minor updates to get started and working on latest modal

pyproject: fix license fields

.github/ISSUE_TEMPLATE/1-bug_report.yml

@@ -0,0 +1,87 @@
+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

.github/ISSUE_TEMPLATE/2-question.yml

@@ -0,0 +1,67 @@
+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

.github/ISSUE_TEMPLATE/3-feature_request.yml

@@ -0,0 +1,52 @@
+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

.github/ISSUE_TEMPLATE/4-service-issue.yml

@@ -0,0 +1,82 @@
+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

.github/ISSUE_TEMPLATE/5-new-service.yml

@@ -0,0 +1,56 @@
+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

.github/ISSUE_TEMPLATE/6-dependency.yml

@@ -0,0 +1,74 @@
+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

.github/ISSUE_TEMPLATE/7-troubleshooting.yml

@@ -0,0 +1,70 @@
+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

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1 @@
+blank_issues_enabled: false

CHANGELOG.md

@@ -9,6 +9,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added `SmartTurnMetricsData`, which contains end-of-turn prediction metrics,
+  to the `MetricsFrame`. Using `MetricsFrame`, you can now retrieve prediction
+  confidence scores and processing time metrics from the smart turn analyzers.
+
+- 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
+  Core ML.
+
 - `DeepgramTTSService` accepts `base_url` argument again, allowing you to
   connect to an on-prem service.
 
@@ -55,6 +67,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- Fixed an issue that would cause TTS websocket-based services to not cleanup
+  resources properly when disconnecting.
+
 - Fixed a `TavusVideoService` issue that was causing audio choppiness.
 
 - Fixed an issue in `SmallWebRTCTransport` where an error was thrown if the

README.md

@@ -1,43 +1,72 @@
 <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 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: Real-Time Voice & Multimodal AI Agents
 
-## What you can build
+**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.
 
-- **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
+## 🚀 What You Can Build
 
-## See it in action
+- **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
 
 <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="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>
+    <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>
     <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="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>
+    <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>
 </p>
 
-## Key features
+## 📱 Client 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
+You can connect to Pipecat from any platform using our official SDKs:
 
-💡 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
+| 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                   |
 
-## Getting started
+## 🧩 Available services
 
-You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you’re ready. You can also add a 📞 telephone number, 🖼️ image output, 📺 video input, use different LLMs, and more.
+| 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 you’re ready.
 
 ```shell
 # Install the module
@@ -53,141 +82,51 @@ To keep things lightweight, only the core framework is included by default. If y
 pip install "pipecat-ai[option,...]"
 ```
 
-### 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
+## 🧪 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
 
-## A simple voice agent running locally
+## 🛠️ Hacking on the framework itself
 
-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.
+1. Set up a virtual environment before following these instructions. From the root of the repo:
 
-```python
-import asyncio
+   ```shell
+   python3 -m venv venv
+   source venv/bin/activate
+   ```
 
-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
+2. Install the development dependencies:
 
-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))
+   ```shell
+   pip install -r dev-requirements.txt
+   ```
 
-  # Use Cartesia for Text-to-Speech
-  tts = CartesiaTTSService(
-    api_key=...,
-    voice_id=...
-  )
+3. Install the git pre-commit hooks (these help ensure your code follows project rules):
 
-  # Simple pipeline that will process text to speech and output the result
-  pipeline = Pipeline([tts, transport.output()])
+   ```shell
+   pre-commit install
+   ```
 
-  # Create Pipecat processor that can run one or more pipelines tasks
-  runner = PipelineRunner()
+4. Install the `pipecat-ai` package locally in editable mode:
 
-  # Assign the task callable to run the pipeline
-  task = PipelineTask(pipeline)
+   ```shell
+   pip install -e .
+   ```
 
-  # 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}!"))
+   > The `-e` or `--editable` option allows you to modify the code without reinstalling.
 
-  # 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()
+5. Include optional dependencies as needed. For example:
 
-  # Run the pipeline task
-  await runner.run(task)
+   ```shell
+   pip install -e ".[daily,deepgram,cartesia,openai,silero]"
+   ```
 
-if __name__ == "__main__":
-  asyncio.run(main())
-```
+6. (Optional) If you want to use this package from another directory:
 
-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, you’ll 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,...]"
-```
+   ```shell
+   pip install "path_to_this_repo[option,...]"
+   ```
 
 ### Running tests
 
@@ -197,11 +136,11 @@ 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:
 
@@ -223,7 +162,7 @@ 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:
@@ -235,7 +174,7 @@ 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:
 
@@ -245,7 +184,7 @@ 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:
 
@@ -258,7 +197,7 @@ 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)
 

docs/ISSUE_TEMPLATE.md

@@ -1,22 +0,0 @@
-# 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

dot-env.template

@@ -92,4 +92,8 @@ ASSEMBLYAI_API_KEY=...
 OPENROUTER_API_KEY=...
 
 # Piper
-PIPER_BASE_URL=...
+PIPER_BASE_URL=...
+
+# Smart turn
+LOCAL_SMART_TURN_MODEL_PATH=
+REMOTE_SMART_TURN_URL=

examples/deployment/modal-example/app.py

@@ -10,24 +10,27 @@ import aiohttp
 import modal
 from bot import _voice_bot_process
 from fastapi import HTTPException
-from fastapi.responses import JSONResponse
+from fastapi.responses import RedirectResponse
 from loguru import logger
 
 MAX_SESSION_TIME = 15 * 60  # 15 minutes
 
-app = modal.App("pipecat-modal")
-
-
-image = modal.Image.debian_slim(python_version="3.12").pip_install_from_requirements(
-    "requirements.txt"
+image = (
+    modal.Image.debian_slim(python_version="3.13")
+    .apt_install("ffmpeg")
+    .pip_install_from_requirements("requirements.txt")
+    .pip_install("pipecat-ai[daily,silero,cartesia,openai]")
+    .add_local_python_source("bot")
 )
 
+app = modal.App("pipecat-modal", image=image)
+
 
 @app.function(
     image=image,
     cpu=1.0,
     secrets=[modal.Secret.from_dotenv()],
-    keep_warm=1,
+    min_containers=1,
     enable_memory_snapshot=True,
     max_inputs=1,  # Do not reuse instances across requests
     retries=0,
@@ -40,7 +43,7 @@ def launch_bot_process(room_url: str, token: str):
     image=image,
     secrets=[modal.Secret.from_dotenv()],
 )
-@modal.web_endpoint(method="POST")
+@modal.fastapi_endpoint(method="GET")
 async def start():
     from pipecat.transports.services.helpers.daily_rest import (
         DailyRESTHelper,
@@ -77,4 +80,4 @@ async def start():
 
