TTSService: pause before processing TTSSpeakFrame

Smallwebrtc memory leak

.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

.github/workflows/android.yaml

@@ -1,48 +0,0 @@
-name: android
-
-on:
-  push:
-    branches:
-      - main
-    paths:
-      - "examples/simple-chatbot/client/android/**"
-  pull_request:
-    branches:
-      - "**"
-    paths:
-      - "examples/simple-chatbot/client/android/**"
-  workflow_dispatch:
-    inputs:
-      sdk_git_ref:
-        type: string
-        description: "Which git ref of the app to build"
-
-concurrency:
-  group: build-android-${{ github.event.pull_request.number || github.ref }}
-  cancel-in-progress: true
-
-jobs:
-  sdk:
-    name: "Simple chatbot demo"
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repo
-        uses: actions/checkout@v4
-        with:
-          ref: ${{ github.event.inputs.sdk_git_ref || github.ref }}
-
-      - name: "Install Java"
-        uses: actions/setup-java@v4
-        with:
-          distribution: 'temurin'
-          java-version: '17'
-
-      - name: Build demo app
-        working-directory: examples/simple-chatbot/client/android
-        run: ./gradlew :simple-chatbot-client:assembleDebug
-
-      - name: Upload demo APK
-        uses: actions/upload-artifact@v4
-        with:
-          name: Simple Chatbot Android Client
-          path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk

.github/workflows/build.yaml

@@ -21,24 +21,20 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      
+      - name: Set up Python
+        run: uv python install 3.10
+      
+      - name: Install development dependencies
+        run: uv sync --group dev
+      
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
-      - name: Install project and other Python dependencies
-        run: |
-          source .venv/bin/activate
-          pip install --editable .
+        run: uv build
+      
+      - name: Install project in editable mode
+        run: uv pip install --editable .

.github/workflows/coverage.yaml

@@ -18,35 +18,28 @@ jobs:
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
       - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
-        with:
-          python-version: "3.10"
-      - name: Cache virtual environment
-        uses: actions/cache@v3
-        with:
-          # We are hashing dev-requirements.txt and test-requirements.txt which
-          # contain all dependencies needed to run the tests.
-          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
-          path: .venv
+        run: uv python install 3.12
+
       - name: Install system packages
-        id: install_system_packages
         run: |
           sudo apt-get install -y portaudio19-dev
-      - name: Setup virtual environment
+
+      - name: Install dependencies
         run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt -r test-requirements.txt
+          uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
+
       - name: Run tests with coverage
         run: |
-          source .venv/bin/activate
-          coverage run
-          coverage xml
+          uv run coverage run
+          uv run coverage xml
+
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v5
         with:

.github/workflows/format.yaml

@@ -17,30 +17,27 @@ concurrency:
 
 jobs:
   ruff-format:
-    name: "Formatting checker"
+    name: "Code quality checks"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: "3.10"
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install development Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      
+      - name: Set up Python
+        run: uv python install 3.10
+      
+      - name: Install development dependencies
+        run: uv sync --group dev
+      
       - name: Ruff formatter
         id: ruff-format
-        run: |
-          source .venv/bin/activate
-          ruff format --diff
-      - name: Ruff import linter
+        run: uv run ruff format --diff
+      
+      - name: Ruff linter (all rules)
         id: ruff-check
-        run: |
-          source .venv/bin/activate
-          ruff check --select I
+        run: uv run ruff check

.github/workflows/publish.yaml

@@ -5,7 +5,7 @@ on:
     inputs:
       gitref:
         type: string
-        description: "what git ref to build"
+        description: "what git tag to build (e.g. v0.0.74)"
         required: true
 
 jobs:
@@ -17,23 +17,17 @@ jobs:
         uses: actions/checkout@v4
         with:
           ref: ${{ github.event.inputs.gitref }}
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      - name: Set up Python
+        run: uv python install 3.10
+      - name: Install development dependencies
+        run: uv sync --group dev
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
+        run: uv build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:

.github/workflows/publish_test.yaml

@@ -12,23 +12,16 @@ jobs:
         with:
           fetch-tags: true
           fetch-depth: 100
-      - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
         with:
-          python-version: '3.10'
-      - name: Setup virtual environment
-        run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          version: "latest"
+      - name: Set up Python
+        run: uv python install 3.10
+      - name: Install development dependencies
+        run: uv sync --group dev
       - name: Build project
-        run: |
-          source .venv/bin/activate
-          python -m build
+        run: uv build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:
@@ -38,7 +31,7 @@ jobs:
   publish-to-test-pypi:
     name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
-    needs: [ build ]
+    needs: [build]
     environment:
       name: testpypi
       url: https://pypi.org/p/pipecat-ai

.github/workflows/python-compatibility.yaml

@@ -0,0 +1,61 @@
+name: Python Compatibility Test
+
+on:
+  push:
+    branches: [main, develop]
+    paths: ['pyproject.toml']
+  pull_request:
+    branches: [main, develop]
+    paths: ['pyproject.toml']
+
+jobs:
+  test-compatibility:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5']
+
+    name: Python ${{ matrix.python-version }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install system dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y \
+            portaudio19-dev \
+            libcairo2-dev \
+            libgirepository1.0-dev \
+            pkg-config
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+        with:
+          version: 'latest'
+
+      - name: Set up Python ${{ matrix.python-version }}
+        run: |
+          uv python install ${{ matrix.python-version }}
+          uv python pin ${{ matrix.python-version }}
+
+      - name: Test uv sync with all extras (Python < 3.13)
+        if: "!startsWith(matrix.python-version, '3.13.')"
+        run: |
+          uv sync --group dev --all-extras --no-extra krisp
+
+      - name: Test uv sync without PyTorch extras (Python 3.13+)
+        if: startsWith(matrix.python-version, '3.13.')
+        run: |
+          uv sync --group dev --all-extras \
+            --no-extra krisp \
+            --no-extra ultravox \
+            --no-extra local-smart-turn \
+            --no-extra moondream \
+            --no-extra mlx-whisper
+
+      - name: Verify installation
+        run: |
+          uv run python --version
+          uv run python -c "import pipecat; print('✅ Pipecat imports successfully')"

.github/workflows/sync-quickstart.yaml

@@ -0,0 +1,51 @@
+name: Sync Quickstart to pipecat-quickstart repo
+
+on:
+  push:
+    branches: [main]
+    paths:
+      - 'examples/quickstart/**'
+  workflow_dispatch: # Manual trigger
+
+jobs:
+  sync-quickstart:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout main repo
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Checkout quickstart repo
+        uses: actions/checkout@v4
+        with:
+          repository: pipecat-ai/pipecat-quickstart
+          token: ${{ secrets.QUICKSTART_SYNC_TOKEN }}
+          path: quickstart-repo
+
+      - name: Sync files (excluding uv.lock and README.md)
+        run: |
+          # Copy all files except uv.lock and README.md
+          find examples/quickstart -type f \
+            -not -name "README.md" \
+            -not -name "uv.lock" \
+            -exec cp {} quickstart-repo/ \;
+
+      - name: Commit and push changes
+        run: |
+          cd quickstart-repo
+          git config user.name "GitHub Action"
+          git config user.email "action@github.com"
+          git add .
+
+          # Only commit if there are changes
+          if ! git diff --staged --quiet; then
+            git commit -m "Sync from pipecat main repo
+            
+            Updated files from examples/quickstart/
+            Commit: ${{ github.sha }}
+            "
+            git push
+          else
+            echo "No changes to sync"
+          fi

