Remove log

Update GeminiMultimodalLiveLLMService to use Gemini 2.5 Flash Native …

.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

.gitignore

@@ -7,7 +7,7 @@ venv
 /.idea
 #*#
 
-# Distribution / packaging
+# Distribution / Packaging
 .Python
 build/
 develop-eggs/
@@ -30,24 +30,24 @@ MANIFEST
 .env
 fly.toml
 
-# Example files
-pipecat/examples/twilio-chatbot/templates/streams.xml
-pipecat/examples/bot-ready-signalling/client/react-native/node_modules/
-pipecat/examples/bot-ready-signalling/client/react-native/.expo/
-pipecat/examples/bot-ready-signalling/client/react-native/dist/
-pipecat/examples/bot-ready-signalling/client/react-native/npm-debug.*
-pipecat/examples/bot-ready-signalling/client/react-native/*.jks
-pipecat/examples/bot-ready-signalling/client/react-native/*.p8
-pipecat/examples/bot-ready-signalling/client/react-native/*.p12
-pipecat/examples/bot-ready-signalling/client/react-native/*.key
-pipecat/examples/bot-ready-signalling/client/react-native/*.mobileprovision
-pipecat/examples/bot-ready-signalling/client/react-native/*.orig.*
-pipecat/examples/bot-ready-signalling/client/react-native/web-build/
+# Examples
+examples/telnyx-chatbot/templates/streams.xml
+examples/twilio-chatbot/templates/streams.xml
+examples/**/node_modules/
+examples/**/.expo/
+examples/**/dist/
+examples/**/npm-debug.*
+examples/**/*.jks
+examples/**/*.p8
+examples/**/*.p12
+examples/**/*.key
+examples/**/*.mobileprovision
+examples/**/*.orig.*
+examples/**/web-build/
 
 # macOS
 .DS_Store
 
-
 # Documentation
 docs/api/_build/
 docs/api/api

.pre-commit-config.yaml

@@ -1,7 +1,8 @@
 repos:
-  - repo: local
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.9.7
     hooks:
-      - id: ruff-format-hook
-        name: Check ruff formatting
-        entry: sh scripts/pre-commit.sh
-        language: system
+      - id: ruff
+        language_version: python3
+        args: [ --select,  I, ]
+      - id: ruff-format

CONTRIBUTING.md

@@ -26,11 +26,52 @@ git commit -m "Description of your changes"
 git push origin your-branch-name
 ```
 
-9. **Submit a Pull Request (PR)**: Open a PR from your forked repository to the main branch of this repo. 
-> Important: Describe the changes you've made clearly!
+8. **Submit a Pull Request (PR)**: Open a PR from your forked repository to the main branch of this repo.
+   > Important: Describe the changes you've made clearly!
 
 Our maintainers will review your PR, and once everything is good, your contributions will be merged!
 
+## Code Style and Documentation
+
+### Python Code Style
+
+We use Ruff for code linting and formatting. Please ensure your code passes all linting checks before submitting a PR.
+
+### Docstring Conventions
+
+We follow Google-style docstrings with these specific conventions:
+
+- Class docstrings should fully document all parameters used in `__init__`
+- We don't require separate docstrings for `__init__` methods when parameters are documented in the class docstring
+- Property methods should have docstrings explaining their purpose and return value
+
+Example of correctly documented class:
+
+```python
+class MyClass:
+    """Class description.
+
+    Additional details about the class.
+
+    Args:
+        param1: Description of first parameter.
+        param2: Description of second parameter.
+    """
+
+    def __init__(self, param1, param2):
+        # No docstring required here as parameters are documented above
+        self.param1 = param1
+        self.param2 = param2
+
+    @property
+    def some_property(self) -> str:
+        """Get the formatted property value.
+
+        Returns:
+            A string representation of the property.
+        """
+        return f"Property: {self.param1}"
+```
 
 # Contributor Covenant Code of Conduct
 
@@ -51,23 +92,23 @@ diverse, inclusive, and healthy community.
 Examples of behavior that contributes to a positive environment for our
 community include:
 
-* Demonstrating empathy and kindness toward other people
-* Being respectful of differing opinions, viewpoints, and experiences
-* Giving and gracefully accepting constructive feedback
-* Accepting responsibility and apologizing to those affected by our mistakes,
+- Demonstrating empathy and kindness toward other people
+- Being respectful of differing opinions, viewpoints, and experiences
+- Giving and gracefully accepting constructive feedback
+- Accepting responsibility and apologizing to those affected by our mistakes,
   and learning from the experience
-* Focusing on what is best not just for us as individuals, but for the overall
+- Focusing on what is best not just for us as individuals, but for the overall
   community
 
 Examples of unacceptable behavior include:
 
-* The use of sexualized language or imagery, and sexual attention or advances of
+- The use of sexualized language or imagery, and sexual attention or advances of
   any kind
-* Trolling, insulting or derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or email address,
+- Trolling, insulting or derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information, such as a physical or email address,
   without their explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
+- Other conduct which could reasonably be considered inappropriate in a
   professional setting
 
 ## Enforcement Responsibilities
@@ -162,4 +203,4 @@ For answers to common questions about this code of conduct, see the FAQ at
 [v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
 [Mozilla CoC]: https://github.com/mozilla/diversity
 [FAQ]: https://www.contributor-covenant.org/faq
-[translations]: https://www.contributor-covenant.org/translations
+[translations]: https://www.contributor-covenant.org/translations

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), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [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), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [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), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [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), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
+| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [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 | [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
@@ -53,154 +82,71 @@ 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), [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), [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), [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), [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), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [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), [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]"` |
-| Vision & Image      | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | `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
 
+Install the test dependencies:
+
+```shell
+pip install -r test-requirements.txt
+```
+
 From the root directory, run:
 
 ```shell
 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:
 
@@ -222,7 +168,7 @@ 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:
@@ -234,7 +180,7 @@ 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:
 
@@ -244,7 +190,7 @@ 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:
 
@@ -257,7 +203,7 @@ 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)
 

dev-requirements.txt

@@ -3,10 +3,11 @@ coverage~=7.6.12
 grpcio-tools~=1.67.1
 pip-tools~=7.4.1
 pre-commit~=4.0.1
-pyright~=1.1.394
+pyright~=1.1.397
 pytest~=8.3.4
 pytest-asyncio~=0.25.3
-ruff~=0.9.7
+pytest-aiohttp==1.1.0
+ruff~=0.11.1
 setuptools~=70.0.0
 setuptools_scm~=8.1.0
 python-dotenv~=1.0.1

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

docs/api/conf.py

@@ -50,6 +50,13 @@ autodoc_mock_imports = [
     "pyht.protos",
     "pyht.protos.api_pb2",
     "pipecat_ai_playht",  # PlayHT wrapper
+    "aiortc",
+    "aiortc.mediastreams",
+    "cv2",
+    "av",
+    "pyneuphonic",
+    "mem0",
+    "mlx_whisper",
     "anthropic",
     "assemblyai",
     "boto3",
@@ -68,7 +75,6 @@ autodoc_mock_imports = [
     "openpipe",
     "simli",
     "soundfile",
-    # Existing mocks
     "pipecat_ai_krisp",
     "pyaudio",
     "_tkinter",
@@ -79,6 +85,66 @@ autodoc_mock_imports = [
     "pydantic.Field",
     "pydantic._internal._model_construction",
     "pydantic._internal._fields",
+    # Moondream dependencies
+    "torch",
+    "transformers",
+    "intel_extension_for_pytorch",
+    # Ultravox dependencies
+    "huggingface_hub",
+    "vllm",
+    "vllm.engine.arg_utils",
+    "transformers.AutoTokenizer",
+    # Langchain dependencies
+    "langchain_core",
+    "langchain_core.messages",
+    "langchain_core.runnables",
+    "langchain_core.messages.AIMessageChunk",
+    "langchain_core.runnables.Runnable",
+    # LiveKit dependencies
+    "livekit",
+    "livekit.rtc",
+    "livekit_api",
+    "livekit_protocol",
+    "tenacity",
+    "tenacity.retry",
+    "tenacity.stop_after_attempt",
+    "tenacity.wait_exponential",
+    "rtc",
+    "rtc.Room",
+    "rtc.RoomOptions",
+    "rtc.AudioSource",
+    "rtc.LocalAudioTrack",
+    "rtc.TrackPublishOptions",
+    "rtc.TrackSource",
+    "rtc.AudioStream",
+    "rtc.AudioFrameEvent",
+    "rtc.AudioFrame",
+    "rtc.Track",
+    "rtc.TrackKind",
+    "rtc.RemoteParticipant",
+    "rtc.RemoteTrackPublication",
+    "rtc.DataPacket",
+    # Riva dependencies
+    "riva",
+    "riva.client",
+    "riva.client.Auth",
+    "riva.client.ASRService",
+    "riva.client.StreamingRecognitionConfig",
+    "riva.client.RecognitionConfig",
+    "riva.client.AudioEncoding",
+    "riva.client.proto.riva_tts_pb2",
+    "riva.client.SpeechSynthesisService",
+    # Local CoreML Smart Turn dependencies
+    "coremltools",
+    "coremltools.models",
+    "coremltools.models.MLModel",
+    "torch",
+    "torch.nn",
+    "torch.nn.functional",
+    "transformers",
+    "transformers.AutoFeatureExtractor",
+    # Also add specific classes that are imported
+    "AutoFeatureExtractor",
 ]
 
 # HTML output settings
@@ -110,12 +176,25 @@ def verify_modules():
         },
     }
 
+    # Skip importing modules that are in autodoc_mock_imports
+    skipped_modules = set(autodoc_mock_imports)
+
     missing = []
     for category, modules in required_modules.items():
         if isinstance(modules, dict):
             # Handle nested structure
             for subcategory, submodules in modules.items():
                 for module in submodules:
+                    # Check if module is in autodoc_mock_imports
+                    if (
+                        f"pipecat.{category}.{subcategory}.{module}" in skipped_modules
+                        or module in skipped_modules
+                    ):
+                        logger.info(
+                            f"Skipping import of mocked module: pipecat.{category}.{subcategory}.{module}"
+                        )
+                        continue
+
                     try:
                         __import__(f"pipecat.{category}.{subcategory}.{module}")
                         logger.info(
@@ -129,6 +208,11 @@ def verify_modules():
         else:
             # Handle flat structure
             for module in modules:
+                # Check if module is in autodoc_mock_imports
+                if f"pipecat.{category}.{module}" in skipped_modules or module in skipped_modules:
+                    logger.info(f"Skipping import of mocked module: pipecat.{category}.{module}")
+                    continue
+
                 try:
                     __import__(f"pipecat.{category}.{module}")
                     logger.info(f"Successfully imported pipecat.{category}.{module}")