         # Return room URL to the user to join
         # Note: in production, you would want to return a token to the user
-        return JSONResponse(content={"room_url": room.url, token: token})
+        return RedirectResponse(room.url)

examples/deployment/modal-example/requirements.txt

@@ -1,5 +1,4 @@
 python-dotenv==1.0.1
 modal==0.71.3
-pipecat-ai[daily,silero,cartesia,openai]==0.0.52
 fastapi==0.115.6
 aiohttp==3.11.11

examples/deployment/pipecat-cloud-daily-pstn-server/fastapi-webhook-server/server.py

@@ -141,6 +141,7 @@ async def dial(request: RoomRequest, raw_request: Request):
             "display_name": request.From,
             "sip_mode": "dial-in",
             "num_endpoints": 2 if request.call_transfer is not None else 1,
+            "codecs": {"audio": ["OPUS"]},
         }
         daily_room_properties["sip"] = sip_config
 

examples/deployment/pipecat-cloud-daily-pstn-server/nextjs-webhook-server/pages/api/dial.js

@@ -103,6 +103,7 @@ export default async function handler(req, res) {
         display_name: From,
         sip_mode: 'dial-in',
         num_endpoints: call_transfer !== null ? 2 : 1,
+        codecs: {"audio": ["OPUS"]},
       };
       daily_room_properties.sip = sip_config;
     }
@@ -172,4 +173,4 @@ export const config = {
       sizeLimit: '1mb',
     },
   },
-};
+};

examples/foundational/01-say-one-thing.py

@@ -42,7 +42,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await task.queue_frames([TTSSpeakFrame(f"<spell>Hello there!</spell>"), EndFrame()])
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=False)
 

examples/foundational/07g-interruptible-openai.py

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

examples/foundational/38-smart-turn.py

@@ -0,0 +1,111 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.turn.smart_turn import SmartTurnAnalyzer
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+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)
+
+
+async def run_bot(webrtc_connection: SmallWebRTCConnection):
+    logger.info(f"Starting bot")
+
+    remote_smart_turn_url = os.getenv("REMOTE_SMART_TURN_URL")
+
+    transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+            vad_audio_passthrough=True,
+            turn_analyzer=SmartTurnAnalyzer(url=remote_smart_turn_url),
+        ),
+    )
+
+    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
+    )
+
+    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)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            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()

examples/foundational/38a-local-smart-turn.py

@@ -0,0 +1,129 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.turn.base_smart_turn import SmartTurnParams
+from pipecat.audio.turn.local_smart_turn import LocalCoreMLSmartTurnAnalyzer
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+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)
+
+
+async def run_bot(webrtc_connection: SmallWebRTCConnection):
+    logger.info(f"Starting bot")
+
+    # To use this locally, set the environment variable LOCAL_SMART_TURN_MODEL_PATH
+    # to the path where the smart-turn repo is cloned.
+    #
+    # Example setup:
+    #
+    #   # Git LFS (Large File Storage)
+    #   brew install git-lfs
+    #   # Hugging Face uses LFS to store large model files, including .mlpackage
+    #   git lfs install
+    #   # Clone the repo with the smart_turn_classifier.mlpackage
+    #   git clone https://huggingface.co/pipecat-ai/smart-turn
+    #
+    # Then set the env variable:
+    #   export LOCAL_SMART_TURN_MODEL_PATH=./smart-turn
+    # or add it to your .env file
+    smart_turn_model_path = os.getenv("LOCAL_SMART_TURN_MODEL_PATH")
+
+    transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+            vad_audio_passthrough=True,
+            turn_analyzer=LocalCoreMLSmartTurnAnalyzer(
+                smart_turn_model_path=smart_turn_model_path, params=SmartTurnParams()
+            ),
+        ),
+    )
+
+    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
+    )
+
+    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)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            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()

examples/p2p-webrtc/daily-interop-bridge/README.md

@@ -0,0 +1,61 @@
+# SmallWebRTC and Daily
+
+A Pipecat example demonstrating how to interoperate audio and video between `SmallWebRTCTransport` and `DailyTransport`.
+
+## 🚀 Quick Start
+
+### 1️⃣ Start the Bot Server
+
+#### 🔧 Set Up the Environment
+1. Create and activate a virtual environment:
+   ```bash
+   python3 -m venv venv
+   source venv/bin/activate  # On Windows: venv\Scripts\activate
+   ```
+
+2. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Configure environment variables:
+   - Copy `env.example` to `.env`
+   ```bash
+   cp env.example .env
+   ```
+   - Add your API keys
+
+#### ▶️ Run the Server
+```bash
+python server.py
+```
+
+###  1️⃣ Connect the first client using Daily Prebuilt
+
+- Open your browser and navigate to the same URL that you configured inside your `.env` file:
+  - `DAILY_SAMPLE_ROOM_URL`
+
+### 2️⃣ Connect the second client using SmallWebRTC Prebuilt UI
+
+- Open your browser and navigate to:
+👉 http://localhost:7860
+  - (Or use your custom port, if configured)
+
+## ⚠️ Important Note
+Ensure the bot server is running before using any client implementations.
+
+## 📌 Requirements
+
+- Python **3.10+**
+- Node.js **16+** (for JavaScript components)
+- Google API Key
+- Modern web browser with WebRTC support
+
+---
+
+### 💡 Notes
+- Ensure all dependencies are installed before running the server.
+- Check the `.env` file for missing configurations.
+- WebRTC requires a secure environment (HTTPS) for full functionality in production.
+
+Happy coding! 🎉