.github/workflows/tests.yaml

@@ -22,31 +22,23 @@ jobs:
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
       - name: Set up Python
-        id: setup_python
-        uses: actions/setup-python@v4
-        with:
-          python-version: "3.10"
-      - name: Cache virtual environment
-        uses: actions/cache@v3
-        with:
-          # We are hashing dev-requirements.txt and test-requirements.txt which
-          # contain all dependencies needed to run the tests.
-          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
-          path: .venv
+        run: uv python install 3.12
+
       - name: Install system packages
-        id: install_system_packages
         run: |
           sudo apt-get install -y portaudio19-dev
-      - name: Setup virtual environment
+
+      - name: Install dependencies
         run: |
-          python -m venv .venv
-      - name: Install basic Python dependencies
-        run: |
-          source .venv/bin/activate
-          python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt -r test-requirements.txt
+          uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
+
       - name: Test with pytest
         run: |
-          source .venv/bin/activate
-          pytest
+          uv run pytest

.gitignore

@@ -7,7 +7,7 @@ venv
 /.idea
 #*#
 
-# Distribution / packaging
+# Distribution / Packaging
 .Python
 build/
 develop-eggs/
@@ -30,9 +30,25 @@ MANIFEST
 .env
 fly.toml
 
-# Example files
-pipecat/examples/twilio-chatbot/templates/streams.xml
+# Examples
+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
+docs/api/api
+
+# uv
+.python-version

.pre-commit-config.yaml

@@ -1,7 +1,8 @@
 repos:
-  - repo: local
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.12.1
     hooks:
-      - id: ruff-format-hook
-        name: Check ruff formatting
-        entry: sh scripts/pre-commit.sh
-        language: system
+      - id: ruff
+        language_version: python3
+        args: [--fix]
+      - id: ruff-format

.readthedocs.yaml

@@ -9,22 +9,14 @@ build:
     - python3-dev
     - libasound2-dev
   jobs:
-    pre_build:
-      - python -m pip install --upgrade pip
-      - pip install wheel setuptools
-    post_build:
-      - echo "Build completed"
+    post_install:
+      - pip install uv
+      - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
 
 sphinx:
   configuration: docs/api/conf.py
   fail_on_warning: false
 
-python:
-  install:
-    - requirements: docs/api/requirements.txt
-    - method: pip
-      path: .
-
 search:
   ranking:
     api/*: 5

CONTRIBUTING.md

@@ -26,11 +26,183 @@ 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!
 
+## Dependency Management
+
+This project uses [uv](https://docs.astral.sh/uv/) for dependency management. The `uv.lock` file is committed to ensure reproducible builds.
+
+### Adding or Updating Dependencies
+
+1. Edit `pyproject.toml` to add/update dependencies
+2. Run `uv lock` to update the lockfile with new dependency resolution
+3. Run `uv sync` to install the updated dependencies locally
+4. Always commit both files together:
+   ```bash
+   git add pyproject.toml uv.lock
+   git commit -m "feat: add new dependency for feature X"
+   ```
+
+**Important:** Never manually edit `uv.lock`. It's auto-generated by `uv lock`.
+
+## 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:
+
+**Regular Classes:**
+
+- Class docstring describes the class purpose and key functionality
+- `__init__` method has its own docstring with complete `Args:` section documenting all parameters
+- All public methods must have docstrings with `Args:` and `Returns:` sections as appropriate
+
+**Dataclasses:**
+
+- Class docstring describes the purpose and documents all fields in a `Parameters:` section
+- No `__init__` docstring (auto-generated)
+
+**Properties:**
+
+- Must have docstrings with `Returns:` section
+
+**Abstract Methods:**
+
+- Must have docstrings explaining what subclasses should implement
+
+**`__init__.py` Files:**
+
+- **Skip docstrings** for pure import/re-export modules
+- **Add brief docstrings** for top-level packages or those with initialization logic
+
+**Enums:**
+
+- Class docstring describes the enumeration purpose
+- Use `Parameters:` section to document each enum value and its meaning
+- No `__init__` docstring (Enums don't have custom constructors)
+
+**Code Examples in Docstrings:**
+
+- Use `Examples:` as a section header for multiple examples
+- Use descriptive text followed by double colons (`::`) for each example
+- **Always include a blank line after the `::"`**
+- Indent all code consistently within each block
+- Separate multiple examples with blank lines for readability
+
+**Lists and Bullets in Docstrings:**
+
+- Use dashes (`-`) for bullet points, not asterisks (`*`)
+- **Add a blank line before bullet lists** when they follow a colon
+- Use section headers like "Supported features:" or "Behavior:" before lists
+- For complex nested information, consider using paragraph format instead
+
+**Deprecations:**
+
+- Use `warnings.warn()` in code for runtime deprecation warnings
+- Add `.. deprecated::` directive in docstrings for documentation visibility
+- Include version information and describe current status
+- Describe parameters in present tense, use directive to indicate deprecation status
+
+#### Examples:
+
+```python
+# Regular class
+class MyService(BaseService):
+    """Description of what the service does.
+
+    Provides detailed explanation of the service's functionality,
+    key features, and usage patterns.
+
+    Supported features:
+
+    - Feature one with detailed explanation
+    - Feature two with additional context
+    - Feature three for advanced use cases
+    """
+
+    def __init__(self, param1: str, old_param: str = None, **kwargs):
+        """Initialize the service.
+
+        Args:
+            param1: Description of param1.
+            old_param: Controls legacy behavior.
+
+                .. deprecated:: 1.2.0
+                    This parameter no longer has any effect and will be removed in version 2.0.
+
+            **kwargs: Additional arguments passed to parent.
+        """
+        if old_param is not None:
+            import warnings
+            warnings.warn(
+                "Parameter 'old_param' is deprecated and will be removed in version 2.0.",
+                DeprecationWarning,
+            )
+        super().__init__(**kwargs)
+
+    @property
+    def sample_rate(self) -> int:
+        """Get the current sample rate.
+
+        Returns:
+            The sample rate in Hz.
+        """
+        return self._sample_rate
+
+    async def process_data(self, data: str) -> bool:
+        """Process the provided data.
+
+        Args:
+            data: The data to process.
+
+        Returns:
+            True if processing succeeded.
+        """
+        pass
+
+# Dataclass with code examples
+@dataclass
+class MessageFrame:
+    """Frame containing messages in OpenAI format.
+
+    Supports both simple and content list message formats.
+
+    Example::
+
+        [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there!"}
+        ]
+
+    Parameters:
+        messages: List of messages in OpenAI format.
+    """
+
+    messages: List[dict]
+
+# Enum class
+class Status(Enum):
+    """Status codes for processing operations.
+
+    Parameters:
+        PENDING: Operation is queued but not started.
+        RUNNING: Operation is currently in progress.
+        COMPLETED: Operation finished successfully.
+        FAILED: Operation encountered an error.
+    """
+
+    PENDING = "pending"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    FAILED = "failed"
+```
 
 # Contributor Covenant Code of Conduct
 
@@ -51,23 +223,23 @@ 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 +334,4 @@ 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

Dockerfile

@@ -1,40 +0,0 @@
-# setup
-FROM python:3.11.5
-
-WORKDIR /app
-COPY requirements.txt /app
-COPY *.py /app
-COPY pyproject.toml /app
-
-COPY src/ /app/src/
-COPY examples/ /app/examples/
-
-WORKDIR /app
-RUN ls --recursive /app/
-RUN pip3 install --upgrade -r requirements.txt
-RUN python -m build .
-RUN pip3 install .
-RUN pip3 install gunicorn
-# If running on Ubuntu, Azure TTS requires some extra config
-# https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform?pivots=programming-language-python&tabs=linux%2Cubuntu%2Cdotnetcli%2Cdotnet%2Cjre%2Cmaven%2Cnodejs%2Cmac%2Cpypi
-
-RUN wget -O - https://www.openssl.org/source/openssl-1.1.1w.tar.gz | tar zxf -
-WORKDIR openssl-1.1.1w
-RUN ./config --prefix=/usr/local
-RUN make -j $(nproc)
-RUN make install_sw install_ssldirs
-RUN ldconfig -v
-ENV SSL_CERT_DIR=/etc/ssl/certs
-
-#ENV LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
-RUN apt clean
-RUN apt-get update
-RUN apt-get -y install build-essential libssl-dev ca-certificates libasound2 wget
-
-ENV PYTHONUNBUFFERED=1
-
-WORKDIR /app
-
-EXPOSE 8000
-# run
-CMD ["gunicorn", "--workers=2", "--log-level", "debug", "--chdir", "examples/server", "--capture-output", "daily-bot-manager:app", "--bind=0.0.0.0:8000"]

MANIFEST.in

@@ -0,0 +1,4 @@
+prune docs
+prune examples
+prune scripts
+prune tests

README.md

@@ -1,206 +1,194 @@
 <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
+> Want to dive right in? Try the [quickstart](https://docs.pipecat.ai/getting-started/quickstart).
 