docs/api/index.rst

@@ -45,8 +45,10 @@ Transport & Serialization
 Utilities
 ~~~~~~~~~
 
+* :mod:`Adapters <pipecat.adapters>`
 * :mod:`Clocks <pipecat.clocks>`
 * :mod:`Metrics <pipecat.metrics>`
+* :mod:`Observers <pipecat.observers>`
 * :mod:`Sync <pipecat.sync>`
 * :mod:`Transcriptions <pipecat.transcriptions>`
 * :mod:`Utils <pipecat.utils>`
@@ -56,10 +58,12 @@ Utilities
    :caption: API Reference
    :hidden:
 
+   Adapters <api/pipecat.adapters>
    Audio <api/pipecat.audio>
    Clocks <api/pipecat.clocks>
    Frames <api/pipecat.frames>
    Metrics <api/pipecat.metrics>
+   Observers <api/pipecat.observers>
    Pipeline <api/pipecat.pipeline>
    Processors <api/pipecat.processors>
    Serializers <api/pipecat.serializers>

docs/api/requirements.txt

@@ -10,31 +10,44 @@ pipecat-ai[anthropic]
 pipecat-ai[assemblyai]
 pipecat-ai[aws]
 pipecat-ai[azure]
-pipecat-ai[canonical]
 pipecat-ai[cartesia]
+pipecat-ai[cerebras]
+pipecat-ai[deepseek]
 pipecat-ai[daily]
 pipecat-ai[deepgram]
 pipecat-ai[elevenlabs]
 pipecat-ai[fal]
 pipecat-ai[fireworks]
+pipecat-ai[fish]
 pipecat-ai[gladia]
 pipecat-ai[google]
 pipecat-ai[grok]
 pipecat-ai[groq]
-# pipecat-ai[krisp] # Mocked instead
-pipecat-ai[langchain]
-pipecat-ai[livekit]
+# pipecat-ai[krisp] # Mocked
+pipecat-ai[koala]
+# pipecat-ai[langchain] # Mocked
+# pipecat-ai[livekit] # Mocked
 pipecat-ai[lmnt]
 pipecat-ai[local]
-pipecat-ai[moondream]
+# pipecat-ai[local-smart-turn] # Mocked
+# pipecat-ai[mem0] # Mocked
+# pipecat-ai[mlx-whisper] # Mocked
+# pipecat-ai[moondream] # Mocked
 pipecat-ai[nim]
+# pipecat-ai[neuphonic] # Mocked
 pipecat-ai[noisereduce]
 pipecat-ai[openai]
 # pipecat-ai[openpipe]
 # pipecat-ai[playht] # Mocked due to grpcio conflict with riva
-pipecat-ai[riva]
+pipecat-ai[qwen]
+pipecat-ai[remote-smart-turn]
+# pipecat-ai[riva] # Mocked
 pipecat-ai[silero]
 pipecat-ai[simli]
 pipecat-ai[soundfile]
+pipecat-ai[tavus]
+pipecat-ai[together]
+# pipecat-ai[ultravox] # Mocked
+# pipecat-ai[webrtc] # Mocked
 pipecat-ai[websocket]
 pipecat-ai[whisper]

dot-env.template

@@ -29,6 +29,9 @@ DAILY_SAMPLE_ROOM_URL=https://...
 ELEVENLABS_API_KEY=...
 ELEVENLABS_VOICE_ID=...
 
+# Neuphonic
+NEUPHONIC_API_KEY=...
+
 # Fal
 FAL_KEY=...
 
@@ -87,3 +90,21 @@ ASSEMBLYAI_API_KEY=...
 
 # OpenRouter
 OPENROUTER_API_KEY=...
+
+# Piper
+PIPER_BASE_URL=...
+
+# Smart turn
+LOCAL_SMART_TURN_MODEL_PATH=...
+FAL_SMART_TURN_API_KEY=...
+
+# Twilio
+TWILIO_ACCOUNT_SID=...
+TWILIO_AUTH_TOKEN=...
+
+# MiniMax
+MINIMAX_API_KEY=...
+MINIMAX_GROUP_ID=...
+
+# Sarvam AI
+SARVAM_API_KEY=...

examples/bot-ready-signalling/client/javascript/package.json

@@ -12,7 +12,7 @@
   "license": "ISC",
   "description": "",
   "devDependencies": {
-    "vite": "^6.0.9"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@daily-co/daily-js": "0.74.0"

examples/bot-ready-signalling/server/signalling_bot.py

@@ -18,7 +18,7 @@ from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame,
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -64,7 +64,7 @@ async def main():
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+            voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
         )
 
         runner = PipelineRunner()

examples/canonical-metrics/.gitignore

@@ -1,161 +0,0 @@
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-recordings/
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-cover/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-.pybuilder/
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# IPython
-profile_default/
-ipython_config.py
-
-# pyenv
-#   For a library or package, you might want to ignore these files since the code is
-#   intended to run in multiple environments; otherwise, check them in:
-# .python-version
-
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
-# poetry
-#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
-#   This is especially recommended for binary packages to ensure reproducibility, and is more
-#   commonly ignored for libraries.
-#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
-#poetry.lock
-
-# pdm
-#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
-#pdm.lock
-#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
-#   in version control.
-#   https://pdm.fming.dev/#use-with-ide
-.pdm.toml
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
-__pypackages__/
-
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
-venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
-
-# pytype static type analyzer
-.pytype/
-
-# Cython debug symbols
-cython_debug/
-
-# PyCharm
-#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
-#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
-#  and can be added to the global gitignore or merged into this file.  For a more nuclear
-#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
-runpod.toml

examples/canonical-metrics/README.md

@@ -1,66 +0,0 @@
-# Chatbot with canonical-metrics
-
-This project implements a chatbot using a pipeline architecture that integrates audio processing, transcription, and a language model for conversational interactions. The chatbot operates within a daily communication environment, utilizing various services for text-to-speech and language model responses.
-
-## Features
-
-- **Audio Input and Output**: Captures microphone input and plays back audio responses.
-- **Voice Activity Detection**: Utilizes Silero VAD to manage audio input intelligently.
-- **Text-to-Speech**: Integrates ElevenLabs TTS service to convert text responses into audio.
-- **Language Model Interaction**: Uses OpenAI's GPT-4 model to generate responses based on user input.
-- **Transcription Services**: Captures and transcribes participant speech for analytics.
-- **Metrics Collection**: Sends audio data for analysis via Canonical Metrics Service.
-
-## Requirements
-
-- Python 3.10+
-- `python-dotenv`
-- Additional libraries from the `pipecat` package.
-
-## Setup
-
-1. Clone the repository.
-2. Install the required packages.
-3. Set up environment variables for API keys:
-   - `OPENAI_API_KEY`
-   - `ELEVENLABS_API_KEY`
-   - `CANONICAL_API_KEY`
-   - `CANONICAL_API_URL`
-4. Run the script.
-
-## Usage
-
-The chatbot introduces itself and engages in conversations, providing brief and creative responses. Designed for flexibility, it can support multiple languages with appropriate configuration.
-
-## Events
-
-- Participants joining or leaving the call are handled dynamically, adjusting the chatbot's behavior accordingly.
-
-
-ℹ️ The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded.
-
-## Get started
-
-```python
-python3 -m venv venv
-source venv/bin/activate
-pip install -r requirements.txt
-
-cp env.example .env # and add your credentials
-
-```
-
-## Run the server
-
-```bash
-python server.py
-```
-
-Then, visit `http://localhost:7860/` in your browser to start a chatbot session.
-
-## Build and test the Docker image
-
-```
-docker build -t chatbot .
-docker run --env-file .env -p 7860:7860 chatbot
-```

examples/canonical-metrics/bot.py

@@ -1,148 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-import sys
-import uuid
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-from runner import configure
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame
-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.processors.audio.audio_buffer_processor import AudioBufferProcessor
-from pipecat.services.canonical import CanonicalMetricsService
-from pipecat.services.elevenlabs import ElevenLabsTTSService
-from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, token) = await configure(session)
-
-        transport = DailyTransport(
-            room_url,
-            token,
-            "Chatbot",
-            DailyParams(
-                audio_out_enabled=True,
-                audio_in_enabled=True,
-                camera_out_enabled=False,
-                vad_enabled=True,
-                vad_audio_passthrough=True,
-                vad_analyzer=SileroVADAnalyzer(),
-                transcription_enabled=True,
-                #
-                # Spanish
-                #
-                # transcription_settings=DailyTranscriptionSettings(
-                #     language="es",
-                #     tier="nova",
-                #     model="2-general"
-                # )
-            ),
-        )
-
-        tts = ElevenLabsTTSService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            #
-            # English
-            #
-            voice_id="cgSgspJ2msm6clMCkdW9",
-            #
-            # Spanish
-            #
-            # model="eleven_multilingual_v2",
-            # voice_id="gD1IexrzCvsXPHUuT0s3",
-        )
-
-        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-
-        messages = [
-            {
-                "role": "system",
-                #
-                # English
-                #
-                "content": "You are Chatbot, a friendly, helpful robot. 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, but keep your responses brief. Start by introducing yourself. Keep all your responses to 12 words or fewer.",
-                #
-                # Spanish
-                #
-                # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
-            },
-        ]
-
-        context = OpenAILLMContext(messages)
-        context_aggregator = llm.create_context_aggregator(context)
-
-        """
-        CanonicalMetrics uses AudioBufferProcessor under the hood to buffer the audio. On
-        call completion, CanonicalMetrics will send the audio buffer to Canonical for
-        analysis. Visit https://voice.canonical.chat to learn more.
-        """
-        audio_buffer_processor = AudioBufferProcessor(num_channels=2)
-        canonical = CanonicalMetricsService(
-            audio_buffer_processor=audio_buffer_processor,
-            aiohttp_session=session,
-            api_key=os.getenv("CANONICAL_API_KEY"),
-            call_id=str(uuid.uuid4()),
-            assistant="pipecat-chatbot",
-            assistant_speaks_first=True,
-            context=context,
-        )
-        pipeline = Pipeline(
-            [
-                transport.input(),  # microphone
-                context_aggregator.user(),
-                llm,
-                tts,
-                transport.output(),
-                audio_buffer_processor,  # captures audio into a buffer
-                canonical,  # uploads audio buffer to Canonical AI for metrics
-                context_aggregator.assistant(),
-            ]
-        )
-
-        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
-
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            await audio_buffer_processor.start_recording()
-            await transport.capture_participant_transcription(participant["id"])
-            await task.queue_frames([context_aggregator.user().get_context_frame()])
-
-        @transport.event_handler("on_participant_left")
-        async def on_participant_left(transport, participant, reason):
-            print(f"Participant left: {participant}")
-            await task.cancel()
-
-        @transport.event_handler("on_call_state_updated")
-        async def on_call_state_updated(transport, state):
-            if state == "left":
-                # Here we don't want to cancel, we just want to finish sending
-                # whatever is queued, so we use an EndFrame().
-                await task.queue_frame(EndFrame())
-
-        runner = PipelineRunner()
-
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/canonical-metrics/requirements.txt

@@ -1,5 +0,0 @@
-python-dotenv
-fastapi[all]
-uvicorn
-pipecat-ai[daily,openai,silero,elevenlabs,canonical]
-

examples/chatbot-audio-recording/bot.py

@@ -23,8 +23,8 @@ from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
-from pipecat.services.elevenlabs import ElevenLabsTTSService
-from pipecat.services.openai import OpenAILLMService
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -32,10 +32,16 @@ load_dotenv(override=True)
 logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
+# Create the recordings directory if it doesn't exist
+os.makedirs("recordings", exist_ok=True)
 
-async def save_audio(audio: bytes, sample_rate: int, num_channels: int):
+
+async def save_audio(audio: bytes, sample_rate: int, num_channels: int, name: str):
     if len(audio) > 0:
-        filename = f"conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav"
+        filename = os.path.join(
+            "recordings",
+            f"{name}_conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav",
+        )
         with io.BytesIO() as buffer:
             with wave.open(buffer, "wb") as wf:
                 wf.setsampwidth(2)
@@ -60,9 +66,7 @@ async def main():
             DailyParams(
                 audio_out_enabled=True,
                 audio_in_enabled=True,
-                camera_out_enabled=False,
-                vad_enabled=True,
-                vad_audio_passthrough=True,
+                video_out_enabled=False,
                 vad_analyzer=SileroVADAnalyzer(),
                 transcription_enabled=True,
                 #
@@ -89,7 +93,7 @@ async def main():
             # voice_id="gD1IexrzCvsXPHUuT0s3",
         )
 
-        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
         messages = [
             {
@@ -110,7 +114,7 @@ async def main():
 
         # NOTE: Watch out! This will save all the conversation in memory. You
         # can pass `buffer_size` to get periodic callbacks.
-        audiobuffer = AudioBufferProcessor()
+        audiobuffer = AudioBufferProcessor(enable_turn_audio=True)
 
         pipeline = Pipeline(
             [
@@ -128,7 +132,15 @@ async def main():
 
         @audiobuffer.event_handler("on_audio_data")
         async def on_audio_data(buffer, audio, sample_rate, num_channels):
-            await save_audio(audio, sample_rate, num_channels)
+            await save_audio(audio, sample_rate, num_channels, "full")
+
+        @audiobuffer.event_handler("on_user_turn_audio_data")
+        async def on_user_turn_audio_data(buffer, audio, sample_rate, num_channels):
+            await save_audio(audio, sample_rate, num_channels, "user")
+
+        @audiobuffer.event_handler("on_bot_turn_audio_data")
+        async def on_bot_turn_audio_data(buffer, audio, sample_rate, num_channels):
+            await save_audio(audio, sample_rate, num_channels, "bot")
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/chatbot-audio-recording/runner.py

@@ -53,4 +53,3 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
     token = await daily_rest_helper.get_token(url, expiry_time)
 
     return (url, token)
-    return (url, token)

examples/daily-custom-tracks/README.md

@@ -0,0 +1,39 @@
+# Daily Custom Tracks
+