examples/p2p-webrtc/daily-interop-bridge/bot.py

@@ -0,0 +1,128 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import (
+    InputAudioRawFrame,
+    InputImageRawFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
+)
+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.frame_processor import Frame, FrameDirection, FrameProcessor
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+class MirrorProcessor(FrameProcessor):
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, InputAudioRawFrame):
+            await self.push_frame(
+                OutputAudioRawFrame(
+                    audio=frame.audio,
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels,
+                )
+            )
+        elif isinstance(frame, InputImageRawFrame):
+            await self.push_frame(
+                OutputImageRawFrame(image=frame.image, size=frame.size, format=frame.format)
+            )
+        else:
+            await self.push_frame(frame, direction)
+
+
+async def run_bot(webrtc_connection):
+    pipecat_transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            camera_in_enabled=True,
+            camera_out_enabled=True,
+            camera_out_is_live=True,
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            camera_out_width=1280,
+            camera_out_height=720,
+            vad_enabled=False,
+        ),
+    )
+
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", "")
+    daily_transport = DailyTransport(
+        room_url,
+        None,
+        "SmallWebRTC",
+        params=DailyParams(
+            camera_in_enabled=True,
+            camera_out_enabled=True,
+            camera_out_is_live=True,
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            camera_out_width=1280,
+            camera_out_height=720,
+            vad_enabled=False,
+        ),
+    )
+
+    pipeline = Pipeline(
+        [
+            ParallelPipeline(
+                [
+                    daily_transport.input(),
+                    MirrorProcessor(),
+                    pipecat_transport.output(),
+                ],
+                [
+                    pipecat_transport.input(),
+                    MirrorProcessor(),
+                    daily_transport.output(),
+                ],
+            )
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=False,
+        ),
+    )
+
+    @daily_transport.event_handler("on_participant_joined")
+    async def on_participant_joined(transport, participant):
+        await transport.capture_participant_video(participant["id"])
+
+    @pipecat_transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info("Pipecat Client connected")
+
+    @pipecat_transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info("Pipecat Client disconnected")
+
+    @pipecat_transport.event_handler("on_client_closed")
+    async def on_client_closed(transport, client):
+        logger.info("Pipecat Client closed")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=False)
+
+    await runner.run(task)

examples/p2p-webrtc/daily-interop-bridge/env.example

@@ -0,0 +1,2 @@
+DAILY_API_KEY=
+DAILY_SAMPLE_ROOM_URL=

examples/p2p-webrtc/daily-interop-bridge/requirements.txt

@@ -0,0 +1,5 @@
+python-dotenv
+fastapi[all]
+uvicorn
+aiortc
+pipecat-ai[silero, webrtc, daily]

examples/p2p-webrtc/daily-interop-bridge/server.py

@@ -0,0 +1,89 @@
+import argparse
+import asyncio
+import logging
+from contextlib import asynccontextmanager
+from typing import Dict
+
+import uvicorn
+from bot import run_bot
+from dotenv import load_dotenv
+from fastapi import BackgroundTasks, FastAPI
+from fastapi.responses import RedirectResponse
+from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
+
+from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
+
+# Load environment variables
+load_dotenv(override=True)
+
+logger = logging.getLogger("pc")
+
+app = FastAPI()
+
+# Store connections by pc_id
+pcs_map: Dict[str, SmallWebRTCConnection] = {}
+
+ice_servers = ["stun:stun.l.google.com:19302"]
+
+# Mount the frontend at /
+app.mount("/prebuilt", SmallWebRTCPrebuiltUI)
+
+
+@app.get("/", include_in_schema=False)
+async def root_redirect():
+    return RedirectResponse(url="/prebuilt/")
+
+
+@app.post("/api/offer")
+async def offer(request: dict, background_tasks: BackgroundTasks):
+    pc_id = request.get("pc_id")
+
+    if pc_id and pc_id in pcs_map:
+        pipecat_connection = pcs_map[pc_id]
+        logger.info(f"Reusing existing connection for pc_id: {pc_id}")
+        await pipecat_connection.renegotiate(
+            sdp=request["sdp"], type=request["type"], restart_pc=request.get("restart_pc", False)
+        )
+    else:
+        pipecat_connection = SmallWebRTCConnection(ice_servers)
+        await pipecat_connection.initialize(sdp=request["sdp"], type=request["type"])
+
+        @pipecat_connection.event_handler("closed")
+        async def handle_disconnected(webrtc_connection: SmallWebRTCConnection):
+            logger.info(f"Discarding peer connection for pc_id: {webrtc_connection.pc_id}")
+            pcs_map.pop(webrtc_connection.pc_id, None)
+
+        background_tasks.add_task(run_bot, pipecat_connection)
+
+    answer = pipecat_connection.get_answer()
+    # Updating the peer connection inside the map
+    pcs_map[answer["pc_id"]] = pipecat_connection
+
+    return answer
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    yield  # Run app
+    coros = [pc.close() for pc in pcs_map.values()]
+    await asyncio.gather(*coros)
+    pcs_map.clear()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="WebRTC demo")
+    parser.add_argument(
+        "--host", default="localhost", help="Host for HTTP server (default: localhost)"
+    )
+    parser.add_argument(
+        "--port", type=int, default=7860, help="Port for HTTP server (default: 7860)"
+    )
+    parser.add_argument("--verbose", "-v", action="count")
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.basicConfig(level=logging.DEBUG)
+    else:
+        logging.basicConfig(level=logging.INFO)
+
+    uvicorn.run(app, host=args.host, port=args.port)

pyproject.toml

@@ -6,14 +6,14 @@ build-backend = "setuptools.build_meta"
 name = "pipecat-ai"
 dynamic = ["version"]
 description = "An open source framework for voice (and multimodal) assistants"
-license = { text = "BSD 2-Clause License" }
+license = "BSD-2-Clause"
+license-files = ["LICENSE"]
 readme = "README.md"
 requires-python = ">=3.10"
 keywords = ["webrtc", "audio", "video", "ai"]
 classifiers = [
     "Development Status :: 5 - Production/Stable",
     "Intended Audience :: Developers",
-    "License :: OSI Approved :: BSD License",
     "Topic :: Communications :: Conferencing",
     "Topic :: Multimedia :: Sound/Audio",
     "Topic :: Multimedia :: Video",
@@ -79,6 +79,8 @@ qwen = []
 rime = [ "websockets~=13.1" ]
 riva = [ "nvidia-riva-client~=2.19.0" ]
 sentry = [ "sentry-sdk~=2.23.1" ]
+local-smart-turn = [ "coremltools>=8.0", "transformers", "torch==2.5.0", "torchaudio==2.5.0" ]
+remote-smart-turn = []
 silero = [ "onnxruntime~=1.20.1" ]
 simli = [ "simli-ai~=0.1.10"]
 soundfile = [ "soundfile~=0.13.0" ]
@@ -90,9 +92,11 @@ websocket = [ "websockets~=13.1", "fastapi~=0.115.6" ]
 whisper = [ "faster-whisper~=1.1.1" ]
 
 [tool.setuptools.packages.find]
-# All the following settings are optional:
 where = ["src"]
 