-## See it in action
+## 🚀 What You Can Build
+
+- **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.
+
+🔍 Looking for help debugging your pipeline and processors? Check out [Whisker](https://github.com/pipecat-ai/whisker), a real-time Pipecat debugger.
+
+## 🧠 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)
+
+## 📱 Client SDKs
+
+You can connect to Pipecat from any platform using our official SDKs:
+
+<table>
+  <tr>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/javascript/javascript-original.svg" width="40" height="40" alt="JavaScript"/>
+      <a href="https://docs.pipecat.ai/client/js/introduction">JavaScript</a>
+    </td>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/react/react-original.svg" width="40" height="40" alt="React"/>
+      <a href="https://docs.pipecat.ai/client/react/introduction">React</a>
+    </td>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/react/react-original.svg" width="40" height="40" alt="React Native"/>
+      <a href="https://docs.pipecat.ai/client/react-native/introduction">React Native</a>
+    </td>
+  </tr>
+  <tr>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/swift/swift-original.svg" width="40" height="40" alt="Swift"/>
+      <a href="https://docs.pipecat.ai/client/ios/introduction">Swift</a>
+    </td>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/kotlin/kotlin-original.svg" width="40" height="40" alt="Kotlin"/>
+      <a href="https://docs.pipecat.ai/client/android/introduction">Kotlin</a>
+    </td>
+    <td>
+      <img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/cplusplus/cplusplus-original.svg" width="40" height="40" alt="JavaScript"/>
+      <a href="https://docs.pipecat.ai/client/c++/introduction">C++</a>
+    </td>
+  </tr>
+</table>
+
+## 🎬 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-examples/tree/main/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/simple-chatbot/image.png" width="400" /></a>&nbsp;
+    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/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-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>&nbsp;
+    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/moondream-chatbot/image.png" width="400" /></a>
 </p>
 
-## Key features
+## 🧩 Available services
 
-- **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
-
-💡 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
-
-## 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. You can also add a 📞 telephone number, 🖼️ image output, 📺 video input, use different LLMs, and more.
-
-```shell
-# Install the module
-pip install pipecat-ai
-
-# Set up your environment
-cp dot-env.template .env
-```
-
-To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
-
-```shell
-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]"`   |
+| 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), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [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), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [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), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                                                          |
+| Text-to-Speech      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [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), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| Serializers         | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+| Video               | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [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), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
 
 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
 
-## Code examples
+## ⚡ 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.
+
+1. Install uv
+
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   ```
+
+   > **Need help?** Refer to the [uv install documentation](https://docs.astral.sh/uv/getting-started/installation/).
+
+2. Install the module
+
+   ```bash
+   # For new projects
+   uv init my-pipecat-app
+   cd my-pipecat-app
+   uv add pipecat-ai
+
+   # Or for existing projects
+   uv add pipecat-ai
+   ```
+
+3. Set up your environment
+
+   ```bash
+   cp env.example .env
+   ```
+
+4. To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
+
+   ```bash
+   uv add "pipecat-ai[option,...]"
+   ```
+
+> **Using pip?** You can still use `pip install pipecat-ai` and `pip install "pipecat-ai[option,...]"` to get set up.
+
+## 🧪 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
+- [Example apps](https://github.com/pipecat-ai/pipecat-examples) — complete applications that you can use as starting points for development
 
-## A simple voice agent running locally
+## 🛠️ Contributing to the framework
 
-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.
+### Prerequisites
 
-```python
-import asyncio
+**Minimum Python Version:** 3.10
+**Recommended Python Version:** 3.12
 
-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
+### Setup Steps
 
-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))
+1. Clone the repository and navigate to it:
 
-  # Use Cartesia for Text-to-Speech
-  tts = CartesiaTTSService(
-    api_key=...,
-    voice_id=...
-  )
+   ```bash
+   git clone https://github.com/pipecat-ai/pipecat.git
+   cd pipecat
+   ```
 
-  # Simple pipeline that will process text to speech and output the result
-  pipeline = Pipeline([tts, transport.output()])
+2. Install development and testing dependencies:
 
-  # Create Pipecat processor that can run one or more pipelines tasks
-  runner = PipelineRunner()
+   ```bash
+   uv sync --group dev --all-extras \
+     --no-extra gstreamer \
+     --no-extra krisp \
+     --no-extra local \
+     --no-extra ultravox # (ultravox not fully supported on macOS)
+   ```
 
-  # Assign the task callable to run the pipeline
-  task = PipelineTask(pipeline)
+3. Install the git pre-commit hooks:
 
-  # 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}!"))
+   ```bash
+   uv run pre-commit install
+   ```
 
-  # 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()
-
-  # Run the pipeline task
-  await runner.run(task)
-
-if __name__ == "__main__":
-  asyncio.run(main())
-```
-
-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,...]"
-```
+> **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
 
 ### Running tests
 
-From the root directory, run:
+To run all tests, from the root directory:
 