+This example shows how to send and receive Daily custom tracks. We will run a simple `daily-python` application to send an audio file with a custom track (named "pipecat") to a room. Then, the Pipecat bot will mirror that custom track into another custom track (named "pipecat-mirror") in the same room.
+
+## Get started
+
+```python
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+```
+
+## Run the bot
+
+Start the bot by giving it a Daily room URL.
+
+```bash
+python bot.py -u ROOM_URL
+```
+
+The bot will wait for the first participant to join. Then, it will mirror a custom track named "pipecat" into a new custom track named "pipecat-mirror".
+
+## Run the sender
+
+Now, run the custom track sender. This is a simple `daily-python` application that opens and audio file and sends it as a custom track to the same Daily room.
+
+```bash
+python custom_track_sender.py -u ROOM_URL -i office-ambience-mono-16000.mp3
+```
+
+## Open client
+
+Finally, open the client so you can hear both custom tracks.
+
+```bash
+open index.html
+```
+
+Once the client is opened, copy the URL of the Daily room and join it. You should be able to select which custom track you want to hear.

examples/daily-custom-tracks/bot.py

@@ -0,0 +1,87 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import sys
+
+import aiohttp
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import Frame, InputAudioRawFrame, OutputAudioRawFrame
+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 FrameDirection, FrameProcessor
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+class CustomTrackMirrorProcessor(FrameProcessor):
+    def __init__(self, transport_destination: str, **kwargs):
+        super().__init__(**kwargs)
+        self._transport_destination = transport_destination
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, InputAudioRawFrame) and frame.transport_source:
+            output_frame = OutputAudioRawFrame(
+                audio=frame.audio,
+                sample_rate=frame.sample_rate,
+                num_channels=frame.num_channels,
+            )
+            output_frame.transport_destination = self._transport_destination
+            await self.push_frame(output_frame)
+        else:
+            await self.push_frame(frame, direction)
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            None,
+            "Custom tracks mirror",
+            DailyParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                microphone_out_enabled=False,  # Disable since we just use custom tracks
+                audio_out_destinations=["pipecat-mirror"],
+            ),
+        )
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                CustomTrackMirrorProcessor("pipecat-mirror"),
+                transport.output(),  # Transport bot output
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                audio_in_sample_rate=16000,
+                audio_out_sample_rate=16000,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_audio(participant["id"], audio_source="pipecat")
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/daily-custom-tracks/custom_track_sender.py

@@ -0,0 +1,74 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import time
+
+from daily import CallClient, CustomAudioSource, Daily
+from pydub import AudioSegment
+
+parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
+parser.add_argument("-u", "--url", type=str, required=True, help="URL of the Daily room to join")
+parser.add_argument(
+    "-i", "--input", type=str, required=True, help="Input audio file (needs 16000 sample rate)"
+)
+
+args, _ = parser.parse_known_args()
+
+audio = AudioSegment.from_mp3(args.input)
+
+raw_bytes = audio.raw_data
+sample_rate = audio.frame_rate
+channels = audio.channels
+
+print(f"Length: {len(raw_bytes)} bytes")
+print(f"Sample rate: {sample_rate}, Channels: {channels}")
+
+# Initialize the Daily context & create call client
+Daily.init()
+
+client = CallClient()
+
+# Join the room and indicate we have a custom track named "pipecat".
+client.join(
+    args.url,
+    client_settings={
+        "publishing": {
+            "camera": False,
+            "microphone": False,
+            "customAudio": {"pipecat": True},
+        },
+    },
+)
+
+# Just sleep for a couple of seconds. To do this well we should really use
+# completions.
+time.sleep(2)
+
+# Create the custom audio source. This is where we will write our audio.
+audio_source = CustomAudioSource(sample_rate, channels)
+
+# Create an audio track and assign it our audio source.
+client.add_custom_audio_track("pipecat", audio_source)
+
+# Just sleep for a second. To do this well we should really use completions.
+time.sleep(1)
+
+try:
+    # Just write one second of audio until we have read all the file.
+    chunk_size = sample_rate * channels * 2
+    while len(raw_bytes) > 0:
+        chunk = raw_bytes[:chunk_size]
+        raw_bytes = raw_bytes[chunk_size:]
+        audio_source.write_frames(chunk)
+
+except KeyboardInterrupt:
+    client.leave()
+
+# Just sleep for a second. To do this well we should really use completions.
+time.sleep(1)
+
+client.release()

examples/daily-custom-tracks/index.html

@@ -0,0 +1,173 @@
+<html>
+  <head>
+    <title>daily custom tracks</title>
+  </head>
+  <script crossorigin src="https://unpkg.com/@daily-co/daily-js"></script>
+  <script src="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.js"></script>
+  <link
+    rel="stylesheet"
+    type="text/css"
+    href="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.css"
+    />
+  <script>
+    function enableButton(buttonId, enable) {
+        const button = document.getElementById(buttonId);
+        button.disabled = !enable;
+    }
+
+    function enableJoinButton(enable) {
+        enableButton("join-button", enable);
+    }
+
+    function enableLeaveButton(enable) {
+        enableButton("leave-button", enable);
+    }
+
+    function destroyPlayers(query) {
+        const items = document.querySelectorAll(query);
+        if (items) {
+            for (const item of items) {
+                item.remove();
+            }
+        }
+    }
+
+    function destroyParticipantPlayers(participantId) {
+        destroyPlayers(`audio[data-participant-id="${participantId}"]`);
+        destroyPlayers(`button[data-participant-id="${participantId}"]`);
+    }
+
+    async function startPlayer(player, track) {
+        player.muted = false;
+        player.autoplay = true;
+        if (track != null) {
+            player.srcObject = new MediaStream([track]);
+        }
+    }
+
+    async function buildAudioPlayer(track, participantId) {
+        const audioContainer = document.getElementById("audio-container");
+        const player = document.createElement("audio");
+        player.dataset.participantId = participantId;
+
+        // Create a new button for controlling audio
+        const audioControlButton = document.createElement("button");
+        audioControlButton.className = "ui primary green button"
+        audioControlButton.innerText = track._mediaTag == "cam-audio" ? "english" : track._mediaTag;
+        audioControlButton.dataset.participantId = participantId;
+        audioControlButton.onclick = () => {
+            if (player.paused) {
+
+                player.play();
+                audioControlButton.className = "ui primary red button"
+            } else {
+                player.pause();
+                audioControlButton.className = "ui primary green button"
+            }
+        };
+
+        audioContainer.appendChild(player);
+        audioContainer.appendChild(audioControlButton);
+
+        await startPlayer(player, track);
+        player.pause()
+
+        return player;
+    }
+
+    function subscribeToTracks(participantId) {
+        console.log(`subscribing to track`);
+
+        if (participantId === "local") {
+            return;
+        }
+
+        callObject.updateParticipant(participantId, {
+            setSubscribedTracks: {
+                audio: true,
+                video: false,
+                custom: true,
+            },
+        });
+    }
+
+    function startDaily() {
+        enableJoinButton(true);
+        enableLeaveButton(false);
+
+        window.callObject = window.DailyIframe.createCallObject({});
+
+        callObject.on("participant-joined", (e) => {
+            if (!e.participant.local) {
+                console.log("participant-joined", e.participant);
+               subscribeToTracks(e.participant.session_id);
+            }
+        });
+
+        callObject.on("participant-left", (e) => {
+            console.log("participant-left", e.participant.session_id);
+            destroyParticipantPlayers(e.participant.session_id);
+        });
+
+        callObject.on("track-started", async (e) => {
+            console.log("track-started", e.track);
+            if (e.track.kind === "audio") {
+                await buildAudioPlayer(e.track, e.participant.session_id);
+            }
+        });
+    }
+
+    async function joinRoom() {
+        enableJoinButton(false);
+        enableLeaveButton(true);
+
+        const meetingUrl = document.getElementById("meeting-url").value;
+
+        callObject.join({
+            url: meetingUrl,
+            startVideoOff: true,
+            startAudioOff: true,
+            subscribeToTracksAutomatically: false,
+            receiveSettings: {
+                base: { video: { layer: 0 } },
+            },
+        });
+    }
+
+    async function leaveRoom() {
+        enableJoinButton(true);
+        enableLeaveButton(false);
+
+        callObject.leave();
+
+        const audioContainer = document.getElementById("audio-container");
+        audioContainer.replaceChildren();
+    }
+  </script>
+
+  <body onload="startDaily()">
+    <div class="ui centered page grid" style="margin-top: 30px">
+      <div class="ten wide column">
+        <div class="ui form" style="margin-top: 30px">
+          <div class="field">
+            <label>Meeting URL</label>
+            <input id="meeting-url" value="" />
+          </div>
+        </div>
+      </div>
+    </div>
+    <div class="ui centered aligned header" style="margin-top: 30px">
+      <button id="join-button" class="ui primary button" onclick="joinRoom()">
+        Join
+      </button>
+      <button id="leave-button" class="ui button" onclick="leaveRoom()">
+        Leave
+      </button>
+    </div>
+    <div id="tile" class="ui container" style="margin-top: 30px">
+      <div id="tile" class="ui center aligned grid">
+        <div id="audio-container"></div><br/>
+      </div>
+    </div>
+  </body>
+</html>

examples/daily-custom-tracks/requirements.txt

@@ -0,0 +1,2 @@
+pydub
+pipecat-ai[daily]

examples/daily-multi-translation/Dockerfile

@@ -1,7 +1,12 @@
 FROM python:3.10-bullseye
+
 RUN mkdir /app
+RUN mkdir /app/assets
+RUN mkdir /app/utils
 COPY *.py /app/
 COPY requirements.txt /app/
+
+
 WORKDIR /app
 RUN pip3 install -r requirements.txt
 

examples/daily-multi-translation/README.md

@@ -0,0 +1,39 @@
+# Daily Multi Translation
+
+This example shows how to use Daily to stream multiple simultaneous translations using a single transport. Daily provides custom tracks and in this example we will simultaneously translate incoming audio in English to Spanish, French and German, each of them being sent to a custom track.
+
+## Get started
+
+```python
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+
+cp env.example .env # and add your credentials
+
+```
+
+## Run the server
+
+```bash
+python server.py
+```
+
+Then, visit `http://localhost:7860/` in your browser. This will open a Daily Prebuilt room where you will speak in English (make sure you are not muted).
+
+## Open client
+
+Next, you need to open the client that will listen to the translations.
+
+```bash
+open index.html
+```
+
+Once the client is opened, copy the URL of the Daily room created above and join it. You should be able to select which translation you want to hear.
+
+## Build and test the Docker image
+
+```
+docker build -t daily-multi-translation .
+docker run --env-file .env -p 7860:7860 daily-multi-translation
+```

examples/daily-multi-translation/bot.py

@@ -0,0 +1,165 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.mixers.soundfile_mixer import SoundfileMixer
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver
+from pipecat.pipeline.parallel_pipeline import ParallelPipeline
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.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.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+BACKGROUND_SOUND_FILE = "office-ambience-mono-16000.mp3"
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Multi translation bot",
+            DailyParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                audio_out_mixer={
+                    "spanish": SoundfileMixer(
+                        sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
+                    ),
+                    "french": SoundfileMixer(
+                        sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
+                    ),
+                    "german": SoundfileMixer(
+                        sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
+                    ),
+                },
+                audio_out_destinations=["spanish", "french", "german"],
+                microphone_out_enabled=False,  # Disable since we just use custom tracks
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+        tts_spanish = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="cefcb124-080b-4655-b31f-932f3ee743de",
+            transport_destination="spanish",
+        )
+        tts_french = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="8832a0b5-47b2-4751-bb22-6a8e2149303d",
+            transport_destination="french",
+        )
+        tts_german = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="38aabb6a-f52b-4fb0-a3d1-988518f4dc06",
+            transport_destination="german",
+        )
+
+        messages_spanish = [
+            {
+                "role": "system",
+                "content": "You will be provided with a sentence in English, and your task is to only translate it into Spanish.",
+            },
+        ]
+        messages_french = [
+            {
+                "role": "system",
+                "content": "You will be provided with a sentence in English, and your task is to only translate it into French.",
+            },
+        ]
+        messages_german = [
+            {
+                "role": "system",
+                "content": "You will be provided with a sentence in English, and your task is to only translate it into German.",
+            },
+        ]
+