+[tool.setuptools.package-data]
+"pipecat" = ["py.typed"]
+
 [tool.pytest.ini_options]
 addopts = "--verbose"
 testpaths = ["tests"]

src/pipecat/audio/turn/base_smart_turn.py

@@ -0,0 +1,176 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import time
+from abc import abstractmethod
+from typing import Any, Dict, Optional, Tuple
+
+import numpy as np
+from loguru import logger
+from pydantic import BaseModel
+
+from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer, EndOfTurnState
+from pipecat.metrics.metrics import MetricsData, SmartTurnMetricsData
+
+# Default timing parameters
+STOP_SECS = 3
+PRE_SPEECH_MS = 0
+MAX_DURATION_SECONDS = 8  # Max allowed segment duration
+USE_ONLY_LAST_VAD_SEGMENT = True
+
+
+class SmartTurnParams(BaseModel):
+    stop_secs: float = STOP_SECS
+    pre_speech_ms: float = PRE_SPEECH_MS
+    max_duration_secs: float = MAX_DURATION_SECONDS
+    # not exposing this for now yet until the model can handle it.
+    # use_only_last_vad_segment: bool = USE_ONLY_LAST_VAD_SEGMENT
+
+
+class BaseSmartTurn(BaseTurnAnalyzer):
+    def __init__(
+        self, *, sample_rate: Optional[int] = None, params: SmartTurnParams = SmartTurnParams()
+    ):
+        super().__init__(sample_rate=sample_rate)
+        self._params = params
+        # Configuration
+        self._stop_ms = self._params.stop_secs * 1000  # silence threshold in ms
+        # Inference state
+        self._audio_buffer = []
+        self._speech_triggered = False
+        self._silence_ms = 0
+        self._speech_start_time = None
+
+    @property
+    def speech_triggered(self) -> bool:
+        return self._speech_triggered
+
+    def append_audio(self, buffer: bytes, is_speech: bool) -> EndOfTurnState:
+        # Convert raw audio to float32 format and append to the buffer
+        audio_int16 = np.frombuffer(buffer, dtype=np.int16)
+        audio_float32 = np.frombuffer(audio_int16, dtype=np.int16).astype(np.float32) / 32768.0
+        self._audio_buffer.append((time.time(), audio_float32))
+
+        state = EndOfTurnState.INCOMPLETE
+
+        if is_speech:
+            # Reset silence tracking on speech
+            self._silence_ms = 0
+            self._speech_triggered = True
+            if self._speech_start_time is None:
+                self._speech_start_time = time.time()
+        else:
+            if self._speech_triggered:
+                chunk_duration_ms = len(audio_int16) / (self._sample_rate / 1000)
+                self._silence_ms += chunk_duration_ms
+                # If silence exceeds threshold, mark end of turn
+                if self._silence_ms >= self._stop_ms:
+                    logger.debug(
+                        f"End of Turn complete due to stop_secs. Silence in ms: {self._silence_ms}"
+                    )
+                    state = EndOfTurnState.COMPLETE
+                    self._clear(state)
+            else:
+                # Trim buffer to prevent unbounded growth before speech
+                max_buffer_time = (
+                    (self._params.pre_speech_ms / 1000)
+                    + self._params.stop_secs
+                    + self._params.max_duration_secs
+                )
+                while (
+                    self._audio_buffer and self._audio_buffer[0][0] < time.time() - max_buffer_time
+                ):
+                    self._audio_buffer.pop(0)
+
+        return state
+
+    def analyze_end_of_turn(self) -> Tuple[EndOfTurnState, Optional[MetricsData]]:
+        state, result = self._process_speech_segment(self._audio_buffer)
+        if state == EndOfTurnState.COMPLETE or USE_ONLY_LAST_VAD_SEGMENT:
+            self._clear(state)
+        logger.debug(f"End of Turn result: {state}")
+        return state, result
+
+    def _clear(self, turn_state: EndOfTurnState):
+        # If the state is still incomplete, keep the _speech_triggered as True
+        self._speech_triggered = turn_state == EndOfTurnState.INCOMPLETE
+        self._audio_buffer = []
+        self._speech_start_time = None
+        self._silence_ms = 0
+
+    def _process_speech_segment(self, audio_buffer) -> Tuple[EndOfTurnState, Optional[MetricsData]]:
+        state = EndOfTurnState.INCOMPLETE
+
+        if not audio_buffer:
+            return state, None
+
+        # Extract recent audio segment for prediction
+        start_time = self._speech_start_time - (self._params.pre_speech_ms / 1000)
+        start_index = 0
+        for i, (t, _) in enumerate(audio_buffer):
+            if t >= start_time:
+                start_index = i
+                break
+
+        end_index = len(audio_buffer) - 1
+
+        # Extract the audio segment
+        segment_audio_chunks = [chunk for _, chunk in audio_buffer[start_index : end_index + 1]]
+        segment_audio = np.concatenate(segment_audio_chunks)
+
+        # Limit maximum duration
+        max_samples = int(self._params.max_duration_secs * self.sample_rate)
+        if len(segment_audio) > max_samples:
+            # slices the array to keep the last max_samples samples, discarding the earlier part.
+            segment_audio = segment_audio[-max_samples:]
+
+        result_data = None
+
+        if len(segment_audio) > 0:
+            start_time = time.perf_counter()
+            result = self._predict_endpoint(segment_audio)
+            state = (
+                EndOfTurnState.COMPLETE if result["prediction"] == 1 else EndOfTurnState.INCOMPLETE
+            )
+            end_time = time.perf_counter()
+
+            # Calculate processing time
+            e2e_processing_time_ms = (end_time - start_time) * 1000
+
+            # Prepare the result data
+            result_data = SmartTurnMetricsData(
+                processor="BaseSmartTurn",
+                is_complete=result["prediction"] == 1,
+                probability=result["probability"],
+                inference_time_ms=result.get("inference_time", 0) * 1000,
+                server_total_time_ms=result.get("total_time", 0) * 1000,
+                e2e_processing_time_ms=e2e_processing_time_ms,
+            )
+
+            logger.trace(f"Prediction: {'Complete' if result_data.is_complete else 'Incomplete'}")
+            logger.trace(f"Probability of complete: {result_data.probability:.4f}")
+            logger.trace(f"Inference time: {result_data.inference_time_ms:.2f}ms")
+            logger.trace(f"Server total time: {result_data.server_total_time_ms:.2f}ms")
+            logger.trace(f"E2E processing time: {result_data.e2e_processing_time_ms:.2f}ms")
+        else:
+            logger.trace(f"params: {self._params}, stop_ms: {self._stop_ms}")
+            logger.trace("Captured empty audio segment, skipping prediction.")
+
+        return state, result_data
+
+    @abstractmethod
+    def _predict_endpoint(self, buffer: np.ndarray) -> Dict[str, Any]:
+        """Abstract method to predict if a turn has ended based on audio.
+
+        Args:
+            buffer: Float32 numpy array of audio samples at 16kHz.
+
+        Returns:
+            Dictionary with:
+              - prediction: 1 if turn is complete, else 0
+              - probability: Confidence of the prediction
+        """
+        pass