-```shell
-pytest
+```bash
+uv run pytest
 ```
 
-## Setting up your editor
+Run a specific test suite:
+
+```bash
+uv run pytest tests/test_name.py
+```
+
+### 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 +210,7 @@ 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 +222,7 @@ 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 +232,7 @@ 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 +245,7 @@ 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

@@ -1,12 +0,0 @@
-build~=1.2.2
-coverage~=7.6.12
-grpcio-tools~=1.67.1
-pip-tools~=7.4.1
-pre-commit~=4.0.1
-pyright~=1.1.393
-pytest~=8.3.4
-pytest-asyncio~=0.25.2
-ruff~=0.9.5
-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/README.md

@@ -1,10 +0,0 @@
-# Pipecat Docs
-
-## [Architecture Overview](architecture.md)
-
-Learn about the thinking behind the framework's design.
-
-## [A Frame's Progress](frame-progress.md)
-
-See how a Frame is processed through a Transport, a Pipeline, and a series of Frame Processors.
-

docs/api/build-docs.sh

@@ -1,10 +1,27 @@
 #!/bin/bash
 
+# Build docs using uv
+echo "Installing dependencies with uv..."
+uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
+
+# Check if sphinx-build is available
+if ! uv run sphinx-build --version &> /dev/null; then
+    echo "Error: sphinx-build is not available" >&2
+    exit 1
+fi
+
 # Clean previous build
 rm -rf _build
 
+echo "Building documentation..."
 # Build docs matching ReadTheDocs configuration
-sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
+uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
 
-# Open docs (MacOS)
-open _build/html/index.html
+if [ $? -eq 0 ]; then
+    echo "Documentation built successfully!"
+    # Open docs (MacOS)
+    open _build/html/index.html
+else
+    echo "Documentation build failed!" >&2
+    exit 1
+fi

docs/api/conf.py

@@ -1,5 +1,7 @@
 import logging
+import os
 import sys
+from datetime import datetime
 from pathlib import Path
 
 # Configure logging
@@ -13,7 +15,8 @@ sys.path.insert(0, str(project_root / "src"))
 
 # Project information
 project = "pipecat-ai"
-copyright = "2024, Daily"
+current_year = datetime.now().year
+copyright = f"2024-{current_year}, Daily" if current_year > 2024 else "2024, Daily"
 author = "Daily"
 
 # General configuration
@@ -24,122 +27,108 @@ extensions = [
     "sphinx.ext.intersphinx",
 ]
 
+suppress_warnings = [
+    "autodoc.mocked_object",
+    "toc.not_included",
+]
+
 # Napoleon settings
 napoleon_google_docstring = True
-napoleon_numpy_docstring = False
 napoleon_include_init_with_doc = True
 
 # AutoDoc settings
 autodoc_default_options = {
     "members": True,
     "member-order": "bysource",
-    "special-members": "__init__",
-    "undoc-members": True,
-    "exclude-members": "__weakref__",
-    "no-index": True,
+    "undoc-members": False,
+    "exclude-members": "__weakref__,model_config",
     "show-inheritance": True,
 }
 
 # Mock imports for optional dependencies
 autodoc_mock_imports = [
-    "riva",
-    "livekit",
-    "pyht",  # Base PlayHT package
-    "pyht.async_client",  # PlayHT specific imports
-    "pyht.client",
-    "pyht.protos",
-    "pyht.protos.api_pb2",
-    "pipecat_ai_playht",  # PlayHT wrapper
-    "anthropic",
-    "assemblyai",
-    "boto3",
-    "azure",
-    "cartesia",
-    "deepgram",
-    "elevenlabs",
-    "fal",
-    "gladia",
-    "google",
-    "krisp",
-    "langchain",
-    "lmnt",
-    "noisereduce",
-    "openai",
-    "openpipe",
-    "simli",
-    "soundfile",
-    # Existing mocks
+    # Krisp - has build issues on some platforms
     "pipecat_ai_krisp",
-    "pyaudio",
+    "krisp",
+    # System-specific GUI libraries
     "_tkinter",
     "tkinter",
-    "daily",
-    "daily_python",
-    "pydantic.BaseModel",
-    "pydantic.Field",
-    "pydantic._internal._model_construction",
-    "pydantic._internal._fields",
+    # Platform-specific audio libraries (if needed)
+    "gi",
+    "gi.require_version",
+    "gi.repository",
+    # OpenCV - sometimes has import issues during docs build
+    "cv2",
+    # Heavy ML packages excluded from ReadTheDocs
+    # ultravox dependencies
+    "vllm",
+    "vllm.engine.arg_utils",
+    # local-smart-turn dependencies
+    "coremltools",
+    "coremltools.models",
+    "coremltools.models.MLModel",
+    "torch",
+    "torch.nn",
+    "torch.nn.functional",
+    "torchaudio",
+    # moondream dependencies
+    "transformers",
+    "transformers.AutoTokenizer",
+    "transformers.AutoFeatureExtractor",
+    "AutoFeatureExtractor",
+    "timm",
+    "einops",
+    "intel_extension_for_pytorch",
+    "huggingface_hub",
+    # 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",
+    # MLX dependencies (Apple Silicon specific)
+    "mlx",
+    "mlx_whisper",  # Note: might need underscore format too
 ]
 
 # HTML output settings
 html_theme = "sphinx_rtd_theme"
-html_static_path = ["_static"]
-autodoc_typehints = "description"
+html_static_path = ["_static"] if os.path.exists("_static") else []
+autodoc_typehints = "signature"  # Show type hints in the signature only, not in the docstring
 html_show_sphinx = False
 
 
-def verify_modules():
-    """Verify that required modules are available."""
-    required_modules = {
-        "services": [
-            "assemblyai",
-            "aws",
-            "cartesia",
-            "deepgram",
-            "google",
-            "lmnt",
-            "riva",
-            "simli",
-        ],
-        "serializers": ["livekit"],
-        "vad": ["silero", "vad_analyzer"],
-        "transports": {
-            "services": ["daily", "livekit"],
-            "local": ["audio", "tk"],
-            "network": ["fastapi_websocket", "websocket_server"],
-        },
-    }
+def import_core_modules():
+    """Import core pipecat modules for autodoc to discover."""
+    core_modules = [
+        "pipecat",
+        "pipecat.frames",
+        "pipecat.pipeline",
+        "pipecat.processors",
+        "pipecat.services",
+        "pipecat.transports",
+        "pipecat.audio",
+        "pipecat.adapters",
+        "pipecat.clocks",
+        "pipecat.metrics",
+        "pipecat.observers",
+        "pipecat.runner",
+        "pipecat.serializers",
+        "pipecat.sync",
+        "pipecat.transcriptions",
+        "pipecat.utils",
+    ]
 
-    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:
-                    try:
-                        __import__(f"pipecat.{category}.{subcategory}.{module}")
-                        logger.info(
-                            f"Successfully imported pipecat.{category}.{subcategory}.{module}"
-                        )
-                    except (ImportError, TypeError, NameError) as e:
-                        missing.append(f"pipecat.{category}.{subcategory}.{module}")
-                        logger.warning(
-                            f"Optional module not available: pipecat.{category}.{subcategory}.{module} - {str(e)}"
-                        )
-        else:
-            # Handle flat structure
-            for module in modules:
-                try:
-                    __import__(f"pipecat.{category}.{module}")
-                    logger.info(f"Successfully imported pipecat.{category}.{module}")
-                except (ImportError, TypeError, NameError) as e:
-                    missing.append(f"pipecat.{category}.{module}")
-                    logger.warning(
-                        f"Optional module not available: pipecat.{category}.{module} - {str(e)}"
-                    )
-
-    if missing:
-        logger.warning(f"Some optional modules are not available: {missing}")
+    for module_name in core_modules:
+        try:
+            __import__(module_name)
+            logger.info(f"Successfully imported {module_name}")
+        except ImportError as e:
+            logger.warning(f"Failed to import {module_name}: {e}")
 
 
 def clean_title(title: str) -> str:
@@ -151,36 +140,7 @@ def clean_title(title: str) -> str:
     parts = title.split(".")
     title = parts[-1]
 
-    # Special cases for service names and common acronyms
-    special_cases = {
-        "ai": "AI",
-        "aws": "AWS",
-        "api": "API",
-        "vad": "VAD",
-        "assemblyai": "AssemblyAI",
-        "deepgram": "Deepgram",
-        "elevenlabs": "ElevenLabs",
-        "openai": "OpenAI",
-        "openpipe": "OpenPipe",