+        llm_spanish = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+        llm_french = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+        llm_german = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+        context_spanish = OpenAILLMContext(messages_spanish)
+        context_aggregator_spanish = llm_spanish.create_context_aggregator(context_spanish)
+
+        context_french = OpenAILLMContext(messages_french)
+        context_aggregator_french = llm_french.create_context_aggregator(context_french)
+
+        context_german = OpenAILLMContext(messages_german)
+        context_aggregator_german = llm_german.create_context_aggregator(context_german)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,
+                ParallelPipeline(
+                    # Spanish pipeline.
+                    [
+                        context_aggregator_spanish.user(),
+                        llm_spanish,
+                        tts_spanish,
+                        context_aggregator_spanish.assistant(),
+                    ],
+                    # French pipeline.
+                    [
+                        context_aggregator_french.user(),
+                        llm_french,
+                        tts_french,
+                        context_aggregator_french.assistant(),
+                    ],
+                    # German pipeline.
+                    [
+                        context_aggregator_german.user(),
+                        llm_german,
+                        tts_german,
+                        context_aggregator_german.assistant(),
+                    ],
+                ),
+                transport.output(),  # Transport bot output
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                audio_in_sample_rate=16000,
+                audio_out_sample_rate=16000,
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+            observers=[TranscriptionLogObserver()],
+        )
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/daily-multi-translation/env.example

@@ -1,6 +1,5 @@
 DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
 DAILY_API_KEY=7df...
 OPENAI_API_KEY=sk-PL...
-ELEVENLABS_API_KEY=aeb...
-CANONICAL_API_KEY=can...
-CANONICAL_API_URL=
+DEEPGRAM_API_KEY=efb...
+CARTESIA_API_KEY=aeb...

examples/daily-multi-translation/index.html

@@ -0,0 +1,202 @@
+<html>
+  <head>
+    <title>daily multi translation</title>
+  </head>
+  <script crossorigin src="https://unpkg.com/@daily-co/daily-js"></script>
+  <script
+    src="https://code.jquery.com/jquery-3.1.1.min.js"
+    integrity="sha256-hVVnYaiADRTO2PzUGmuLJr8BLUSjGIZsDYGmIJLv2b8="
+    crossorigin="anonymous"
+    ></script>
+  <script src="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.js"></script>
+  <link
+    rel="stylesheet"
+    type="text/css"
+    href="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.css"
+    />
+  <script>
+    function enableButton(buttonId, enable) {
+        const button = document.getElementById(buttonId);
+        button.disabled = !enable;
+    }
+
+    function enableJoinButton(enable) {
+        enableButton("join-button", enable);
+    }
+
+    function enableLeaveButton(enable) {
+        enableButton("leave-button", enable);
+    }
+
+    function destroyPlayers(query) {
+        const items = document.querySelectorAll(query);
+        if (items) {
+            for (const item of items) {
+                item.remove();
+            }
+        }
+    }
+
+    function destroyParticipantPlayers(participantId) {
+        destroyPlayers(`video[data-participant-id="${participantId}"]`);
+        destroyPlayers(`audio[data-participant-id="${participantId}"]`);
+        destroyPlayers(`button[data-participant-id="${participantId}"]`);
+    }
+
+    async function startPlayer(player, track) {
+        player.muted = false;
+        player.autoplay = true;
+        if (track != null) {
+            player.srcObject = new MediaStream([track]);
+        }
+    }
+
+    async function buildVideoPlayer(track, participantId) {
+        const videoContainer = document.getElementById("video-container");
+        const player = document.createElement("video");
+        player.dataset.participantId = participantId;
+
+        videoContainer.appendChild(player);
+
+        await startPlayer(player, track);
+        await player.play();
+
+        return player;
+    }
+
+    async function buildAudioPlayer(track, participantId) {
+        const audioContainer = document.getElementById("audio-container");
+        const player = document.createElement("audio");
+        player.dataset.participantId = participantId;
+
+        // Create a new button for controlling audio
+        const audioControlButton = document.createElement("button");
+        audioControlButton.className = "ui primary green button"
+        audioControlButton.innerText = track._mediaTag == "cam-audio" ? "english" : track._mediaTag;
+        audioControlButton.dataset.participantId = participantId;
+        audioControlButton.onclick = () => {
+            if (player.paused) {
+
+                player.play();
+                audioControlButton.className = "ui primary red button"
+            } else {
+                player.pause();
+                audioControlButton.className = "ui primary green button"
+            }
+        };
+
+        audioContainer.appendChild(player);
+        audioContainer.appendChild(audioControlButton);
+
+        await startPlayer(player, track);
+        player.pause()
+
+        return player;
+    }
+
+    function subscribeToTracks(participantId) {
+        console.log(`subscribing to track`);
+
+        if (participantId === "local") {
+            return;
+        }
+
+        callObject.updateParticipant(participantId, {
+            setSubscribedTracks: {
+                audio: true,
+                video: true,
+                custom: true,
+            },
+        });
+    }
+
+    function startDaily() {
+        enableJoinButton(true);
+        enableLeaveButton(false);
+
+        window.callObject = window.DailyIframe.createCallObject({});
+
+        callObject.on("participant-joined", (e) => {
+            if (!e.participant.local) {
+                console.log("participant-joined", e.participant);
+               subscribeToTracks(e.participant.session_id);
+            }
+        });
+
+        callObject.on("participant-left", (e) => {
+            console.log("participant-left", e.participant.session_id);
+            destroyParticipantPlayers(e.participant.session_id);
+        });
+
+        callObject.on("track-started", async (e) => {
+            console.log("track-started", e.track);
+            if (e.track.kind === "video") {
+                await buildVideoPlayer(e.track, e.participant.session_id);
+            } else if (e.track.kind === "audio") {
+                await buildAudioPlayer(e.track, e.participant.session_id);
+            }
+        });
+    }
+
+    async function joinRoom() {
+        enableJoinButton(false);
+        enableLeaveButton(true);
+
+        const meetingUrl = document.getElementById("meeting-url").value;
+
+        callObject.join({
+            url: meetingUrl,
+            startVideoOff: true,
+            startAudioOff: true,
+            subscribeToTracksAutomatically: false,
+            receiveSettings: {
+                base: { video: { layer: 0 } },
+            },
+        });
+    }
+
+    async function leaveRoom() {
+        enableJoinButton(true);
+        enableLeaveButton(false);
+
+        callObject.leave();
+
+        const videoContainer = document.getElementById("video-container");
+        videoContainer.replaceChildren();
+
+        const audioContainer = document.getElementById("audio-container");
+        audioContainer.replaceChildren();
+    }
+  </script>
+
+  <body onload="startDaily()">
+    <div class="ui centered page grid" style="margin-top: 30px">
+      <div class="ten wide column">
+        <div class="ui form" style="margin-top: 30px">
+          <div class="field">
+            <label>Meeting URL</label>
+            <input id="meeting-url" value="" />
+          </div>
+        </div>
+      </div>
+    </div>
+    <div class="ui centered aligned header" style="margin-top: 30px">
+      <button id="join-button" class="ui primary button" onclick="joinRoom()">
+        Join
+      </button>
+      <button id="leave-button" class="ui button" onclick="leaveRoom()">
+        Leave
+      </button>
+    </div>
+    <div id="tile" class="ui container" style="margin-top: 30px">
+      <div id="tile" class="ui center aligned grid">
+        <div id="audio-container"></div><br/>
+      </div>
+    </div>
+    <div id="tile" class="ui container" style="margin-top: 30px">
+      <div id="tile" class="ui center aligned grid">
+        <div id="video-container" class="ui segment"></div>
+      </div>
+    </div>
+  </body>
+</html>

examples/daily-multi-translation/requirements.txt

@@ -0,0 +1,5 @@
+aiofiles
+python-dotenv
+fastapi[all]
+uvicorn
+pipecat-ai[daily,deepgram,openai,silero,cartesia]

examples/daily-multi-translation/runner.py

@@ -0,0 +1,55 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+import aiohttp
+
+from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
+
+
+async def configure(aiohttp_session: aiohttp.ClientSession):
+    parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
+    parser.add_argument(
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
+    parser.add_argument(
+        "-k",
+        "--apikey",
+        type=str,
+        required=False,
+        help="Daily API Key (needed to create an owner token for the room)",
+    )
+
+    args, unknown = parser.parse_known_args()
+
+    url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
+    key = args.apikey or os.getenv("DAILY_API_KEY")
+
+    if not url:
+        raise Exception(
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
+
+    if not key:
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
+
+    daily_rest_helper = DailyRESTHelper(
+        daily_api_key=key,
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
+    )
+
+    # Create a meeting token for the given room with an expiration 1 hour in
+    # the future.
+    expiry_time: float = 60 * 60
+
+    token = await daily_rest_helper.get_token(url, expiry_time)
+
+    return (url, token)

examples/deployment/flyio-example/bot.py

@@ -1,3 +1,9 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
 import argparse
 import asyncio
 import os
@@ -12,8 +18,8 @@ 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.elevenlabs import ElevenLabsTTSService
-from pipecat.services.openai import OpenAILLMService
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -35,8 +41,7 @@ async def main(room_url: str, token: str):
             api_key=daily_api_key,
             audio_in_enabled=True,
             audio_out_enabled=True,
-            camera_out_enabled=False,
-            vad_enabled=True,
+            video_out_enabled=False,
             vad_analyzer=SileroVADAnalyzer(),
             transcription_enabled=True,
         ),
@@ -47,7 +52,7 @@ async def main(room_url: str, token: str):
         voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
     )
 
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
     messages = [
         {

examples/deployment/modal-example/.gitignore

@@ -1,3 +1,6 @@
+# Modal clone
+modal-examples
+
 # Python
 __pycache__/
 *.py[cod]

examples/deployment/modal-example/README.md

@@ -1,37 +1,91 @@
 # Deploying Pipecat to Modal.com
 
-Barebones deployment example for [modal.com](https://www.modal.com)
+Deployment example for [modal.com](https://www.modal.com). This example demonstrates how to deploy a FastAPI webapp to Modal with an RTVI compatible `/connect` endpoint that launches a Pipecat pipeline in a separate Modal container and returns a room/token for the client to join. This example also supports providing a parameter to the `/connect` endpoint for specifying which Pipecat pipeline to launch; openai, gemini, or vllm. The vllm pipeline points to a self-hosted OpenAI compatible LLM, using a llama model (neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w4a16), deployed to Modal.
 
-1. Install dependencies
+![](diagram.jpg)
 
-```bash
-python -m venv venv
-source venv/bin/active # or OS equivalent
-pip install -r requirements.txt
-```
+# Running this Example
 
-2. Setup .env
+## Install the Modal CLI
 
-```bash
-cp env.example .env
-```
+Setup a Modal account and install it on your machine if you have not already, following their easy 3 steps in their [Getting Started Guide](https://modal.com/docs/guide#getting-started)
 
-Alternatively, you can configure your Modal app to use [secrets](https://modal.com/docs/guide/secrets)
+## Deploy a self-serve LLM
 
-3. Test the app locally
+1. Deploy Modal's OpenAI-compatible LLM service:
 
-```bash
-modal serve app.py
-```
+   ```bash
+   git clone https://github.com/modal-labs/modal-examples
+   cd modal-examples
+   modal deploy 06_gpu_and_ml/llm-serving/vllm_inference.py
+   ```
+
+   Refer to Modal's guide and example for [Deploying an OpenAI-compatible LLM service with vLLM](https://modal.com/docs/examples/vllm_inference) for more details.
+
+2. Take note of the endpoint URL from the previous step, which will look like:
+   ```
+   https://{your-workspace}--example-vllm-openai-compatible-serve.modal.run
+   ```
+   You'll need this for the `bot_vllm.py` file in the next section.
+
+    **Note:**  The default Modal LLM example uses Llama-3.1 and will shut down after 15 minutes of inactivity. Cold starts take 5-10 minutes. To prepare the service, we recommend visiting the `/docs` endpoint (`https://<Modal workspace>--example-vllm-openai-compatible-serve.modal.run/docs`) for your deployed LLM and wait for it to fully load before connecting your client.
+
+## Deploy FastAPI App and Pipecat pipeline to Modal 
+
+1. Setup environment variables
+
+   ```bash
+   cd server
+   cp env.example .env
+   # Modify .env to provide your service API Keys
+   ```
+
+   Alternatively, you can configure your Modal app to use [secrets](https://modal.com/docs/guide/secrets)
+
+2. Update the `modal_url` in `server/src/bot_vllm.py` to point to the url produced from the self-serve llm deploy, mentioned above.
+
+3. From within the `server` directory, test the app locally:
+
+   ```bash
+   modal serve app.py
+   ```
 
 4. Deploy to production
 
-```bash
-modal deploy app.py
-```
+   ```bash
+   modal deploy app.py
+   ```
 
-## Configuration options
+5. Note the endpoint URL produced from this deployment. It will look like:
 
-This app sets some sensible defaults for reducing cold starts, such as `minkeep_warm=1`, which will keep at least 1 warm instance ready for your bot function.
+   ```bash
+   https://{your-workspace}--pipecat-modal-fastapi-app.modal.run
+   ```
 
