMContextAggregator(notifier=notifier, start_open=True)
# Notify if the user hasn't said anything.
async def user_idle_notifier(frame):
await notifier.notify()
# Sometimes the LLM will fail detecting if a user should be
# moderated, this will wake up the notifier if that happens.
user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=3.0)
kick_participant = KickParticipantProcessor()
# The ParallePipeline input are the user transcripts. We have two
# contexts. The first one will be used to determine if the user is
# moderated and if so the notifier will be woken up. The second
# context is simply the regular context but it's gated waiting for the
# notifier to be woken up.
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
ParallelPipeline(
[
moderator_context_aggregator.user(),
moderator_llm,
kick_participant,
# completeness_check,
NullFilter(),
],
[context_aggregator.user(), gated_context_aggregator, llm],
),
user_idle,
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
report_only_initial_ttfb=True,
),
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
await runner.run(task)
if __name__ == "__main__":
from run import main
main()

View File

@@ -17,8 +17,6 @@ from loguru import logger
from pipecat.services.openai.llm import OpenAILLMService
try:
from google.auth import default
from google.auth.exceptions import GoogleAuthError
from google.auth.transport.requests import Request
from google.oauth2 import service_account
@@ -102,13 +100,6 @@ class GoogleVertexLLMService(OpenAILLMService):
creds = service_account.Credentials.from_service_account_file(
credentials_path, scopes=["https://www.googleapis.com/auth/cloud-platform"]
)
else:
try:
creds, project_id = default(
scopes=["https://www.googleapis.com/auth/cloud-platform"]
)
except GoogleAuthError:
pass
if not creds:
raise ValueError("No valid credentials provided.")

View File

@@ -32,8 +32,6 @@ from pipecat.utils.time import time_now_iso8601
try:
from google.api_core.client_options import ClientOptions
from google.auth import default
from google.auth.exceptions import GoogleAuthError
from google.cloud import speech_v2
from google.cloud.speech_v2.types import cloud_speech
from google.oauth2 import service_account
@@ -453,7 +451,6 @@ class GoogleSTTService(STTService):
client_options = ClientOptions(api_endpoint=f"{self._location}-speech.googleapis.com")
# Extract project ID and create client
creds: Optional[service_account.Credentials] = None
if credentials:
json_account_info = json.loads(credentials)
self._project_id = json_account_info.get("project_id")
@@ -464,16 +461,7 @@ class GoogleSTTService(STTService):
self._project_id = json_account_info.get("project_id")
creds = service_account.Credentials.from_service_account_file(credentials_path)
else:
try:
creds, project_id = default(
scopes=["https://www.googleapis.com/auth/cloud-platform"]
)
self._project_id = project_id
except GoogleAuthError:
pass
if not creds:
raise ValueError("No valid credentials provided.")
raise ValueError("Either credentials or credentials_path must be provided")
if not self._project_id:
raise ValueError("Project ID not found in credentials")

View File

@@ -27,8 +27,6 @@ from pipecat.services.tts_service import TTSService
from pipecat.transcriptions.language import Language
try:
from google.auth import default
from google.auth.exceptions import GoogleAuthError
from google.cloud import texttospeech_v1
from google.oauth2 import service_account
@@ -253,16 +251,6 @@ class GoogleTTSService(TTSService):
elif credentials_path:
# Use service account JSON file if provided
creds = service_account.Credentials.from_service_account_file(credentials_path)
else:
try:
creds, project_id = default(
scopes=["https://www.googleapis.com/auth/cloud-platform"]
)
except GoogleAuthError:
pass
if not creds:
raise ValueError("No valid credentials provided.")
return texttospeech_v1.TextToSpeechAsyncClient(credentials=creds)