-        "playht": "PlayHT",
-        "xtts": "XTTS",
-        "lmnt": "LMNT",
-    }
-
-    # Check if the entire title is a special case
-    if title.lower() in special_cases:
-        return special_cases[title.lower()]
-
-    # Otherwise, capitalize each word
-    words = title.split("_")
-    cleaned_words = []
-    for word in words:
-        if word.lower() in special_cases:
-            cleaned_words.append(special_cases[word.lower()])
-        else:
-            cleaned_words.append(word.capitalize())
-
-    return " ".join(cleaned_words)
+    return title
 
 
 def setup(app):
@@ -205,9 +165,8 @@ def setup(app):
 
     excludes = [
         str(project_root / "src/pipecat/pipeline/to_be_updated"),
-        str(project_root / "src/pipecat/processors/gstreamer"),
-        str(project_root / "src/pipecat/services/to_be_updated"),
-        str(project_root / "src/pipecat/vad"),  # deprecated
+        str(project_root / "src/pipecat/examples"),
+        str(project_root / "src/pipecat/tests"),
         "**/test_*.py",
         "**/tests/*.py",
     ]
@@ -248,5 +207,4 @@ def setup(app):
         logger.error(f"Error generating API documentation: {e}", exc_info=True)
 
 
-# Run module verification
-verify_modules()
+import_core_modules()

docs/api/index.rst

@@ -1,77 +1,36 @@
-Pipecat API Reference Docs
-==========================
+Pipecat API Reference
+=====================
 
-Welcome to Pipecat's API reference documentation!
+Welcome to the Pipecat API reference.
 
-Pipecat is an open source framework for building voice and multimodal assistants.
-It provides a flexible pipeline architecture for connecting various AI services,
-audio processing, and transport layers.
+Use the navigation on the left to browse modules, or search using the search box.
+
+**New to Pipecat?** Check out the `main documentation <https://docs.pipecat.ai>`_ for tutorials, guides, and client SDK information.
 
 Quick Links
 -----------
 
 * `GitHub Repository <https://github.com/pipecat-ai/pipecat>`_
-* `Website <https://pipecat.ai>`_
-
-API Reference
--------------
-
-Core Components
-~~~~~~~~~~~~~~~
-
-* :mod:`Frames <pipecat.frames>`
-* :mod:`Processors <pipecat.processors>`
-* :mod:`Pipeline <pipecat.pipeline>`
-
-Audio Processing
-~~~~~~~~~~~~~~~~
-
-* :mod:`Audio <pipecat.audio>`
-
-Services
-~~~~~~~~
-
-* :mod:`Services <pipecat.services>`
-
-Transport & Serialization
-~~~~~~~~~~~~~~~~~~~~~~~~~
-
-* :mod:`Transports <pipecat.transports>`
-   * :mod:`Local <pipecat.transports.local>`
-   * :mod:`Network <pipecat.transports.network>`
-   * :mod:`Services <pipecat.transports.services>`
-* :mod:`Serializers <pipecat.serializers>`
-
-Utilities
-~~~~~~~~~
-
-* :mod:`Clocks <pipecat.clocks>`
-* :mod:`Metrics <pipecat.metrics>`
-* :mod:`Sync <pipecat.sync>`
-* :mod:`Transcriptions <pipecat.transcriptions>`
-* :mod:`Utils <pipecat.utils>`
+* `Join our Community <https://discord.gg/pipecat>`_
 
 .. toctree::
-   :maxdepth: 3
+   :maxdepth: 2
    :caption: API Reference
    :hidden:
 
+   Adapters <api/pipecat.adapters>
    Audio <api/pipecat.audio>
    Clocks <api/pipecat.clocks>
+   Extensions <api/pipecat.extensions>
    Frames <api/pipecat.frames>
    Metrics <api/pipecat.metrics>
+   Observers <api/pipecat.observers>
    Pipeline <api/pipecat.pipeline>
    Processors <api/pipecat.processors>
+   Runner <api/pipecat.runner>
    Serializers <api/pipecat.serializers>
    Services <api/pipecat.services>
    Sync <api/pipecat.sync>
    Transcriptions <api/pipecat.transcriptions>
    Transports <api/pipecat.transports>
-   Utils <api/pipecat.utils>
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`
+   Utils <api/pipecat.utils>

docs/api/requirements.txt

@@ -1,40 +0,0 @@
-# Sphinx dependencies
-sphinx>=8.1.3
-sphinx-rtd-theme
-sphinx-markdown-builder
-sphinx-autodoc-typehints
-toml
-
-# Install all extras individually to ensure they're properly resolved
-pipecat-ai[anthropic]
-pipecat-ai[assemblyai]
-pipecat-ai[aws]
-pipecat-ai[azure]
-pipecat-ai[canonical]
-pipecat-ai[cartesia]
-pipecat-ai[daily]
-pipecat-ai[deepgram]
-pipecat-ai[elevenlabs]
-pipecat-ai[fal]
-pipecat-ai[fireworks]
-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[lmnt]
-pipecat-ai[local]
-pipecat-ai[moondream]
-pipecat-ai[nim]
-pipecat-ai[noisereduce]
-pipecat-ai[openai]
-# pipecat-ai[openpipe]
-# pipecat-ai[playht] # Mocked due to grpcio conflict with riva
-pipecat-ai[riva]
-pipecat-ai[silero]
-pipecat-ai[simli]
-pipecat-ai[soundfile]
-pipecat-ai[websocket]
-pipecat-ai[whisper]

docs/architecture.md

@@ -1,17 +0,0 @@
-# Pipecat architecture guide
-
-## Frames
-
-Frames can represent discrete chunks of data, for instance a chunk of text, a chunk of audio, or an image. They can also be used to as control flow, for instance a frame that indicates that there is no more data available, or that a user started or stopped talking. They can also represent more complex data structures, such as a message array used for an LLM completion.
-
-## FrameProcessors
-
-Frame processors operate on frames. Every frame processor implements a `process_frame` method that consumes one frame and produces zero or more frames. Frame processors can do simple transforms, such as concatenating text fragments into sentences, or they can treat frames as input for an AI Service, and emit chat completions based on message arrays or transform text into audio or images.
-
-## Pipelines
-
-Pipelines are lists of frame processors linked together. Frame processors can push frames upstream or downstream to their peers. A very simple pipeline might chain an LLM frame processor to a text-to-speech frame processor, with a transport as an output.
-
-## Transports
-
-Transports provide input and output frame processors to receive or send frames respectively. For example, the `DailyTransport` does this with a WebRTC session joined to a Daily.co room.

docs/frame-progress.md

@@ -1,46 +0,0 @@
-# A Frame's Progress
-
-1. A user says “Hello, LLM” and the cloud transcription service delivers a transcription to the Transport.
-![A transcript frame arrives](images/frame-progress-01.png)
-
-2. The Transport places a Transcription frame in the Pipeline’s source queue.
-![Frame in source queue](images/frame-progress-02.png)
-
-3. The Pipeline passes the Transcription frame to the first Frame Processor in its list, the LLM User Message Aggregator.
-![To UMA](images/frame-progress-03.png)
-
-4. The LLM User Message Aggregator updates the LLM Context with a `{“user”: “Hello LLM”}` message.
-![Update context](images/frame-progress-04.png)
-
-5. The LLM User Message Aggregator yields an LLM Message Frame, containing the updated LLM Context. The Pipeline passes this frame to the LLM Frame Processor.
-![Update context](images/frame-progress-05.png)
-
-6. The LLM Frame Processor creates a streaming chat completion based on the LLM context and yields the first chunk of a response, Text Frame with the value “Hi, “. The Pipeline passes this frame to the TTS Frame Processor. The TTS Frame Processor aggregates this response but doesn’t yield anything, yet, because it’s waiting for a full sentence.
-![LLM yields Text](images/frame-progress-06.png)
-
-7. The LLM Frame Processor yields another Text Frame with the value “there.”. The Pipeline passes this frame to the TTS Frame Processor.
-![LLM yields more Text](images/frame-progress-07.png)
-
-8. The TTS Frame Processor now has a full sentence, so it starts streaming audio based on “Hi, there.” It yields the first chunk of streaming audio as an Audio frame, which the Pipeline passes to the LLM Assistant Message Aggregator.
-![TTS yields Audio](images/frame-progress-08.png)
-
-9. The LLM Assistant Message Aggregator doesn’t do anything with Audio frames, so it immediately yields the frame, unchanged. This is the convention for all Frame Processors: frames that the processor doesn’t process should be immediately yielded.
-![pass-through](images/frame-progress-09.png)
-
-10. The Pipeline places the first Audio frame in its sink queue, which is being watched by the Transport. Since the frame is now in a queue, the Pipeline can continue processing other frames. Note that the source and sink queues form a sort of “boundary of concurrent processing” between a Pipeline and the outside world. In a Pipeline, Frames are processed sequentially; once a Frame is on a queue it can be processed in parallel with the frames being processed by the Pipeline. TODO: link to a more in-depth section about this.