-It has been configured to only allow a concurrency of 1 (`max_inputs=1`) as each user will require their own running function.
+   You'll need this URL for the client's `app.js` configuration mentioned in its README.
+
+## Launch your bots on Modal
+
+### Option 1: Direct Link
+
+Simply click on the url displayed after running the server or deploy step to launch an agent and be redirected to a Daily room to talk with the launched bot. This will use the OpenAI pipeline.
+
+### Option 2: Connect via an RTVI Client
+
+Follow the instructions provided in the [client folder's README](client/javascript/README.md) for building and running a custom client that connects to your Modal endpoint. The provided client provides a dropdown for choosing which bot pipeline to run.
+
+# Navigating your llm, server, and Pipecat logs
+
+In your [Modal dashboard](https://modal.com/apps), you should have two Apps listed under Live Apps:
+
+1. `example-vllm-openai-compatible`: This App contains the containers and logs used to run your self-hosted LLM. There will be just one App Function listed: `serve`. Click on this function to view logs for your LLM.
+2. `pipecat-modal`: This App contains the containers and logs used to run your `connect` endpoints and Pipecat pipelines. It will list two App Functions:
+    1. `fastapi_app`: This function is running the endpoints that your client will interact with and initiate starting a new pipeline (`/`, `/connect`, `/status`). Click on this function to see logs for each endpoint hit.
+    2. `bot_runner`: This function handles launching and running a bot pipeline. Click on this function to get a list of all pipeline runs and access each run's logs.
+
+# Modal + Pipecat Tips
+
+- In most other Pipecat examples, we use `Popen` to launch the pipeline process from the `/connect` endpoint. In this example, we use a Modal function instead. This allows us to run the pipelines using a separately defined Modal image as well as run each pipeline in an isolated container.
+- For the FastAPI and most common Pipecat Pipeline containers, a default `debian_slim` CPU-only should be all that's required to run. GPU containers are needed for self-hosted services.
+- To minimize cold starts of the pipeline and reduce latency for users, set `min_containers=1` on the Modal Function that launches the pipeline to ensure at least one warm instance of your function is always available.
+- For next steps on running a self-hosted llm and reducing latency, check out all of [Modal's LLM examples](https://modal.com/docs/examples/vllm_inference).

examples/deployment/modal-example/app.py

@@ -1,74 +0,0 @@
-import os
-
-import aiohttp
-import modal
-from bot import _voice_bot_process
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-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"
-)
-
-
-@app.function(
-    image=image,
-    cpu=1.0,
-    secrets=[modal.Secret.from_dotenv()],
-    keep_warm=1,
-    enable_memory_snapshot=True,
-    max_inputs=1,  # Do not reuse instances across requests
-    retries=0,
-)
-def launch_bot_process(room_url: str, token: str):
-    _voice_bot_process(room_url, token)
-
-
-@app.function(
-    image=image,
-    secrets=[modal.Secret.from_dotenv()],
-)
-@modal.web_endpoint(method="POST")
-async def start():
-    from pipecat.transports.services.helpers.daily_rest import (
-        DailyRESTHelper,
-        DailyRoomParams,
-    )
-
-    logger.info("Request received")
-
-    async with aiohttp.ClientSession() as session:
-        daily_rest_helper = DailyRESTHelper(
-            daily_api_key=os.getenv("DAILY_API_KEY", ""),
-            daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-            aiohttp_session=session,
-        )
-
-        # Create new Daily room
-        room = await daily_rest_helper.create_room(DailyRoomParams())
-        if not room.url:
-            raise HTTPException(
-                status_code=500,
-                detail="Unable to create room",
-            )
-        logger.info(f"Created room: {room.url}")
-
-        # Create bot token for room
-        token = await daily_rest_helper.get_token(room.url, MAX_SESSION_TIME)
-        if not token:
-            raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
-
-        logger.info(f"Bot token created: {token}")
-
-        # Spawn a new bot process
-        launch_bot_process.spawn(room_url=room.url, token=token)
-
-        # 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})

examples/deployment/modal-example/bot.py

@@ -1,89 +0,0 @@
-import asyncio
-import os
-import sys
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-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 import CartesiaTTSService
-from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def main(room_url: str, token: str):
-    transport = DailyTransport(
-        room_url,
-        token,
-        "bot",
-        DailyParams(
-            audio_out_enabled=True,
-            transcription_enabled=True,
-            vad_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(),
-        ),
-    )
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY", ""), voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22"
-    )
-
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-
-    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(),
-            context_aggregator.user(),
-            llm,
-            tts,
-            transport.output(),
-            context_aggregator.assistant(),
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
-        ),
-    )
-
-    @transport.event_handler("on_first_participant_joined")
-    async def on_first_participant_joined(transport, participant):
-        await transport.capture_participant_transcription(participant["id"])
-        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_participant_left")
-    async def on_participant_left(transport, participant, reason):
-        await task.cancel()
-
-    runner = PipelineRunner()
-
-    await runner.run(task)
-
-
-def _voice_bot_process(room_url: str, token: str):
-    asyncio.run(main(room_url, token))

examples/deployment/modal-example/client/javascript/.gitignore

@@ -0,0 +1 @@
+node_modules

examples/deployment/modal-example/client/javascript/README.md

@@ -0,0 +1,29 @@
+# JavaScript Implementation
+
+Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
+
+## Setup
+
+1. Deploy the Modal server. See the main [README](../../README).
+
+2. Navigate to the `client/javascript` directory:
+
+```bash
+cd client/javascript
+```
+
+3. Modify the baseUrl in src/app.js to point to your deployed Modal endpoint
+
+4. Install dependencies:
+
+```bash
+npm install
+```
+
+5. Run the client app:
+
+```
+npm run dev
+```
+
+6. Visit http://localhost:5173 in your browser.

examples/deployment/modal-example/client/javascript/index.html

@@ -0,0 +1,49 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>AI Chatbot</title>
+  </head>
+
+  <body>
+    <div class="container">
+      <div class="status-bar">
+        <div class="status">
+          Status: <span id="connection-status">Disconnected</span>
+        </div>
+        <div class="controls">
+          <select id="bot-selector">
+            <option value="openai">OpenAI</option>
+            <option value="gemini">Gemini</option>
+            <option value="vllm">Llama</option>
+          </select>
+          <button id="connect-btn">Connect</button>
+          <button id="disconnect-btn" disabled>Disconnect</button>
+        </div>
+      </div>
+
+      <div class="main-content">
+        <div class="bot-container">
+          <div id="bot-video-container"></div>
+          <audio id="bot-audio" autoplay></audio>
+        </div>
+      </div>
+
+      <div class="device-bar">
+        <div class="device-controls">
+          <select id="device-selector"></select>
+          <button id="mic-toggle-btn">Mute Mic</button>
+        </div>
+      </div>
+
+      <div class="debug-panel">
+        <h3>Debug Info</h3>
+        <div id="debug-log"></div>
+      </div>
+    </div>
+
+    <script type="module" src="/src/app.js"></script>
+    <link rel="stylesheet" href="/src/style.css" />
+  </body>
+</html>

examples/deployment/modal-example/client/javascript/package.json

@@ -0,0 +1,21 @@
+{
+  "name": "client",
+  "version": "1.0.0",
+  "main": "index.js",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "description": "",
+  "devDependencies": {
+    "vite": "^6.3.5"
+  },
+  "dependencies": {
+    "@pipecat-ai/client-js": "^0.3.5",
+    "@pipecat-ai/daily-transport": "^0.3.10"
+  }
+}

examples/deployment/modal-example/client/javascript/src/app.js

@@ -0,0 +1,381 @@
+/**
+ * Copyright (c) 2024–2025, Daily
+ *
+ * SPDX-License-Identifier: BSD 2-Clause License
+ */
+
+/**
+ * RTVI Client Implementation
+ *
+ * This client connects to an RTVI-compatible bot server using WebRTC (via Daily).
+ * It handles audio/video streaming and manages the connection lifecycle.
+ *
+ * Requirements:
+ * - A running RTVI bot server (defaults to http://localhost:7860)
+ * - The server must implement the /connect endpoint that returns Daily.co room credentials
+ * - Browser with WebRTC support
+ */
+
+import { RTVIClient, RTVIEvent } from '@pipecat-ai/client-js';
+import { DailyTransport } from '@pipecat-ai/daily-transport';
+
+/**
+ * ChatbotClient handles the connection and media management for a real-time
+ * voice and video interaction with an AI bot.
+ */
+class ChatbotClient {
+  constructor() {
+    // Initialize client state
+    this.rtviClient = null;
+    this.setupDOMElements();
+    this.initializeClientAndTransport();
+    this.setupEventListeners();
+  }
+
+  /**
+   * Set up references to DOM elements and create necessary media elements
+   */
+  setupDOMElements() {
+    // Get references to UI control elements
+    this.connectBtn = document.getElementById('connect-btn');
+    this.disconnectBtn = document.getElementById('disconnect-btn');
+    this.statusSpan = document.getElementById('connection-status');
+    this.debugLog = document.getElementById('debug-log');
+    this.botVideoContainer = document.getElementById('bot-video-container');
+    this.deviceSelector = document.getElementById('device-selector');
+
+    // Create an audio element for bot's voice output
+    this.botAudio = document.createElement('audio');
+    this.botAudio.autoplay = true;
+    this.botAudio.playsInline = true;
+    document.body.appendChild(this.botAudio);
+  }
+
+  /**
+   * Set up event listeners for connect/disconnect buttons
+   */
+  setupEventListeners() {
+    this.connectBtn.addEventListener('click', () => this.connect());
+    this.disconnectBtn.addEventListener('click', () => this.disconnect());
+
+    // Populate device selector
+    this.rtviClient.getAllMics().then((mics) => {
+      console.log('Available mics:', mics);
+      mics.forEach((device) => {
+        const option = document.createElement('option');
+        option.value = device.deviceId;
+        option.textContent = device.label || `Microphone ${device.deviceId}`;
+        this.deviceSelector.appendChild(option);
+      });
+    });
+    this.deviceSelector.addEventListener('change', (event) => {
+      const selectedDeviceId = event.target.value;
+      console.log('Selected device ID:', selectedDeviceId);
+      this.rtviClient.updateMic(selectedDeviceId);
+    });
+
+    // Handle mic mute/unmute toggle
+    const micToggleBtn = document.getElementById('mic-toggle-btn');
+
+    micToggleBtn.addEventListener('click', () => {
+      let micEnabled = this.rtviClient.isMicEnabled;
+      micToggleBtn.textContent = micEnabled ? 'Unmute Mic' : 'Mute Mic';
+      this.rtviClient.enableMic(!micEnabled);
+      // Add logic to mute/unmute the mic
+      if (micEnabled) {
+        console.log('Mic muted');
+        // Add code to mute the mic
+      } else {
+        console.log('Mic unmuted');
+        // Add code to unmute the mic
+      }
+    });
+  }
+
+  /**
+   * Set up the RTVI client and Daily transport
+   */
+  async initializeClientAndTransport() {
+    // Initialize the RTVI client with a DailyTransport and our configuration
+    this.rtviClient = new RTVIClient({
+      transport: new DailyTransport(),
+      params: {
+        // REPLACE WITH YOUR MODAL URL ENDPOINT
+        baseUrl:
+          'https://<Modal workspace>--pipecat-modal-bot-launcher.modal.run',
+        endpoints: {
+          connect: '/connect',
+        },
+        requestData: {
+          bot_name: 'openai',
+        },
+      },
+      enableMic: true, // Enable microphone for user input
+      enableCam: false,
+      callbacks: {
+        // Handle connection state changes
+        onConnected: () => {
+          this.updateStatus('Connected');
+          this.connectBtn.disabled = true;
+          this.disconnectBtn.disabled = false;
+          this.log('Client connected');
+        },
+        onDisconnected: () => {
+          this.updateStatus('Disconnected');
+          this.connectBtn.disabled = false;
+          this.disconnectBtn.disabled = true;
+          this.log('Client disconnected');
+        },
+        // Handle transport state changes
+        onTransportStateChanged: (state) => {
+          this.updateStatus(`Transport: ${state}`);
+          this.log(`Transport state changed: ${state}`);
+          if (state === 'connecting') {
+            window.startTime = Date.now();
+          }
+          if (state === 'ready') {
+            this.setupMediaTracks();
+            console.warn('TIME TO BOT READY:', Date.now() - window.startTime);
+          }
+        },
+        // Handle bot connection events
+        onBotConnected: (participant) => {
+          this.log(`Bot connected: ${JSON.stringify(participant)}`);
+        },
+        onBotDisconnected: (participant) => {
+          this.log(`Bot disconnected: ${JSON.stringify(participant)}`);
+        },
+        onBotReady: (data) => {
+          this.log(`Bot ready: ${JSON.stringify(data)}`);
+          this.setupMediaTracks();
+        },
+        // Transcript events
+        onUserTranscript: (data) => {
+          // Only log final transcripts
+          if (data.final) {
+            this.log(`User: ${data.text}`);
+          }
+        },
+        onBotTranscript: (data) => {
+          this.log(`Bot: ${data.text}`);
+        },
+        // Error handling
+        onMessageError: (error) => {
+          console.log('Message error:', error);
+        },
+        onMicUpdated: (data) => {
+          console.log('Mic updated:', data);
+          this.deviceSelector.value = data.deviceId;
+        },
+        onError: (error) => {
+          console.log('Error:', JSON.stringify(error));
+        },
+      },
+    });
+
+    // Set up listeners for media track events
+    this.setupTrackListeners();
+
+    await this.rtviClient.initDevices();
+    window.client = this.rtviClient;
+  }
+
+  /**