src/pipecat/audio/turn/base_turn_analyzer.py

@@ -0,0 +1,80 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+from abc import ABC, abstractmethod
+from enum import Enum
+from typing import Optional, Tuple
+
+from pipecat.metrics.metrics import MetricsData
+
+
+class EndOfTurnState(Enum):
+    COMPLETE = 1
+    INCOMPLETE = 2
+
+
+class BaseTurnAnalyzer(ABC):
+    """Abstract base class for analyzing user end of turn.
+
+    This class inherits from BaseObject to leverage its event handling system
+    while still defining an abstract interface through abstract methods.
+    """
+
+    def __init__(self, *, sample_rate: Optional[int] = None):
+        self._init_sample_rate = sample_rate
+        self._sample_rate = 0
+
+    @property
+    def sample_rate(self) -> int:
+        """Returns the current sample rate.
+
+        Returns:
+            int: The effective sample rate for audio processing.
+        """
+        return self._sample_rate
+
+    def set_sample_rate(self, sample_rate: int):
+        """Sets the sample rate for audio processing.
+
+        If the initial sample rate was provided, it will use that; otherwise, it sets to
+        the provided sample rate.
+
+        Args:
+            sample_rate (int): The sample rate to set.
+        """
+        self._sample_rate = self._init_sample_rate or sample_rate
+
+    @property
+    @abstractmethod
+    def speech_triggered(self) -> bool:
+        """Determines if speech has been detected.
+
+        Returns:
+            bool: True if speech is triggered, otherwise False.
+        """
+        pass
+
+    @abstractmethod
+    def append_audio(self, buffer: bytes, is_speech: bool) -> EndOfTurnState:
+        """Appends audio data for analysis.
+
+        Args:
+            buffer (bytes): The audio data to append.
+            is_speech (bool): Indicates whether the appended audio is speech or not.
+
+        Returns:
+            EndOfTurnState: The resulting state after appending the audio.
+        """
+        pass
+
+    @abstractmethod
+    def analyze_end_of_turn(self) -> Tuple[EndOfTurnState, Optional[MetricsData]]:
+        """Analyzes if an end of turn has occurred based on the audio input.
+
+        Returns:
+            EndOfTurnState: The result of the end of turn analysis.
+        """
+        pass

src/pipecat/audio/turn/local_smart_turn.py

@@ -0,0 +1,65 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+import os
+from typing import Dict
+
+import numpy as np
+import torch
+from loguru import logger
+
+from pipecat.audio.turn.base_smart_turn import BaseSmartTurn
+
+try:
+    import coremltools as ct
+    from transformers import AutoFeatureExtractor
+except ModuleNotFoundError as e:
+    logger.error(f"Exception: {e}")
+    logger.error(
+        "In order to use the LocalSmartTurnAnalyzer, you need to `pip install pipecat-ai[local-smart-turn]`."
+    )
+    raise Exception(f"Missing module: {e}")
+
+
+class LocalCoreMLSmartTurnAnalyzer(BaseSmartTurn):
+    def __init__(self, smart_turn_model_path: str, **kwargs):
+        super().__init__(**kwargs)
+
+        if not smart_turn_model_path:
+            logger.error("smart_turn_model_path is not set.")
+            raise Exception("smart_turn_model_path must be provided.")
+
+        core_ml_model_path = f"{smart_turn_model_path}/coreml/smart_turn_classifier.mlpackage"
+
+        logger.debug("Loading Local Smart Turn model...")
+        # Only load the processor, not the torch model
+        self._turn_processor = AutoFeatureExtractor.from_pretrained(smart_turn_model_path)
+        self._turn_model = ct.models.MLModel(core_ml_model_path)
+        logger.debug("Loaded Local Smart Turn")
+
+    def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, any]:
+        inputs = self._turn_processor(
+            audio_array,
+            sampling_rate=16000,
+            padding="max_length",
+            truncation=True,
+            max_length=800,  # Maximum length as specified in training
+            return_attention_mask=True,
+            return_tensors="pt",
+        )
+
+        output = self._turn_model.predict(dict(inputs))
+        logits = output["logits"]  # Core ML returns numpy array
+        logits_tensor = torch.tensor(logits)
+        probabilities = torch.nn.functional.softmax(logits_tensor, dim=1)
+        completion_prob = probabilities[0, 1].item()  # Probability of class 1 (Complete)
+        prediction = 1 if completion_prob > 0.5 else 0
+
+        return {
+            "prediction": prediction,
+            "probability": completion_prob,
+        }

src/pipecat/audio/turn/smart_turn.py

@@ -0,0 +1,75 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+import io
+import os
+from typing import Dict
+
+import numpy as np
+import requests
+from loguru import logger
+
+from pipecat.audio.turn.base_smart_turn import BaseSmartTurn
+
+
+class SmartTurnAnalyzer(BaseSmartTurn):
+    def __init__(self, url: str, **kwargs):
+        super().__init__(**kwargs)
+        self.remote_smart_turn_url = url
+
+        if not self.remote_smart_turn_url:
+            logger.error("remote_smart_turn_url is not set.")
+            raise Exception("remote_smart_turn_url must be provided.")
+
+        # Use a session to reuse connections (keep-alive)
+        self.session = requests.Session()
+        self.session.headers.update({"Connection": "keep-alive"})
+
+    def _serialize_array(self, audio_array: np.ndarray) -> bytes:
+        logger.trace("Serializing NumPy array to bytes...")
+        buffer = io.BytesIO()
+        np.save(buffer, audio_array)
+        serialized_bytes = buffer.getvalue()
+        logger.trace(f"Serialized size: {len(serialized_bytes)} bytes")
+        return serialized_bytes
+
+    def _send_raw_request(self, data_bytes: bytes):
+        headers = {"Content-Type": "application/octet-stream"}
+        logger.trace(
+            f"Sending {len(data_bytes)} bytes as raw body to {self.remote_smart_turn_url}..."
+        )
+        try:
+            response = self.session.post(
+                self.remote_smart_turn_url,
+                data=data_bytes,
+                headers=headers,
+                timeout=60,
+            )
+
+            logger.trace("\n--- Response ---")
+            logger.trace(f"Status Code: {response.status_code}")
+
+            if response.ok:
+                try:
+                    logger.trace("Response JSON:")
+                    logger.trace(response.json())
+                    return response.json()
+                except requests.exceptions.JSONDecodeError:
+                    logger.trace("Response Content (non-JSON):")
+                    logger.trace(response.text)
+            else:
+                logger.trace("Response Content (Error):")
+                logger.trace(response.text)
+                response.raise_for_status()
+
+        except requests.exceptions.RequestException as e:
+            logger.error(f"Failed to send raw request to Daily Smart Turn: {e}")
+            raise Exception("Failed to send raw request to Daily Smart Turn.")
+
+    def _predict_endpoint(self, audio_array: np.ndarray) -> Dict[str, any]:
+        serialized_array = self._serialize_array(audio_array)
+        return self._send_raw_request(serialized_array)