-![sink queue](images/frame-progress-10.png)
-
-11. The TTS Frame Processor yields another Audio frame as the Transport transmits the first Audio frame.
-![parallel audio](images/frame-progress-11.png)
-
-12. As before, the LLM Assistant Message Aggregator immediately yields the Audio frame and the Pipeline places the Audio frame in the sink queue.
-![sink queue 2](images/frame-progress-12.png)
-
-13. The TTS Frame Processor has no more frames to yield. The LLM Frame Processor emits an LLM Response End Frame, which the Pipeline passes to the TTS Frame Processor.
-![response end](images/frame-progress-13.png)
-
-14. The TTS Frame Processor immediately yields the LLM Response End Frame, so the Pipeline passes it along to the LLM Assistant Message Aggregator. The LLM Assistant Message Aggregator updates the LLM Context with the full response from the LLM. TODO TODO: I realized I forgot that the TSS Frame Processor also yields the Text frames that the LLM emitted so that the LLM Assistant Message Aggregator could accumulate them, arrggh.
-![response end](images/frame-progress-14.png)
-
-15. The system is quiet, and waiting for the next message from the Transport.
-![response end](images/frame-progress-15.png)

docs/frame.md

@@ -1,110 +0,0 @@
-# Understanding Different Frame Types in the Pipecat System
-
-In the Pipecat system, frames are used to represent different types of data and control signals that flow through the pipeline. Understanding these frame types is crucial for working with the system effectively. This tutorial will cover the main categories of frames and their specific uses.
-
-## 1. Base Frame Classes
-
-### Frame
-The `Frame` class is the base class for all frames. It includes:
-- `id`: A unique identifier
-- `name`: A descriptive name
-- `pts`: Presentation timestamp (optional)
-
-### DataFrame
-`DataFrame` is a subclass of `Frame` and serves as a base for most data-carrying frames.
-
-## 2. Audio Frames
-
-### AudioRawFrame
-Represents a chunk of audio with properties:
-- `audio`: Raw audio data
-- `sample_rate`: Audio sample rate
-- `num_channels`: Number of audio channels
-
-Subclasses include:
-- `InputAudioRawFrame`: For audio from input sources
-- `OutputAudioRawFrame`: For audio to be played by output devices
-- `TTSAudioRawFrame`: For audio generated by Text-to-Speech services
-
-## 3. Image Frames
-
-### ImageRawFrame
-Represents an image with properties:
-- `image`: Raw image data
-- `size`: Image dimensions
-- `format`: Image format (e.g., JPEG, PNG)
-
-Subclasses include:
-- `InputImageRawFrame`: For images from input sources
-- `OutputImageRawFrame`: For images to be displayed
-- `UserImageRawFrame`: For images associated with a specific user
-- `VisionImageRawFrame`: For images with associated text for description
-- `URLImageRawFrame`: For images with an associated URL
-
-### SpriteFrame
-Represents an animated sprite, containing a list of `ImageRawFrame` objects.
-
-## 4. Text and Transcription Frames
-
-### TextFrame
-Represents a chunk of text, used for various purposes in the pipeline.
-
-### TranscriptionFrame
-A specialized `TextFrame` for speech transcriptions, including:
-- `user_id`: ID of the speaking user
-- `timestamp`: When the transcription was generated
-- `language`: Detected language of the speech
-
-### InterimTranscriptionFrame
-Similar to `TranscriptionFrame`, but for interim (not final) transcriptions.
-
-## 5. LLM (Language Model) Frames
-
-### LLMMessagesFrame
-Contains a list of messages for an LLM service to process.
-
-### LLMMessagesAppendFrame and LLMMessagesUpdateFrame
-Used to modify the current context of LLM messages.
-
-### LLMSetToolsFrame
-Specifies tools (functions) available for the LLM to use.
-
-### LLMEnablePromptCachingFrame
-Controls prompt caching in certain LLMs.
-
-## 6. System and Control Frames
-
-### SystemFrame
-Base class for system-level frames.
-
-Important system frames include:
-- `StartFrame`: Initiates a pipeline
-- `CancelFrame`: Stops a pipeline immediately
-- `ErrorFrame`: Notifies of errors (with `FatalErrorFrame` for unrecoverable errors)
-- `EndTaskFrame` and `CancelTaskFrame`: Control pipeline tasks
-- `StartInterruptionFrame` and `StopInterruptionFrame`: Indicate user speech for interruptions
-
-### ControlFrame
-Base class for control-flow frames.
-
-Notable control frames:
-- `EndFrame`: Signals the end of a pipeline
-- `LLMFullResponseStartFrame` and `LLMFullResponseEndFrame`: Bracket LLM responses
-- `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame`: Indicate user speech activity
-- `BotStartedSpeakingFrame` and `BotStoppedSpeakingFrame`: Indicate bot speech activity
-- `TTSStartedFrame` and `TTSStoppedFrame`: Bracket Text-to-Speech responses
-
-## 7. Special Purpose Frames
-
-### MetricsFrame
-Contains performance metrics data.
-
-### FunctionCallInProgressFrame and FunctionCallResultFrame
-Used for handling LLM function (tool) calls.
-
-### ServiceUpdateSettingsFrame
-Base class for updating service settings, with specific subclasses for LLM, TTS, and STT services.
-
-## Conclusion
-
-Understanding these frame types is essential for working with the Pipecat system. Each frame type serves a specific purpose in the pipeline, whether it's carrying data (like audio or images), controlling the flow of the pipeline, or managing system-level operations. By using the appropriate frame types, you can effectively process and transmit various kinds of information through your pipeline.

env.example

@@ -1,6 +1,13 @@
+# AI-COUSTICS
+AICOUSTICS_LICENSE_KEY=...
+
 # Anthropic
 ANTHROPIC_API_KEY=...
 
+# Async
+ASYNCAI_API_KEY=...
+ASYNCAI_VOICE_ID=...
+
 # AWS
 AWS_SECRET_ACCESS_KEY=...
 AWS_ACCESS_KEY_ID=...
@@ -18,14 +25,23 @@ AZURE_DALLE_API_KEY=...
 AZURE_DALLE_ENDPOINT=https://...
 AZURE_DALLE_MODEL=...
 
+# Cartesia
+CARTESIA_API_KEY=...
+
 # Daily
 DAILY_API_KEY=...
 DAILY_SAMPLE_ROOM_URL=https://...
 
+# Deepgram
+DEEPGRAM_API_KEY=...
+
 # ElevenLabs
 ELEVENLABS_API_KEY=...
 ELEVENLABS_VOICE_ID=...
 
+# Neuphonic
+NEUPHONIC_API_KEY=...
+
 # Fal
 FAL_KEY=...
 
@@ -34,11 +50,21 @@ FIREWORKS_API_KEY=...
 
 # Gladia
 GLADIA_API_KEY=...
+GLADIA_REGION=...
+
+# Google
+GOOGLE_API_KEY=...
+GOOGLE_CLOUD_PROJECT_ID=...
+GOOGLE_TEST_CREDENTIALS=...
+GOOGLE_VERTEX_TEST_CREDENTIALS=...
 
 # LMNT
 LMNT_API_KEY=...
 LMNT_VOICE_ID=...
 
+# Perplexity
+PERPLEXITY_API_KEY=...
+
 # PlayHT
 PLAY_HT_USER_ID=...
 PLAY_HT_API_KEY=...
@@ -70,6 +96,9 @@ GROQ_API_KEY=...
 # Grok
 GROK_API_KEY=...
 
+# Inworld
+INWORLD_API_KEY=...
+
 # Together.ai
 TOGETHER_API_KEY=...
 
@@ -84,3 +113,45 @@ 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=...
+
+# Soniox
+SONIOX_API_KEY=
+
+# Speechmatics
+SPEECHMATICS_API_KEY=...
+
+# SambaNova
+SAMBANOVA_API_KEY=...
+
+# Sentry
+SENTRY_DSN=...
+
+# Heygen
+HEYGEN_API_KEY=...
+
+# Mistral
+MISTRAL_API_KEY=...
+
+# NVIDIA
+NVIDIA_API_KEY=...
+
+# Qwen
+QWEN_API_KEY=...

examples/README.md

@@ -1,88 +1,31 @@
+# Pipecat Examples
 
+This directory contains examples to help you learn how to build with Pipecat.
 
-# Pipecat — Examples
+## Getting Started
 
-## Foundational snippets
-Small snippets that build on each other, introducing one or two concepts at a time.
+New to Pipecat? Start here:
 
-➡️ [Take a look](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational)
+- **[Quickstart](quickstart/)** - Get your first voice AI bot running in 5 minutes _(coming soon)_
+- **[Client/Server Web](client-server-web/)** - Learn to build web applications with Pipecat's client SDKs _(coming soon)_
+- **[Phone Bot with Twilio](phone-bot-twilio/)** - Connect your bot to a phone number _(coming soon)_
 
-## Chatbot examples
-Collection of self-contained real-time voice and video AI demo applications built with Pipecat.
+## Foundational Examples
 
-### Quickstart
+Single-file examples that introduce core Pipecat concepts one at a time. These examples:
 
-Each project has its own set of dependencies and configuration variables. They intentionally avoids shared code across projects — you can grab whichever demo folder you want to work with as a starting point.
+- Build on each other progressively
+- Focus on specific features or integrations
+- Are used for testing with every Pipecat release
 
-We recommend you start with a virtual environment:
+See the **[Foundational Examples README](foundational/)** for the complete list.
 
-```shell
-cd pipecat-ai/examples/simple-chatbot
+## More Advanced Examples
 
-python -m venv venv
+Ready to explore complex use cases? Visit **[pipecat-examples](https://github.com/pipecat-ai/pipecat-examples)** for:
 
-source venv/bin/activate
-
-pip install -r requirements.txt
-```
-
-Next, follow the steps in the README for each demo.
-
-ℹ️ Make sure you `pip install -r requirements.txt` for each demo project, so you can be sure to have the necessary service dependencies that extend the functionality of Pipecat. You can read more about the framework architecture [here](https://github.com/pipecat-ai/pipecat/tree/main/docs).
-
-## Projects:
-
-| Project                                      | Description                                                                                                                                | Services                                                          |
-|----------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|
-| [Simple Chatbot](simple-chatbot)             | Basic voice-driven conversational bot. A good starting point for learning the flow of the framework.                                       | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI            |
-| [Storytelling Chatbot](storytelling-chatbot) | Stitches together multiple third-party services to create a collaborative storytime experience.                                            | Deepgram, ElevenLabs, OpenAI, Fal, Daily, Custom UI               |
-| [Translation Chatbot](translation-chatbot)   | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI                 |
-| [Moondream Chatbot](moondream-chatbot)       | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU**                                                       | Deepgram, ElevenLabs, OpenAI, Moondream, Daily, Daily Prebuilt UI |
-| [Patient intake](patient-intake)             | A chatbot that can call functions in response to user input.                                                                               | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI            |
-| [Phone Chatbot](phone-chatbot)             | A chatbot that connects to PSTN/SIP phone calls, powered by Daily or Twilio.                                                                    | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
-| [Twilio Chatbot](twilio-chatbot)             | A chatbot that connects to an incoming phone call from Twilio.                                                                             | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
-| [studypal](studypal)                         | A chatbot to have a conversation about any article on the web                                                                              |                                                                   |
-| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities. | Cartesia, Deepgram, OpenAI, Websockets |
-
-> [!IMPORTANT]
-> These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.
-> It provides a quick way to join a real-time session with your bot and test your ideas without building any frontend code. If you'd like to see an example of a custom UI, try Storybot.
-
-
-## FAQ
-
-### Deployment
-
-For each of these demos we've included a `Dockerfile`. Out of the box, this should provide everything needed to get the respective demo running on a VM:
-
-```shell
-docker build username/app:tag .
-
-docker run -p 7860:7860 --env-file ./.env username/app:tag
-
-docker push ...
-```
-
-### SSL
-
-If you're working with a custom UI (such as with the Storytelling Chatbot), it's important to ensure your deployment platform supports HTTPS, as accessing user devices such as mics and webcams requires SSL.
-
-If you try to run a custom UI without SSL, you may see an error in the console telling you that `navigator` is undefined, or no devices are available.
-
-### Are these examples production ready?
-
-Yes, kind of.
-
-These demos attempt to keep things simple and are unopinionated regarding environment or scalability.
-
-We're using FastAPI to spawn a subprocess for the bots / agents — useful for small tests, but not so great for production grade apps with many concurrent users. You can see how this works in each project's `start` endpoint in `server.py`.
-
-Creating virtualized worker pools and on-demand instances is out of scope for these examples, but we hope to add some examples to this repo soon!
-
-For projects that have CUDA as a requirement, such as Moondream Chatbot, be sure to deploy to a GPU-powered platform (such as [fly.io](https://fly.io) or [Runpod](https://runpod.io).)
-
-## Getting help
-
-➡️ [Join our Discord](https://discord.gg/pipecat)
-
-➡️ [Reach us on Twitter](https://x.com/pipecat_ai)
+- Production-ready applications
+- Multi-platform client implementations
+- Telephony integrations
+- Multimodal and creative applications
+- Deployment and monitoring examples

examples/bot-ready-signalling/README.md

@@ -1,45 +0,0 @@
-# Bot ready signaling
-
-A simple Pipecat example demonstrating how to handle signaling between the client and the bot, 
-ensuring that the bot starts sending audio only when the client is available, 
-thereby avoiding the risk of cutting off the beginning of the audio.
-
-## Quick Start
-
-### First, start the bot server:
-
-1. Navigate to the server directory:
-   ```bash
-   cd server
-   ```
-2. Create and activate a virtual environment:
-   ```bash
-   python3 -m venv venv
-   source venv/bin/activate  # On Windows: venv\Scripts\activate
-   ```
-3. Install requirements:
-   ```bash
-   pip install -r requirements.txt
-   ```
-4. Copy env.example to .env and configure:
-   - Add your API keys
-5. Start the server:
-   ```bash
-   python server.py
-   ```
-
-### Next, connect using the client app:
-
-For client-side setup, refer to the [JavaScript Guide](client/javascript/README.md).
-
-## Important Note
-
-Ensure the bot server is running before using any client implementations.
-
-## Requirements
-
-- Python 3.10+
-- Node.js 16+ (for JavaScript)
-- Daily API key
-- Cartesia API key
-- Modern web browser with WebRTC support

examples/bot-ready-signalling/client/javascript/README.md

@@ -1,27 +0,0 @@
-# JavaScript Implementation
-
-Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
-
-## Setup
-
-1. Run the bot server. See the [server README](../../README).
-
-2. Navigate to the `client/javascript` directory:
-
-```bash
-cd client/javascript
-```
-
-3. Install dependencies:
-
-```bash
-npm install
-```
-
-4. Run the client app:
-
-```
-npm run dev
-```
-
-5. Visit http://localhost:5173 in your browser.

examples/bot-ready-signalling/client/javascript/index.html

@@ -1,34 +0,0 @@
-<!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">
-        <button id="connect-btn">Connect</button>
-        <button id="disconnect-btn" disabled>Disconnect</button>
-      </div>
-    </div>
-
-    <audio id="bot-audio" autoplay></audio>
-
-    <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/bot-ready-signalling/client/javascript/package.json

@@ -1,20 +0,0 @@
-{
-  "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": "^6.0.9"
-  },
-  "dependencies": {
-    "@daily-co/daily-js": "0.74.0"
-  }
-}

examples/bot-ready-signalling/client/javascript/src/app.js

@@ -1,216 +0,0 @@
-/**
- * Copyright (c) 2024–2025, Daily
- *
- * SPDX-License-Identifier: BSD 2-Clause License
- */
-
-import Daily from "@daily-co/daily-js";
-
-/**
- * ChatbotClient handles the connection and media management for a real-time
- * voice interaction with an AI bot.
- */
-class ChatbotClient {
-  constructor() {
-    // Initialize client state
-    this.dailyCallObject = null;
-    this.setupDOMElements();
-    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');
-
-    // 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());
-  }
-
-  /**
-   * 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}`);
-  }
-
-  handleEventToConsole (evt) {
-    this.log(`Received event: ${evt.action}`);
-  };
-
-  /**
-   * Set up listeners for track events (start/stop)
-   * This handles new tracks being added during the session
-   */
-  setupTrackListeners() {
-    if (!this.dailyCallObject) return;
-
-    this.dailyCallObject.on("joined-meeting", () => {