+   * Add a timestamped message to the debug log
+   */
+  log(message) {
+    const entry = document.createElement('div');
+    entry.textContent = `${new Date().toISOString()} - ${message}`;
+
+    // Add styling based on message type
+    if (message.startsWith('User: ')) {
+      entry.style.color = '#2196F3'; // blue for user
+    } else if (message.startsWith('Bot: ')) {
+      entry.style.color = '#4CAF50'; // green for bot
+    }
+
+    this.debugLog.appendChild(entry);
+    this.debugLog.scrollTop = this.debugLog.scrollHeight;
+    console.log(message);
+  }
+
+  /**
+   * Update the connection status display
+   */
+  updateStatus(status) {
+    this.statusSpan.textContent = status;
+    this.log(`Status: ${status}`);
+  }
+
+  /**
+   * Check for available media tracks and set them up if present
+   * This is called when the bot is ready or when the transport state changes to ready
+   */
+  setupMediaTracks() {
+    if (!this.rtviClient) return;
+
+    // Get current tracks from the client
+    const tracks = this.rtviClient.tracks();
+
+    // Set up any available bot tracks
+    if (tracks.bot?.audio) {
+      this.setupAudioTrack(tracks.bot.audio);
+    }
+    if (tracks.bot?.video) {
+      this.setupVideoTrack(tracks.bot.video);
+    }
+  }
+
+  /**
+   * Set up listeners for track events (start/stop)
+   * This handles new tracks being added during the session
+   */
+  setupTrackListeners() {
+    if (!this.rtviClient) return;
+
+    // Listen for new tracks starting
+    this.rtviClient.on(RTVIEvent.TrackStarted, (track, participant) => {
+      // Only handle non-local (bot) tracks
+      if (!participant?.local) {
+        if (track.kind === 'audio') {
+          this.setupAudioTrack(track);
+        } else if (track.kind === 'video') {
+          this.setupVideoTrack(track);
+        }
+        this.log(
+          `Track started event: ${track.kind} from ${
+            participant?.name || 'unknown'
+          }`
+        );
+      } else {
+        this.log('Local mic unmuted');
+      }
+    });
+
+    // Listen for tracks stopping
+    this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => {
+      if (participant.local) {
+        this.log('Local mic muted');
+        return;
+      }
+      this.log(
+        `Track stopped event: ${track.kind} from ${
+          participant?.name || 'unknown'
+        }`
+      );
+    });
+  }
+
+  /**
+   * Set up an audio track for playback
+   * Handles both initial setup and track updates
+   */
+  setupAudioTrack(track) {
+    this.log('Setting up audio track');
+    // Check if we're already playing this track
+    if (this.botAudio.srcObject) {
+      const oldTrack = this.botAudio.srcObject.getAudioTracks()[0];
+      if (oldTrack?.id === track.id) return;
+    }
+    // Create a new MediaStream with the track and set it as the audio source
+    this.botAudio.srcObject = new MediaStream([track]);
+  }
+
+  /**
+   * Set up a video track for display
+   * Handles both initial setup and track updates
+   */
+  setupVideoTrack(track) {
+    this.log('Setting up video track');
+    const videoEl = document.createElement('video');
+    videoEl.autoplay = true;
+    videoEl.playsInline = true;
+    videoEl.muted = true;
+    videoEl.style.width = '100%';
+    videoEl.style.height = '100%';
+    videoEl.style.objectFit = 'cover';
+
+    // Check if we're already displaying this track
+    if (this.botVideoContainer.querySelector('video')?.srcObject) {
+      const oldTrack = this.botVideoContainer
+        .querySelector('video')
+        .srcObject.getVideoTracks()[0];
+      if (oldTrack?.id === track.id) return;
+    }
+
+    // Create a new MediaStream with the track and set it as the video source
+    videoEl.srcObject = new MediaStream([track]);
+    this.botVideoContainer.innerHTML = '';
+    this.botVideoContainer.appendChild(videoEl);
+  }
+
+  /**
+   * Initialize and connect to the bot
+   * This sets up the RTVI client, initializes devices, and establishes the connection
+   */
+  async connect() {
+    try {
+      const botSelector = document.getElementById('bot-selector');
+      const selectedBot = botSelector.value;
+      this.rtviClient.params.requestData.bot_name = selectedBot;
+
+      // Initialize audio/video devices
+      this.log('Initializing devices...');
+      await this.rtviClient.initDevices();
+
+      // Connect to the bot
+      this.log(`Connecting to bot: ${selectedBot}`);
+      await this.rtviClient.connect();
+
+      this.log('Connection complete');
+    } catch (error) {
+      // Handle any errors during connection
+      console.error('Connection error:', error);
+      this.log(`Error connecting: ${JSON.stringify(error.message)}`);
+      this.log(`Error stack: ${error.stack}`);
+      this.updateStatus('Error');
+
+      // Clean up if there's an error
+      if (this.rtviClient) {
+        try {
+          await this.rtviClient.disconnect();
+        } catch (disconnectError) {
+          this.log(`Error during disconnect: ${disconnectError.message}`);
+        }
+      }
+    }
+  }
+
+  /**
+   * Disconnect from the bot and clean up media resources
+   */
+  async disconnect() {
+    if (this.rtviClient) {
+      try {
+        // Disconnect the RTVI client
+        await this.rtviClient.disconnect();
+
+        // Clean up audio
+        if (this.botAudio.srcObject) {
+          this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
+          this.botAudio.srcObject = null;
+        }
+
+        // Clean up video
+        if (this.botVideoContainer.querySelector('video')?.srcObject) {
+          const video = this.botVideoContainer.querySelector('video');
+          video.srcObject.getTracks().forEach((track) => track.stop());
+          video.srcObject = null;
+        }
+        this.botVideoContainer.innerHTML = '';
+      } catch (error) {
+        this.log(`Error disconnecting: ${error.message}`);
+      }
+    }
+  }
+}
+
+// Initialize the client when the page loads
+window.addEventListener('DOMContentLoaded', () => {
+  new ChatbotClient();
+});

examples/deployment/modal-example/client/javascript/src/style.css

@@ -0,0 +1,135 @@
+body {
+  margin: 0;
+  padding: 20px;
+  font-family: Arial, sans-serif;
+  background-color: #f0f0f0;
+}
+
+.container {
+  max-width: 1200px;
+  margin: 0 auto;
+}
+
+.status-bar,
+.device-bar {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  padding: 10px;
+  background-color: #fff;
+  border-radius: 8px;
+  margin-bottom: 20px;
+}
+
+.controls,
+.device-controls {
+  display: flex;
+  align-items: center;
+  gap: 10px; /* Adds spacing between elements */
+}
+
+.device-controls {
+  margin-left: auto;
+}
+
+.controls button,
+.device-controls button {
+  padding: 8px 16px;
+  margin-left: 10px;
+  border: none;
+  border-radius: 4px;
+  cursor: pointer;
+}
+
+#bot-selector,
+#device-selector {
+  padding: 8px 16px;
+  padding-right: 40px;
+  border: none;
+  border-radius: 4px;
+  background-color: #6c757d; /* Gray background */
+  color: white; /* White text */
+  cursor: pointer;
+  appearance: none; /* Removes default browser styling for dropdowns */
+  background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='white'%3E%3Cpath d='M7 10l5 5 5-5z'/%3E%3C/svg%3E"); /* Custom arrow */
+  background-repeat: no-repeat;
+  background-position: right 8px center; /* Position the arrow */
+}
+
+#bot-selector:focus,
+#device-selector:focus {
+  outline: none;
+  box-shadow: 0 0 4px rgba(0, 0, 0, 0.3); /* Add a subtle focus effect */
+}
+
+#connect-btn {
+  background-color: #4caf50;
+  color: white;
+}
+
+#disconnect-btn {
+  background-color: #f44336;
+  color: white;
+}
+
+#mic-toggle-btn {
+}
+
+button:disabled {
+  opacity: 0.5;
+  cursor: not-allowed;
+}
+
+.main-content {
+  background-color: #fff;
+  border-radius: 8px;
+  padding: 20px;
+  margin-bottom: 20px;
+}
+
+.bot-container {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+}
+
+#bot-video-container {
+  width: 640px;
+  height: 360px;
+  background-color: #e0e0e0;
+  border-radius: 8px;
+  margin: 20px auto;
+  overflow: hidden;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+}
+
+#bot-video-container video {
+  width: 100%;
+  height: 100%;
+  object-fit: cover;
+}
+
+.debug-panel {
+  background-color: #fff;
+  border-radius: 8px;
+  padding: 20px;
+}
+
+.debug-panel h3 {
+  margin: 0 0 10px 0;
+  font-size: 16px;
+  font-weight: bold;
+}
+
+#debug-log {
+  height: 200px;
+  overflow-y: auto;
+  background-color: #f8f8f8;
+  padding: 10px;
+  border-radius: 4px;
+  font-family: monospace;
+  font-size: 12px;
+  line-height: 1.4;
+}

examples/deployment/modal-example/env.example

@@ -1,3 +0,0 @@
-DAILY_API_KEY=
-OPENAI_API_KEY=
-CARTESIA_API_KEY=

examples/deployment/modal-example/requirements.txt

@@ -1,5 +0,0 @@
-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/modal-example/server/app.py

@@ -0,0 +1,307 @@
+"""modal_example.
+
+This module shows a simple example of how to deploy a bot using Modal and FastAPI.
+
+It includes:
+- FastAPI endpoints for starting agents and checking bot statuses.
+- Dynamic loading of bot implementations.
+- Use of a Daily transport for bot communication.
+"""
+
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import importlib
+import os
+from contextlib import asynccontextmanager
+from typing import Any, Dict, Literal
+
+import aiohttp
+import modal
+from fastapi import APIRouter, FastAPI, HTTPException
+from fastapi.responses import JSONResponse, RedirectResponse
+from pydantic import BaseModel
+
+# container specifications for the FastAPI web server
+web_image = (
+    modal.Image.debian_slim(python_version="3.13")
+    .pip_install_from_requirements("requirements.txt")
+    .pip_install("pipecat-ai[daily]")
+    .add_local_dir("src", remote_path="/root/src")
+)
+
+# container specifications for the Pipecat pipeline
+bot_image = (
+    modal.Image.debian_slim(python_version="3.13")
+    .apt_install("ffmpeg")
+    .pip_install_from_requirements("requirements.txt")
+    .pip_install("pipecat-ai[daily,elevenlabs,openai,silero,google]")
+    .add_local_dir("src", remote_path="/root/src")
+)
+
+app = modal.App("pipecat-modal", secrets=[modal.Secret.from_dotenv()])
+
+router = APIRouter()
+
+bot_jobs = {}
+daily_helpers = {}
+
+# Names of all supported bot implementations
+# These correspond to the bot files in the src directory
+BotName = Literal["openai", "gemini", "vllm"]
+
+
+def cleanup():
+    """Cleanup function to terminate all bot processes.
+
+    Called during server shutdown.
+    """
+    for entry in bot_jobs.values():
+        func = modal.FunctionCall.from_id(entry[0])
+        if func:
+            func.cancel()
+
+
+def get_bot_file(bot_name: BotName) -> str:
+    """Retrieve the bot file name corresponding to the provided bot_name.
+
+    Args:
+        bot_name (BotName): The name of the bot (e.g., 'openai', 'gemini', 'vllm').
+
+    Returns:
+        str: The file name corresponding to the bot implementation.
+
+    Raises:
+        ValueError: If the bot name is invalid or not supported.
+    """
+    # bot_implementation = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    bot_implementation = bot_name.lower().strip()
+    if not bot_implementation:
+        bot_implementation = "openai"
+    if bot_implementation not in ["openai", "gemini", "vllm"]:
+        raise ValueError(
+            f"Invalid BOT_IMPLEMENTATION: {bot_implementation}. Must be 'openai' or 'gemini' or 'vllm'"
+        )
+
+    return f"bot_{bot_implementation}"
+
+
+def get_runner(path: str, bot_file: str) -> callable:
+    """Dynamically import the run_bot function based on the bot name.
+
+    Args:
+        path (str): The path to the bot files (e.g., 'src').
+        bot_file (str): The file name of the bot implementation (e.g., 'openai', 'gemini', 'vllm').
+
+    Returns:
+        function: The run_bot function from the specified bot module.
+
+    Raises:
+        ImportError: If the specified bot module or run_bot function is not found.
+    """
+    try:
+        # Dynamically construct the module name
+        module_name = f"{path}.{bot_file}"
+        # Import the module
+        module = importlib.import_module(module_name)
+        # Get the run_bot function from the module
+        return getattr(module, "run_bot")
+    except (ImportError, AttributeError) as e:
+        raise ImportError(f"Failed to import run_bot from {module_name}: {e}")
+
+
+async def create_room_and_token() -> tuple[str, str]:
+    """Create a Daily room and generate an authentication token.
+
+    This function checks for existing room URL and token in the environment variables.
+    If not found, it creates a new room using the Daily API and generates a token for it.
+
+    Returns:
+        tuple[str, str]: A tuple containing the room URL and the authentication token.
+
+    Raises:
+        HTTPException: If room creation or token generation fails.
+    """
+    from pipecat.transports.services.helpers.daily_rest import DailyRoomParams
+
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
+    token = os.getenv("DAILY_SAMPLE_ROOM_TOKEN", None)
+    if not room_url:
+        room = await daily_helpers["rest"].create_room(DailyRoomParams())
+        if not room.url:
+            raise HTTPException(status_code=500, detail="Failed to create room")
+        room_url = room.url
+
+        token = await daily_helpers["rest"].get_token(room_url)
+        if not token:
+            raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room_url}")
+
+    return room_url, token
+
+
+@app.function(image=bot_image, min_containers=1)
+async def bot_runner(room_url, token, bot_name: BotName = "openai"):
+    """Launch the provided bot process, providing the given room URL and token for the bot to join.
+
+    Args:
+        room_url (str): The URL of the Daily room where the bot and client will communicate.
+        token (str): The authentication token for the room.
+        bot_name (BotName): The name of the bot implementation to use. Defaults to "openai".
+
+    Raises:
+        HTTPException: If the bot pipeline fails to start.
+    """
+    try:
+        path = "src"
+        bot_file = get_bot_file(bot_name)
+        run_bot = get_runner(path, bot_file)
+
+        print(f"Starting bot process: {bot_file} -u {room_url} -t {token}")
+        await run_bot(room_url, token)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to start bot pipeline: {e}")
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """FastAPI lifespan manager that handles startup and shutdown tasks.
+
+    - Creates aiohttp session
+    - Initializes Daily API helper
+    - Cleans up resources on shutdown
+    """
+    from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
+
+    aiohttp_session = aiohttp.ClientSession()
+    daily_helpers["rest"] = DailyRESTHelper(