src/pipecat/metrics/metrics.py

@@ -30,3 +30,13 @@ class LLMUsageMetricsData(MetricsData):
 
 class TTSUsageMetricsData(MetricsData):
     value: int
+
+
+class SmartTurnMetricsData(MetricsData):
+    """Metrics data for smart turn predictions."""
+
+    is_complete: bool
+    probability: float
+    inference_time_ms: float
+    server_total_time_ms: float
+    e2e_processing_time_ms: float

src/pipecat/services/cartesia/tts.py

@@ -185,7 +185,8 @@ class CartesiaTTSService(AudioContextWordTTSService):
 
     async def _connect(self):
         await self._connect_websocket()
-        if not self._receive_task:
+
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
     async def _disconnect(self):
@@ -197,7 +198,7 @@ class CartesiaTTSService(AudioContextWordTTSService):
 
     async def _connect_websocket(self):
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
             logger.debug("Connecting to Cartesia")
             self._websocket = await websockets.connect(
@@ -215,11 +216,11 @@ class CartesiaTTSService(AudioContextWordTTSService):
             if self._websocket:
                 logger.debug("Disconnecting from Cartesia")
                 await self._websocket.close()
-                self._websocket = None
-
-            self._context_id = None
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._context_id = None
+            self._websocket = None
 
     def _get_websocket(self):
         if self._websocket:
@@ -279,7 +280,7 @@ class CartesiaTTSService(AudioContextWordTTSService):
         logger.debug(f"{self}: Generating TTS [{text}]")
 
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 await self._connect()
 
             if not self._context_id:

src/pipecat/services/elevenlabs/tts.py

@@ -309,10 +309,10 @@ class ElevenLabsTTSService(InterruptibleWordTTSService):
     async def _connect(self):
         await self._connect_websocket()
 
-        if not self._receive_task:
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
-        if not self._keepalive_task:
+        if self._websocket and not self._keepalive_task:
             self._keepalive_task = self.create_task(self._keepalive_task_handler())
 
     async def _disconnect(self):
@@ -328,7 +328,7 @@ class ElevenLabsTTSService(InterruptibleWordTTSService):
 
     async def _connect_websocket(self):
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
 
             logger.debug("Connecting to ElevenLabs")
@@ -375,11 +375,11 @@ class ElevenLabsTTSService(InterruptibleWordTTSService):
                 logger.debug("Disconnecting from ElevenLabs")
                 await self._websocket.send(json.dumps({"text": ""}))
                 await self._websocket.close()
-                self._websocket = None
-
-            self._started = False
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._started = False
+            self._websocket = None
 
     def _get_websocket(self):
         if self._websocket:
@@ -419,7 +419,7 @@ class ElevenLabsTTSService(InterruptibleWordTTSService):
         logger.debug(f"{self}: Generating TTS [{text}]")
 
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 await self._connect()
 
             try:

src/pipecat/services/fish/tts.py

@@ -104,7 +104,8 @@ class FishAudioTTSService(InterruptibleTTSService):
 
     async def _connect(self):
         await self._connect_websocket()
-        if not self._receive_task:
+
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
     async def _disconnect(self):
@@ -116,7 +117,7 @@ class FishAudioTTSService(InterruptibleTTSService):
 
     async def _connect_websocket(self):
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
 
             logger.debug("Connecting to Fish Audio")
@@ -141,16 +142,17 @@ class FishAudioTTSService(InterruptibleTTSService):
                 stop_message = {"event": "stop"}
                 await self._websocket.send(ormsgpack.packb(stop_message))
                 await self._websocket.close()
-                self._websocket = None
-            self._request_id = None
-            self._started = False
         except Exception as e:
             logger.error(f"Error closing websocket: {e}")
+        finally:
+            self._request_id = None
+            self._started = False
+            self._websocket = None
 
     async def flush_audio(self):
         """Flush any buffered audio by sending a flush event to Fish Audio."""
         logger.trace(f"{self}: Flushing audio buffers")
-        if not self._websocket:
+        if not self._websocket or self._websocket.closed:
             return
         flush_message = {"event": "flush"}
         await self._get_websocket().send(ormsgpack.packb(flush_message))

src/pipecat/services/gladia/stt.py

@@ -285,7 +285,7 @@ class GladiaSTTService(STTService):
         settings = self._prepare_settings()
         response = await self._setup_gladia(settings)
         self._websocket = await websockets.connect(response["url"])
-        if not self._receive_task:
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler())
 
     async def stop(self, frame: EndFrame):

src/pipecat/services/google/llm_vertex.py

@@ -17,6 +17,8 @@ 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
 
@@ -100,6 +102,13 @@ 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.")

src/pipecat/services/google/stt.py

@@ -32,6 +32,8 @@ 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
@@ -451,6 +453,7 @@ 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")
@@ -461,7 +464,16 @@ class GoogleSTTService(STTService):
                 self._project_id = json_account_info.get("project_id")
             creds = service_account.Credentials.from_service_account_file(credentials_path)
         else:
-            raise ValueError("Either credentials or credentials_path must be provided")
+            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.")
 
         if not self._project_id:
             raise ValueError("Project ID not found in credentials")

src/pipecat/services/google/tts.py

@@ -27,6 +27,8 @@ 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
 
@@ -251,6 +253,16 @@ 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)
 

src/pipecat/services/lmnt/tts.py

@@ -109,7 +109,7 @@ class LmntTTSService(InterruptibleTTSService):
     async def _connect(self):
         await self._connect_websocket()
 
-        if not self._receive_task:
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
     async def _disconnect(self):
@@ -122,7 +122,7 @@ class LmntTTSService(InterruptibleTTSService):
     async def _connect_websocket(self):
         """Connect to LMNT websocket."""
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
 
             logger.debug("Connecting to LMNT")
@@ -158,11 +158,11 @@ class LmntTTSService(InterruptibleTTSService):
                 # errors on the websocket, so we just skip it for now.
                 # await self._websocket.send(json.dumps({"eof": True}))
                 await self._websocket.close()
-                self._websocket = None
-
-            self._started = False
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._started = False
+            self._websocket = None
 
     def _get_websocket(self):
         if self._websocket:
@@ -170,7 +170,7 @@ class LmntTTSService(InterruptibleTTSService):
         raise Exception("Websocket not connected")
 
     async def flush_audio(self):
-        if not self._websocket:
+        if not self._websocket or self._websocket.closed:
             return
         await self._get_websocket().send(json.dumps({"flush": True}))
 
@@ -203,7 +203,7 @@ class LmntTTSService(InterruptibleTTSService):
         logger.debug(f"{self}: Generating TTS [{text}]")
 
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 await self._connect()
 
             try:

src/pipecat/services/neuphonic/tts.py

@@ -106,6 +106,9 @@ class NeuphonicTTSService(InterruptibleTTSService):
         self._started = False
         self._cumulative_time = 0
 
+        self._receive_task = None
+        self._keepalive_task = None
+
     def can_generate_metrics(self) -> bool:
         return True
 
@@ -159,8 +162,11 @@ class NeuphonicTTSService(InterruptibleTTSService):
     async def _connect(self):
         await self._connect_websocket()
 
-        self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
-        self._keepalive_task = self.create_task(self._keepalive_task_handler())
+        if self._websocket and not self._receive_task:
+            self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
+
+        if self._websocket and not self._keepalive_task:
+            self._keepalive_task = self.create_task(self._keepalive_task_handler())
 
     async def _disconnect(self):
         if self._receive_task:
@@ -175,6 +181,9 @@ class NeuphonicTTSService(InterruptibleTTSService):
 
     async def _connect_websocket(self):
         try:
+            if self._websocket and self._websocket.open:
+                return
+
             logger.debug("Connecting to Neuphonic")
 
             tts_config = {
@@ -190,7 +199,6 @@ class NeuphonicTTSService(InterruptibleTTSService):
             url = f"{self._url}/speak/{self._settings['lang_code']}?{'&'.join(query_params)}"
 
             self._websocket = await websockets.connect(url)
-
         except Exception as e:
             logger.error(f"{self} initialization error: {e}")
             self._websocket = None
@@ -203,11 +211,11 @@ class NeuphonicTTSService(InterruptibleTTSService):
             if self._websocket:
                 logger.debug("Disconnecting from Neuphonic")
                 await self._websocket.close()
-                self._websocket = None
-
-            self._started = False
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._started = False
+            self._websocket = None
 
     async def _receive_messages(self):
         async for message in self._websocket:
@@ -235,7 +243,7 @@ class NeuphonicTTSService(InterruptibleTTSService):
         logger.debug(f"Generating TTS: [{text}]")
 
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 await self._connect()
 
             try:

src/pipecat/services/openai/tts.py

@@ -70,7 +70,7 @@ class OpenAITTSService(TTSService):
         if sample_rate and sample_rate != self.OPENAI_SAMPLE_RATE:
             logger.warning(
                 f"OpenAI TTS only supports {self.OPENAI_SAMPLE_RATE}Hz sample rate. "
-                f"Current rate of {self.sample_rate}Hz may cause issues."
+                f"Current rate of {sample_rate}Hz may cause issues."
             )
         super().__init__(sample_rate=sample_rate, **kwargs)
 

src/pipecat/services/playht/tts.py

@@ -157,7 +157,7 @@ class PlayHTTTSService(InterruptibleTTSService):
     async def _connect(self):
         await self._connect_websocket()
 
-        if not self._receive_task:
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
     async def _disconnect(self):
@@ -169,7 +169,7 @@ class PlayHTTTSService(InterruptibleTTSService):
 
     async def _connect_websocket(self):
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
 
             logger.debug("Connecting to PlayHT")
@@ -197,11 +197,11 @@ class PlayHTTTSService(InterruptibleTTSService):
             if self._websocket:
                 logger.debug("Disconnecting from PlayHT")
                 await self._websocket.close()
-                self._websocket = None
-
-            self._request_id = None
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._request_id = None
+            self._websocket = None
 
     async def _get_websocket_url(self):
         async with aiohttp.ClientSession() as session:

src/pipecat/services/rime/tts.py

@@ -168,7 +168,7 @@ class RimeTTSService(AudioContextWordTTSService):
         """Establish websocket connection and start receive task."""
         await self._connect_websocket()
 
-        if not self._receive_task:
+        if self._websocket and not self._receive_task:
             self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
 
     async def _disconnect(self):
@@ -182,7 +182,7 @@ class RimeTTSService(AudioContextWordTTSService):
     async def _connect_websocket(self):
         """Connect to Rime websocket API with configured settings."""
         try:
-            if self._websocket:
+            if self._websocket and self._websocket.open:
                 return
 
             params = "&".join(f"{k}={v}" for k, v in self._settings.items())
@@ -201,10 +201,11 @@ class RimeTTSService(AudioContextWordTTSService):
             if self._websocket:
                 await self._websocket.send(json.dumps(self._build_eos_msg()))
                 await self._websocket.close()
-                self._websocket = None
-            self._context_id = None
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
+        finally:
+            self._context_id = None
+            self._websocket = None
 
     def _get_websocket(self):
         """Get active websocket connection or raise exception."""
@@ -316,7 +317,7 @@ class RimeTTSService(AudioContextWordTTSService):
         """
         logger.debug(f"{self}: Generating TTS [{text}]")
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 await self._connect()
 
             try:

src/pipecat/services/websocket_service.py

@@ -31,7 +31,7 @@ class WebsocketService(ABC):
             bool: True if connection is verified working, False otherwise
         """
         try:
-            if not self._websocket:
+            if not self._websocket or self._websocket.closed:
                 return False
             await self._websocket.ping()
             return True

src/pipecat/transports/base_input.py

@@ -6,10 +6,14 @@
 
 import asyncio
 from concurrent.futures import ThreadPoolExecutor
-from typing import Optional
+from typing import Mapping, Optional
 
 from loguru import logger
 
+from pipecat.audio.turn.base_turn_analyzer import (
+    BaseTurnAnalyzer,
+    EndOfTurnState,
+)
 from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState
 from pipecat.frames.frames import (
     BotInterruptionFrame,
@@ -20,6 +24,7 @@ from pipecat.frames.frames import (
     FilterUpdateSettingsFrame,
     Frame,
     InputAudioRawFrame,
+    MetricsFrame,
     StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
@@ -28,6 +33,7 @@ from pipecat.frames.frames import (
     UserStoppedSpeakingFrame,
     VADParamsUpdateFrame,
 )
+from pipecat.metrics.metrics import MetricsData, SmartTurnMetricsData
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.base_transport import TransportParams
 