+        daily_api_key=os.getenv("DAILY_API_KEY", ""),
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
+    )
+    yield
+    await aiohttp_session.close()
+    cleanup()
+
+
+class ConnectData(BaseModel):
+    """Data provided by client to specify the bot pipeline.
+
+    Attributes:
+        bot_name (BotName): The name of the bot to connect to. Defaults to "openai".
+    """
+
+    bot_name: BotName = "openai"
+
+
+async def start(data: ConnectData):
+    """Internal method to start a bot agent and return the room URL and token.
+
+    Args:
+        data (ConnectData): The data containing the bot name to use.
+
+    Returns:
+        tuple[str, str]: A tuple containing the room URL and token.
+    """
+    room_url, token = await create_room_and_token()
+    launch_bot_func = modal.Function.from_name("pipecat-modal", "bot_runner")
+    function_id = launch_bot_func.spawn(room_url, token, data.bot_name)
+    bot_jobs[function_id] = (function_id, room_url)
+
+    return room_url, token
+
+
+@router.get("/")
+async def start_agent():
+    """A user endpoint for launching a bot agent and redirecting to the created room URL.
+
+    This function retrieves the bot implementation from the environment,
+    starts the bot agent, and redirects the user to the room URL to
+    interact with the bot through a Daily Prebuilt Interface.
+
+    Returns:
+        RedirectResponse: A response that redirects to the room URL.
+    """
+    bot_name = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    print(f"Starting bot: {bot_name}")
+    room_url, token = await start(ConnectData(bot_name=bot_name))
+
+    return RedirectResponse(room_url)
+
+
+@router.post("/connect")
+async def rtvi_connect(data: ConnectData) -> Dict[Any, Any]:
+    """A user endpoint for launching a bot agent and retrieving the room/token credentials.
+
+    This function retrieves the bot implementation from the request, if provided,
+    starts the bot agent, and returns the room URL and token for the bot. This allows the
+    client to then connect to the bot using their own RTVI interface.
+
+    Args:
+        data (ConnectData): Optional. The data containing the bot name to use.
+
+    Returns:
+        Dict[Any, Any]: A dictionary containing the room URL and token.
+    """
+    print(f"Starting bot: {data.bot_name}")
+    if data is None or not data.bot_name:
+        data.bot_name = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    room_url, token = await start(data)
+
+    return {"room_url": room_url, "token": token}
+
+
+@router.get("/status/{fid}")
+def get_status(fid: str):
+    """Retrieve the status of a bot process by its function ID.
+
+    Args:
+        fid (str): The function ID of the bot process.
+
+    Returns:
+        JSONResponse: A JSON response containing the bot's status and result code.
+
+    Raises:
+        HTTPException: If the bot process with the given ID is not found.
+    """
+    func = modal.FunctionCall.from_id(fid)
+    if not func:
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {fid} not found")
+
+    try:
+        result = func.get(timeout=0)
+        return JSONResponse({"bot_id": fid, "status": "finished", "code": result})
+    except modal.exception.OutputExpiredError:
+        return JSONResponse({"bot_id": fid, "status": "finished", "code": 404})
+    except TimeoutError:
+        return JSONResponse({"bot_id": fid, "status": "running", "code": 202})
+
+
+@app.function(image=web_image, min_containers=1)
+@modal.concurrent(max_inputs=1)
+@modal.asgi_app()
+def fastapi_app():
+    """Create and configure the FastAPI application.
+
+    This function initializes the FastAPI app with middleware, routes, and lifespan management.
+    It is decorated to be used as a Modal ASGI app.
+    """
+    from fastapi.middleware.cors import CORSMiddleware
+
+    # Initialize FastAPI app
+    web_app = FastAPI(lifespan=lifespan)
+
+    web_app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    # Include the endpoints from endpoints.py
+    web_app.include_router(router)
+
+    return web_app

examples/deployment/modal-example/server/env.example

@@ -0,0 +1,14 @@
+DAILY_API_KEY=
+
+# determines which bot file to default to: 'openai', 'gemini', or 'vllm'
+BOT_IMPLEMENTATION=openai
+
+# needed for the openai bot pipeline
+OPENAI_API_KEY=
+ELEVENLABS_API_KEY=
+
+# needed for the gemini live bot pipeline
+GOOGLE_API_KEY=
+
+# needed if you modified the API Key for your self-hosted LLM
+VLLM_API_KEY=

examples/deployment/modal-example/server/requirements.txt

@@ -0,0 +1,2 @@
+python-dotenv==1.0.1
+modal==0.71.3

examples/deployment/modal-example/server/src/bot_gemini.py

@@ -0,0 +1,198 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Gemini Bot Implementation.
+
+This module implements a chatbot using Google's Gemini Multimodal Live model.
+It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Speech-to-speech model
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow using Gemini's streaming capabilities.
+"""
+
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport with specific audio parameters
+    - Gemini Live multimodal model integration
+    - Voice activity detection
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with specific audio/video parameters for Gemini
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_audio_passthrough=True,
+            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+        ),
+    )
+
+    # Initialize the Gemini Multimodal Live model
+    llm = GeminiMultimodalLiveLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        voice_id="Puck",  # Aoede, Charon, Fenrir, Kore, Puck
+        transcribe_user_audio=True,
+    )
+
+    messages = [
+        {
+            "role": "user",
+            "content": "You are Chatbot, a friendly, helpful robot. 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, but keep your responses brief. Start by introducing yourself.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @transport.event_handler("on_participant_left")
+    async def on_participant_left(transport, participant, reason):
+        print(f"Participant left: {participant}")
+        await task.cancel()
+
+    runner = PipelineRunner()
+
+    await runner.run(task)

examples/deployment/modal-example/server/src/bot_openai.py

@@ -0,0 +1,226 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""OpenAI Bot Implementation.
+
+This module implements a chatbot using OpenAI's GPT-4 model for natural language
+processing. It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Text-to-speech using ElevenLabs
+- Support for both English and Spanish
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow.
+"""
+
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+# Load sequential animation frames
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport
+    - Speech-to-text and text-to-speech services
+    - Language model integration
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with video/audio parameters
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            transcription_enabled=True,
+            #
+            # Spanish
+            #
+            # transcription_settings=DailyTranscriptionSettings(
+            #     language="es",
+            #     tier="nova",
+            #     model="2-general"
+            # )
+        ),
+    )
+
+    # Initialize text-to-speech service
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY"),
+        #
+        # English
+        #
+        voice_id="SAz9YHcvj6GT2YYXdXww",
+        #
+        # Spanish
+        #
+        # model="eleven_multilingual_v2",
+        # voice_id="gD1IexrzCvsXPHUuT0s3",
+    )
+
+    # Initialize LLM service
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            #
+            # English
+            #
+            "content": "You are an incessant one-upper. Start by asking the user how their day is going.",
+            #
+            # Spanish
+            #
+            # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            tts,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @transport.event_handler("on_participant_left")
+    async def on_participant_left(transport, participant, reason):
+        print(f"Participant left: {participant}")
+        await task.cancel()
+
+    runner = PipelineRunner()
+
+    await runner.run(task)

examples/deployment/modal-example/server/src/bot_vllm.py

@@ -0,0 +1,239 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""OpenAI Bot Implementation.
+
+This module implements a chatbot using OpenAI's GPT-4 model for natural language
+processing. It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Text-to-speech using ElevenLabs
+- Support for both English and Spanish
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow.
+"""
+
+import os
+import sys
+from typing import List
+
+from dotenv import load_dotenv
+from loguru import logger
+from openai.types.chat import ChatCompletionMessageParam
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+# REPLACE WITH YOUR MODAL URL ENDPOINT
+modal_url = "https://<Modal workspace>--example-vllm-openai-compatible-serve.modal.run"
+api_key = os.getenv("VLLM_API_KEY", "super-secret-key")
+
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+# Load sequential animation frames
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport
+    - Speech-to-text and text-to-speech services
+    - Language model integration
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with video/audio parameters
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            transcription_enabled=True,
+            #
+            # Spanish
+            #
+            # transcription_settings=DailyTranscriptionSettings(
+            #     language="es",
+            #     tier="nova",
+            #     model="2-general"
+            # )
+        ),
+    )
+
+    # Initialize text-to-speech service
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY"),
+        #
+        # English
+        #
+        voice_id="D38z5RcWu1voky8WS1ja",
+        #
+        # Spanish
+        #
+        # model="eleven_multilingual_v2",
+        # voice_id="gD1IexrzCvsXPHUuT0s3",
+    )
+
+    # Initialize LLM service
+    llm = OpenAILLMService(
+        # To use OpenAI
+        api_key=api_key,
+        # Or, to use a local vLLM (or similar) api server
+        model="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w4a16",
+        base_url=f"{modal_url}/v1",
+    )
+
+    messages = [
+        {
+            "role": "system",
+            #
+            # English
+            #
+            "content": "You are a salesman for Modal, the cloud-native serverless Python computing platform.",
+            #
+            # Spanish
+            #
+            # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            tts,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @transport.event_handler("on_participant_left")
+    async def on_participant_left(transport, participant, reason):
+        print(f"Participant left: {participant}")
+        await task.cancel()
+
+    runner = PipelineRunner()
+
+    await runner.run(task)

examples/deployment/modal-example/server/src/runner.py

@@ -0,0 +1,84 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import importlib
+import os
+
+
+def get_bot_file(arg_bot: str | None) -> str:
+    bot_implementation = arg_bot or os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    if not bot_implementation:
+        bot_implementation = "openai"
+    if bot_implementation not in ["openai", "gemini", "vllm"]:
+        raise ValueError(
+            f"Invalid BOT_IMPLEMENTATION: {bot_implementation}. Must be 'openai' or 'gemini'"
+        )
+    return f"bot_{bot_implementation}"
+
+
+def get_runner(bot_file: str):
+    """Dynamically import the run_bot function based on the bot name.
+
+    Args:
+        bot_name (str): The name of the bot implementation (e.g., 'openai', 'gemini').
+
+    Returns:
+        function: The run_bot function from the specified bot module.
+
+    Raises:
+        ImportError: If the specified bot module or run_bot function is not found.
+    """
+    try:
+        # Dynamically construct the module name
+        module_name = f"{bot_file}"
+        # Import the module
+        module = importlib.import_module(module_name)
+        # Get the run_bot function from the module
+        return getattr(module, "run_bot")
+    except (ImportError, AttributeError) as e:
+        raise ImportError(f"Failed to import run_bot from {module_name}: {e}")
+
+
+def main():
+    """Parse the args to launch the appropriate bot using the given room/token."""
+    parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
+    parser.add_argument(
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
+    parser.add_argument(
+        "-t",
+        "--token",
+        type=str,
+        required=False,
+        help="Daily room token",
+    )
+    parser.add_argument(
+        "-b",
+        "--bot",
+        type=str,
+        required=False,
+        help="Bot runner to use (e.g., openai, gemini)",
+    )
+
+    args, unknown = parser.parse_known_args()
+
+    url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
+    token = args.token or os.getenv("DAILY_SAMPLE_ROOM_TOKEN")
+    bot_file = get_bot_file(args.bot)
+
+    if not url:
+        raise Exception(
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
+
+    run_bot = get_runner(bot_file)
+    asyncio.run(run_bot(url, token))
+
+
+if __name__ == "__main__":
+    main()

examples/deployment/pipecat-cloud-daily-pstn-server/README.md

@@ -0,0 +1,200 @@
+# Handling PSTN/SIP Dial-in on Pipecat Cloud
+
+This repository contains two server implementations for handling
+the pinless dial-in workflow in Pipecat Cloud. This is the companion to the
+Pipecat Cloud [pstn_sip starter image](https://github.com/daily-co/pipecat-cloud-images/tree/main/pipecat-starters/pstn_sip).
+In addition you can use `/api/dial` to trigger dial-out, and
+eventually, call-transfers.
+
+1. [FastAPI Server](fastapi-webhook-server/README.md) -
+   A FastAPI implementation that handles PSTN (Public Switched Telephone
+   Network) and SIP (Session Initiation Protocol) calls using the Daily API.
+
+2. [Next.js Serverless](nextjs-webhook-server/README.md) -
+   A Next.js API implementation designed for deployment on Vercel's
+   serverless platform.
+
+Both implementations provide:
+
+- HMAC signature validation for pinless webhook
+- Structured logging
+- Support for dial-in and dial-out settings
+- Voicemail detection and call transfer functionality (coming soon)
+- Test request handling
+
+## Choosing an Implementation
+
+- Use the **FastAPI Server** if you:
+
+  - Need a standalone server
+  - Prefer Python and FastAPI
+  - Want to deploy to traditional hosting platforms