@@ -64,12 +70,20 @@ class BaseInputTransport(FrameProcessor):
     def vad_analyzer(self) -> Optional[VADAnalyzer]:
         return self._params.vad_analyzer
 
+    @property
+    def turn_analyzer(self) -> Optional[BaseTurnAnalyzer]:
+        return self._params.turn_analyzer
+
     async def start(self, frame: StartFrame):
         self._sample_rate = self._params.audio_in_sample_rate or frame.audio_in_sample_rate
 
         # Configure VAD analyzer.
         if self._params.vad_enabled and self._params.vad_analyzer:
             self._params.vad_analyzer.set_sample_rate(self._sample_rate)
+        # Configure End of turn analyzer.
+        if self._params.turn_analyzer:
+            self._params.turn_analyzer.set_sample_rate(self._sample_rate)
+
         # Start audio filter.
         if self._params.audio_in_filter:
             await self._params.audio_in_filter.start(self._sample_rate)
@@ -187,10 +201,18 @@ class BaseInputTransport(FrameProcessor):
             and new_vad_state != VADState.STOPPING
         ):
             frame = None
-            if new_vad_state == VADState.SPEAKING:
-                frame = UserStartedSpeakingFrame()
-            elif new_vad_state == VADState.QUIET:
-                frame = UserStoppedSpeakingFrame()
+            # If the turn analyser is enabled, this will prevent:
+            # - Creating the UserStoppedSpeakingFrame
+            # - Creating the UserStartedSpeakingFrame multiple times
+            can_create_user_frames = (
+                self._params.turn_analyzer is None
+                or not self._params.turn_analyzer.speech_triggered
+            )
+            if can_create_user_frames:
+                if new_vad_state == VADState.SPEAKING:
+                    frame = UserStartedSpeakingFrame()
+                elif new_vad_state == VADState.QUIET:
+                    frame = UserStoppedSpeakingFrame()
 
             if frame:
                 await self._handle_user_interruption(frame)
@@ -198,6 +220,32 @@ class BaseInputTransport(FrameProcessor):
             vad_state = new_vad_state
         return vad_state
 
+    async def _handle_end_of_turn(self):
+        if self.turn_analyzer:
+            state, prediction = await self.get_event_loop().run_in_executor(
+                self._executor, self.turn_analyzer.analyze_end_of_turn
+            )
+
+            await self._handle_prediction_result(prediction)
+
+            await self._handle_end_of_turn_complete(state)
+
+    async def _handle_end_of_turn_complete(self, state: EndOfTurnState):
+        if state == EndOfTurnState.COMPLETE:
+            await self._handle_user_interruption(UserStoppedSpeakingFrame())
+
+    async def _run_turn_analyzer(
+        self, frame: InputAudioRawFrame, vad_state: VADState, previous_vad_state: VADState
+    ):
+        is_speech = vad_state == VADState.SPEAKING or vad_state == VADState.STARTING
+        # If silence exceeds threshold, we are going to receive EndOfTurnState.COMPLETE
+        end_of_turn_state = self._params.turn_analyzer.append_audio(frame.audio, is_speech)
+        if end_of_turn_state == EndOfTurnState.COMPLETE:
+            await self._handle_end_of_turn_complete(end_of_turn_state)
+        # Otherwise we are going to trigger to check if the turn is completed based on the VAD
+        elif vad_state == VADState.QUIET and vad_state != previous_vad_state:
+            await self._handle_end_of_turn()
+
     async def _audio_task_handler(self):
         vad_state: VADState = VADState.QUIET
         while True:
@@ -211,12 +259,24 @@ class BaseInputTransport(FrameProcessor):
 
             # Check VAD and push event if necessary. We just care about
             # changes from QUIET to SPEAKING and vice versa.
+            previous_vad_state = vad_state
             if self._params.vad_enabled:
                 vad_state = await self._handle_vad(frame, vad_state)
                 audio_passthrough = self._params.vad_audio_passthrough
 
+            if self._params.turn_analyzer:
+                await self._run_turn_analyzer(frame, vad_state, previous_vad_state)
+
             # Push audio downstream if passthrough.
             if audio_passthrough:
                 await self.push_frame(frame)
 
             self._audio_in_queue.task_done()
+
+    async def _handle_prediction_result(self, result: MetricsData):
+        """Handle a prediction result event from the turn analyzer.
+
+        Args:
+            result: The prediction result MetricsData.
+        """
+        await self.push_frame(MetricsFrame(data=[result]))

src/pipecat/transports/base_output.py

@@ -386,10 +386,13 @@ class BaseOutputTransport(FrameProcessor):
     async def _draw_image(self, frame: OutputImageRawFrame):
         desired_size = (self._params.camera_out_width, self._params.camera_out_height)
 
+        # TODO: we should refactor in the future to support dynamic resolutions
+        # which is kind of what happens in P2P connections.
+        # We need to add support for that inside the DailyTransport
         if frame.size != desired_size:
             image = Image.frombytes(frame.format, frame.size, frame.image)
             resized_image = image.resize(desired_size)
-            logger.warning(f"{frame} does not have the expected size {desired_size}, resizing")
+            # logger.warning(f"{frame} does not have the expected size {desired_size}, resizing")
             frame = OutputImageRawFrame(
                 resized_image.tobytes(), resized_image.size, resized_image.format
             )

src/pipecat/transports/base_transport.py

@@ -11,6 +11,7 @@ from pydantic import BaseModel, ConfigDict
 
 from pipecat.audio.filters.base_audio_filter import BaseAudioFilter
 from pipecat.audio.mixers.base_audio_mixer import BaseAudioMixer
+from pipecat.audio.turn.base_turn_analyzer import BaseTurnAnalyzer
 from pipecat.audio.vad.vad_analyzer import VADAnalyzer
 from pipecat.processors.frame_processor import FrameProcessor
 from pipecat.utils.base_object import BaseObject
@@ -41,6 +42,7 @@ class TransportParams(BaseModel):
     vad_enabled: bool = False
     vad_audio_passthrough: bool = False
     vad_analyzer: Optional[VADAnalyzer] = None
+    turn_analyzer: Optional[BaseTurnAnalyzer] = None
 
 
 class BaseTransport(BaseObject):