+
+- Use the **Next.js Serverless** implementation if you:
+  - Want serverless deployment
+  - Prefer JavaScript/TypeScript
+  - Already use Next.js and Vercel for other projects
+  - Need quick scaling and zero maintenance
+
+## Prerequisites
+
+### Environment Variables
+
+Both implementations require similar environment variables:
+
+- `PIPECAT_CLOUD_API_KEY`: Pipecat Cloud API Key, begins with pk\_\*
+- `AGENT_NAME`: Your Daily agent name
+- `PINLESS_HMAC_SECRET`: Your HMAC secret for request verification
+- `LOG_LEVEL`: (Optional) Logging level (defaults to 'info')
+
+See the individual README files in each implementation directory for
+specific setup instructions.
+
+### Phone number setup
+
+You can buy a phone number through the Pipecat Cloud Dashboard:
+
+1. Go to `Settings` > `Telephony`
+2. Follow the UI to purchase a phone number
+3. Configure the webhook URL to receive incoming calls (e.g. `https://my-webhook-url.com/api/dial`)
+
+Or purchase the number using Daily's
+[PhoneNumbers API](https://docs.daily.co/reference/rest-api/phone-numbers).
+
+```bash
+curl --request POST \
+--url https://api.daily.co/v1/domain-dialin-config \
+--header 'Authorization: Bearer $TOKEN' \
+--header 'Content-Type: application/json' \
+--data-raw '{
+	"type": "pinless_dialin",
+	"name_prefix": "Customer1",
+    "phone_number": "+1PURCHASED_NUM",
+	"room_creation_api": "https://example.com/api/dial",
+    "hold_music_url": "https://example.com/static/ringtone.mp3",
+	"timeout_config": {
+		"message": "No agent is available right now"
+	}
+}'
+```
+
+The API will return a static SIP URI (`sip_uri`) that can be called
+from other SIP services.
+
+### `room_creation_api`
+
+To make and receive calls currently you have to host a server that
+handles incoming calls. In the coming weeks, incoming calls will be
+directly handled within Daily and we will expose an endpoint similar
+to `{service}/start` that will manage this for you.
+
+In the meantime, the server described below serves as the webhook
+handler for the `room_creation_api`. Configure your pinless phone
+number or SIP interconnect to the `ngrok` tunnel or
+the actual server URL, append `/api/dial` to the webhook URL.
+
+## Example curl commands
+
+Note: Replace `http://localhost:3000` with your actual server URL and
+phone numbers with valid values for your use case.
+
+### Dialin Request
+
+The server will receive a request when a call is received from Daily. 
+The payload that the webhook received is as follows:
+```json
+{
+  // for dial-in from webhook
+  "To": "+14152251493",
+  "From": "+14158483432",
+  "callId": "string-contains-uuid",
+  "callDomain": "string-contains-uuid",
+  "sipHeaders": {
+    "X-My-Custom-Header": "value",
+    "x-caller": "+1234567890",
+    "x-called": "+1987654321", 
+   },
+}
+```
+The `To`, `From`, `callId`, `callDomain` fields are converted to 
+`snake_case` and mapped to `dialin_settings`. In addition, `sipHeader` 
+contains any custom SIP headers received by Daily on the SIP 
+interconnect address (`sip_uri`). These are headers sent from 
+Twilio or other external SIP platforms, for example, to send the 
+caller's phone number.
+
+### Dialout Request
+
+Dial a number, will use any purchased number
+
+```bash
+curl -X POST http://localhost:3000/api/dial \
+  -H "Content-Type: application/json" \
+  -d '{
+    "dialout_settings": [
+      {
+        "phoneNumber": "+1234567890",
+      }
+    ]
+  }'
+```
+
+Dial a number with callerId, which is the UUID of a purchased number.
+
+```bash
+curl -X POST http://localhost:3000/api/dial \
+  -H "Content-Type: application/json" \
+  -d '{
+    "dialout_settings": [
+      {
+        "phoneNumber": "+1234567890",
+        "callerId": "purchased_phone_uuid"
+      }
+    ]
+  }'
+```
+
+Dial a number
+
+```bash
+curl -X POST http://localhost:3000/api/dial \
+  -H "Content-Type: application/json" \
+  -d '{
+    "dialout_settings": [
+      {
+        "phoneNumber": "+1234567890",
+        "callerId": "purchased_phone_uuid"
+      }
+    ]
+  }'
+```
+
+### Advanced Request with Voicemail Detection
+
+```bash
+curl -X POST http://localhost:3000/api/dial \
+  -H "Content-Type: application/json" \
+  -d '{
+    "To": "+1234567890",
+    "From": "+1987654321",
+    "callId": "call-uuid-123",
+    "callDomain": "domain-uuid-456",
+    "sipHeader": {},
+    "dialout_settings": [
+      {
+        "phoneNumber": "+1234567890",
+        "callerId": "purchased_phone_uuid"
+      }
+    ],
+    "voicemail_detection": {
+      "testInPrebuilt": true
+    },
+    "call_transfer": {
+      "mode": "dialout",
+      "speakSummary": true,
+      "storeSummary": true,
+      "operatorNumber": "+1234567890",
+      "testInPrebuilt": true
+    }
+  }'
+```

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

@@ -0,0 +1,98 @@
+# FastAPI server for handling Daily PSTN/SIP Webhook
+
+A FastAPI server that handles PSTN (Public Switched Telephone Network) and SIP (Session Initiation Protocol) calls using the Daily API.
+
+## Setup
+
+1. Clone the repository
+
+2. Navigate to the `fastapi-webhook-server` directory:
+
+   ```bash
+   cd fastapi-webhook-server
+   ```
+
+3. Install dependencies:
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. Copy `env.example` to `.env`:
+
+   ```bash
+   cp env.example .env
+   ```
+
+5. Update `.env` with your credentials:
+
+   - `AGENT_NAME`: Your Daily agent name
+   - `PIPECAT_CLOUD_API_KEY`: Your Daily API key
+   - `PINLESS_HMAC_SECRET`: Your HMAC secret for request verification
+
+## Running the Server
+
+Start the server:
+
+```bash
+python server.py
+```
+
+The server will run on `http://localhost:7860` and you can expose it via ngrok for testing:
+
+```bash
+`ngrok http 7860`
+```
+
+> Tip: Use a subdomain for a consistent URL (e.g. `ngrok http -subdomain=mydomain http://localhost:7860`)
+
+## API Endpoints
+
+### GET /
+
+Health check endpoint that returns a "Hello, World!" message.
+
+### POST /api/dial
+
+Initiates a PSTN/SIP call with the following request body format:
+
+```json
+{
+  "To": "+14152251493",
+  "From": "+14158483432",
+  "callId": "string-contains-uuid",
+  "callDomain": "string-contains-uuid",
+  "dialout_settings": [
+    {
+      "phoneNumber": "+14158483432",
+      "callerId": "+14152251493"
+    }
+  ],
+  "voicemail_detection": {
+    "testInPrebuilt": true
+  },
+  "call_transfer": {
+    "mode": "dialout",
+    "speakSummary": true,
+    "storeSummary": true,
+    "operatorNumber": "+14152250006",
+    "testInPrebuilt": true
+  }
+}
+```
+
+#### Response
+
+Returns a JSON object containing:
+
+- `status`: Success/failure status
+- `data`: Response from Daily API
+- `room_properties`: Properties of the created Daily room
+
+## Error Handling
+
+- 401: Invalid signature
+- 400: Invalid authorization header (e.g. missing Daily API key in bot.py)
+- 405: Method not allowed (e.g. incorrect route on the webhook URL)
+- 500: Server errors (missing API key, network issues)
+- Other status codes are passed through from the Daily API

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

@@ -0,0 +1,3 @@
+AGENT_NAME="your-agent-name"
+PIPECAT_CLOUD_API_KEY="your-daily-api-key"
+PINLESS_HMAC_SECRET="hmac-secret-pinless-dialin"

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

@@ -0,0 +1,6 @@
+fastapi
+uvicorn
+python-dotenv
+requests
+pydantic
+loguru

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

@@ -0,0 +1,216 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+# server.py
+
+
+import base64  # for calculating hmac signature
+import hmac
+import os  # for accessing environment variables
+import time  # for setting expiration time
+from typing import Any, Dict, List, Optional
+
+import requests
+from dotenv import load_dotenv
+from fastapi import FastAPI, HTTPException, Request
+from loguru import logger
+from pydantic import BaseModel, Field
+
+load_dotenv(override=True)
+
+app = FastAPI()
+
+
+class RoomRequest(BaseModel):
+    test: Optional[str] = Field(None, alias="Test", description="Test field")
+    To: Optional[str] = Field(None, alias="to", description="Destination phone number")
+    From: Optional[str] = Field(None, alias="from", description="Source phone number")
+    callId: Optional[str] = Field(None, alias="call_id", description="Unique call identifier")
+    callDomain: Optional[str] = Field(
+        None, alias="call_domain", description="Call domain identifier"
+    )
+    dialout_settings: Optional[List[Dict[str, Any]]] = Field(
+        None, description="An array of phone numbers or SIP URIs to dialout to"
+    )
+    voicemail_detection: Optional[Dict[str, Any]] = Field(
+        None, description="A flag to perform voicemail or answeing-machine detection"
+    )
+    call_transfer: Optional[Dict[str, Any]] = Field(None, description="to initiate a call transfer")
+    sipHeaders: Optional[Dict[str, Any]] = Field(
+        None,
+        alias="sip_headers",
+        description="Custom SIP headers received from the external SIP provider",
+    )
+
+    class Config:
+        populate_by_name = True
+        alias_generator = None
+
+
+"""
+    body can contain any fields, but for handling PSTN/SIP, 
+    we recommend sending the following custom values:
+    dialin, dialout, voicemail detection, and call transfer
+    
+    
+    "To": "+14152251493",
+    "From": "+14158483432",
+    "callId": "string-contains-uuid",
+    "callDomain": "string-contains-uuid"
+    These need to be remapped to dialin_settings
+
+    In addition, we may receive in the body that can be 
+    sent to the bot as a custom field, sip_headers
+    "sipHeaders": {
+        "X-My-Custom-Header": "value",
+        "x-caller": "+14158483432",
+        "x-called": "+14152251493",
+    },
+
+    "dialout_settings": [
+        {"phoneNumber": "+14158483432", "callerId": "+14152251493"}, 
+        {"sipUri": "sip:username@sip.hostname"}
+        ],
+    },
+
+    voicemail_detection:{
+        testInPrebuilt: true
+    },
+
+    "call_transfer": {
+        "mode": "dialout",
+        "speakSummary": true,
+        "storeSummary": true,
+        "operatorNumber": "+14152250006",
+        "testInPrebuilt": true
+    }
+"""
+
+
+@app.get("/")
+async def read_root():
+    return {"message": "Hello, World!"}
+
+
+@app.post("/api/dial")
+async def dial(request: RoomRequest, raw_request: Request):
+    logger.info("Incoming request to /dial:")
+    logger.info(f"Headers: {dict(raw_request.headers)}")
+    raw_body = await raw_request.body()
+    raw_body_str = raw_body.decode()
+    logger.info(f"Raw body: {raw_body_str}")
+    logger.info(f"Parsed body: {request.dict()}")
+
+    # calculate signature and compare/verify
+    hmac_secret = os.getenv("PINLESS_HMAC_SECRET")
+    timestamp = raw_request.headers.get("x-pinless-timestamp")
+    signature = raw_request.headers.get("x-pinless-signature")
+
+    if not hmac_secret:
+        logger.debug("Skipping HMAC validation - PINLESS_HMAC_SECRET not set")
+    elif timestamp and signature:
+        message = timestamp + "." + raw_body_str
+
+        base64_decoded_secret = base64.b64decode(hmac_secret)
+        computed_signature = base64.b64encode(
+            hmac.new(base64_decoded_secret, message.encode(), "sha256").digest()
+        ).decode()
+
+        if computed_signature != signature:
+            logger.error(f"Invalid signature. Expected {signature}, got {computed_signature}")
+            raise HTTPException(status_code=401, detail="Invalid signature")
+    else:
+        logger.debug("Skipping HMAC validation - no signature headers present")
+
+    if request.test == "test":
+        logger.debug("Test request received")
+        return {"status": "success", "message": "Test request received"}
+
+    dialin_settings = None
+    # these fields are camelCase in the request
+    required_fields = ["To", "From", "callId", "callDomain"]
+    if all(
+        field in request.dict() and request.dict()[field] is not None for field in required_fields
+    ):
+        # transform from camelCase to snake_case because daily-python expects snake_case
+        dialin_settings = {
+            "From": request.From,
+            "To": request.To,
+            "call_id": request.callId,
+            "call_domain": request.callDomain,
+            # transform from camelCase to snake_case
+        }
+        logger.debug(f"Populated dialin_settings from request: {dialin_settings}")
+
+    daily_room_properties = {
+        "enable_dialout": request.dialout_settings is not None,
+    }
+
+    if dialin_settings is not None:
+        sip_config = {
+            "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
+
+    # Setting default expiry to 5 minutes from now
+    daily_room_properties["exp"] = int(time.time()) + (5 * 60)
+
+    logger.debug(f"Daily room properties: {daily_room_properties}")
+    payload = {
+        "createDailyRoom": True,
+        "dailyRoomProperties": daily_room_properties,
+        "body": {
+            "dialin_settings": dialin_settings,
+            "dialout_settings": request.dialout_settings,
+            "voicemail_detection": request.voicemail_detection,
+            "call_transfer": request.call_transfer,
+            "sip_headers": request.sipHeaders,  # passing the SIP headers to the bot
+        },
+    }
+
+    pcc_api_key = os.getenv("PIPECAT_CLOUD_API_KEY")
+    agent_name = os.getenv("AGENT_NAME", "my-first-agent")
+
+    if not pcc_api_key:
+        raise HTTPException(status_code=500, detail="DAILY_API_KEY environment variable is not set")
+
+    headers = {"Authorization": f"Bearer {pcc_api_key}", "Content-Type": "application/json"}
+
+    url = f"https://api.pipecat.daily.co/v1/public/{agent_name}/start"
+
+    logger.debug(f"Making API call to Daily: {url} {headers} {payload}")
+
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+        response.raise_for_status()
+        response_data = response.json()
+        logger.debug(f"Response: {response_data}")
+        return {
+            "status": "success",
+            "data": response_data,
+            "room_properties": daily_room_properties,
+        }
+    except requests.exceptions.HTTPError as e:
+        # Pass through the status code and error details from the Daily API
+        status_code = e.response.status_code
+        error_detail = e.response.json() if e.response.content else str(e)
+        logger.error(f"HTTP error: {error_detail}")
+        raise HTTPException(status_code=status_code, detail=error_detail)
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Request error: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+if __name__ == "__main__":
+    try:
+        import uvicorn
+
+        uvicorn.run(app, host="0.0.0.0", port=7860)
+    except KeyboardInterrupt:
+        logger.info("Server stopped manually")