-      this.updateStatus('Connected');
-      this.connectBtn.disabled = true;
-      this.disconnectBtn.disabled = false;
-      this.log('Client connected');
-    });
-    this.dailyCallObject.on("track-started", (evt) => {
-      if (evt.track.kind === "audio" && evt.participant.local === false) {
-        this.log("Audio track started.")
-        this.setupAudioTrack(evt.track);
-      }
-    });
-    this.dailyCallObject.on("track-stopped", this.handleEventToConsole.bind(this));
-    this.dailyCallObject.on("participant-joined", this.handleEventToConsole.bind(this));
-    this.dailyCallObject.on("participant-updated", this.handleEventToConsole.bind(this));
-    this.dailyCallObject.on("participant-left", () => {
-      // When the bot leaves, we are also disconnecting from the call
-      this.disconnect()
-    });
-    this.dailyCallObject.on("left-meeting", () => {
-      this.updateStatus('Disconnected');
-      this.connectBtn.disabled = false;
-      this.disconnectBtn.disabled = true;
-      this.log('Client disconnected');
-    });
-    this.dailyCallObject.on("error", this.handleEventToConsole.bind(this));
-  }
-
-  /**
-   * Set up an audio track for playback
-   * Handles both initial setup and track updates
-   */
-  setupAudioTrack(track) {
-    this.log(`Setting up audio track, track state: ${track.readyState}, muted: ${track.muted}`);
-
-    // 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]);
-    this.botAudio.onplaying = async (event) => {
-      this.log("onplaying")
-      this.log("Will send the audio message to play the audio at the next tick")
-      this.dailyCallObject.sendAppMessage("playable")
-    }
-  }
-
-  async fetchRoomInfo() {
-    let connectUrl = '/connect'
-    let res = await fetch(connectUrl, {
-      method: "POST",
-      mode: "cors",
-      headers: new Headers({
-        "Content-Type": "application/json"
-      }),
-    })
-    if (res.ok) {
-      return res.json();
-    }
-  }
-
-  /**
-   * Initialize and connect to the bot
-   * This sets up the RTVI client, initializes devices, and establishes the connection
-   */
-  async connect() {
-    try {
-      // Initialize the client
-      this.dailyCallObject = Daily.createCallObject({
-        subscribeToTracksAutomatically: true,
-      });
-
-      // Set up listeners for media track events
-      this.setupTrackListeners();
-
-      this.log('Creating the bot...');
-      let roomInfo = await this.fetchRoomInfo()
-
-      // Connect to the bot
-      this.log('Connecting to bot...');
-      // Only for making debugger easier
-      window.callObject = this.dailyCallObject;
-      await this.dailyCallObject.join({
-        url: roomInfo.room_url,
-      });
-
-      this.log('Connection complete');
-    } catch (error) {
-      // Handle any errors during connection
-      this.log(`Error connecting: ${error.message}`);
-      this.log(`Error stack: ${error.stack}`);
-      this.updateStatus('Error');
-
-      // Clean up if there's an error
-      if (this.dailyCallObject) {
-        try {
-          await this.dailyCallObject.leave();
-        } catch (disconnectError) {
-          this.log(`Error during disconnect: ${disconnectError.message}`);
-        }
-      }
-    }
-  }
-
-  /**
-   * Disconnect from the bot and clean up media resources
-   */
-  async disconnect() {
-    if (this.dailyCallObject) {
-      try {
-        // Disconnect the RTVI client
-        await this.dailyCallObject.leave();
-        await this.dailyCallObject.destroy();
-        this.dailyCallObject = null;
-
-        // Clean up audio
-        if (this.botAudio.srcObject) {
-          this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
-          this.botAudio.srcObject = null;
-        }
-      } catch (error) {
-        this.log(`Error disconnecting: ${error.message}`);
-      }
-    }
-  }
-}
-
-// Initialize the client when the page loads
-window.addEventListener('DOMContentLoaded', () => {
-  new ChatbotClient();
-});

examples/bot-ready-signalling/client/javascript/src/style.css

@@ -1,98 +0,0 @@
-body {
-  margin: 0;
-  padding: 20px;
-  font-family: Arial, sans-serif;
-  background-color: #f0f0f0;
-}
-
-.container {
-  max-width: 1200px;
-  margin: 0 auto;
-}
-
-.status-bar {
-  display: flex;
-  justify-content: space-between;
-  align-items: center;
-  padding: 10px;
-  background-color: #fff;
-  border-radius: 8px;
-  margin-bottom: 20px;
-}
-
-.controls button {
-  padding: 8px 16px;
-  margin-left: 10px;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-#connect-btn {
-  background-color: #4caf50;
-  color: white;
-}
-
-#disconnect-btn {
-  background-color: #f44336;
-  color: white;
-}
-
-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/bot-ready-signalling/client/javascript/vite.config.js

@@ -1,13 +0,0 @@
-import { defineConfig } from 'vite';
-
-export default defineConfig({
-    server: {
-        proxy: {
-            // Proxy /api requests to the backend server
-            '/connect': {
-                target: 'http://0.0.0.0:7860', // Replace with your backend URL
-                changeOrigin: true,
-            },
-        },
-    },
-});

examples/bot-ready-signalling/server/README.md

@@ -1,50 +0,0 @@
-# Bot ready signaling Server
-
-A FastAPI server that manages bot instances and provide endpoint for Pipecat client connections.
-
-## Endpoints
-
-- `POST /connect` - Pipecat client connection endpoint
-
-## Environment Variables
-
-Copy `env.example` to `.env` and configure:
-
-```ini
-# Required API Keys
-DAILY_API_KEY=           # Your Daily API key
-CARTESIA_API_KEY=        # Your Cartesia API key
-
-# Optional Configuration
-DAILY_API_URL=           # Optional: Daily API URL (defaults to https://api.daily.co/v1)
-DAILY_SAMPLE_ROOM_URL=   # Optional: Fixed room URL for development
-HOST=                    # Optional: Host address (defaults to 0.0.0.0)
-FAST_API_PORT=           # Optional: Port number (defaults to 7860)
-```
-
-## Running the Server
-
-Set up and activate your virtual environment:
-
-```bash
-python3 -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
-```
-
-Install dependencies:
-
-```bash
-pip install -r requirements.txt
-```
-
-If you want to use the local version of `pipecat` in this repo rather than the last published version, also run:
-
-```bash
-pip install --editable "../../../[daily,cartesia,openai]"
-```
-
-Run the server:
-
-```bash
-python server.py
-```

examples/bot-ready-signalling/server/env.example

@@ -1,3 +0,0 @@
-DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
-DAILY_API_KEY=
-CARTESIA_API_KEY=

examples/bot-ready-signalling/server/requirements.txt

@@ -1,4 +0,0 @@
-python-dotenv
-fastapi[all]
-uvicorn
-pipecat-ai[daily,cartesia,openai]

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

@@ -1,64 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-from typing import Optional
-
-import aiohttp
-
-from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
-
-
-async def configure(aiohttp_session: aiohttp.ClientSession):
-    (url, token, _) = await configure_with_args(aiohttp_session)
-    return (url, token)
-
-
-async def configure_with_args(
-    aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
-):
-    if not parser:
-        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, args)

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

@@ -1,147 +0,0 @@
-#
-# Copyright (c) 2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-import subprocess
-from contextlib import asynccontextmanager
-from typing import Any, Dict
-
-import aiohttp
-from dotenv import load_dotenv
-from fastapi import FastAPI, HTTPException, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
-
-from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
-
-# Load environment variables from .env file
-load_dotenv(override=True)
-
-# Dictionary to track bot processes: {pid: (process, room_url)}
-bot_procs = {}
-
-# Store Daily API helpers
-daily_helpers = {}
-
-
-def cleanup():
-    """Cleanup function to terminate all bot processes.
-
-    Called during server shutdown.
-    """
-    for entry in bot_procs.values():
-        proc = entry[0]
-        proc.terminate()
-        proc.wait()
-
-
-@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
-    """
-    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()
-
-
-# Initialize FastAPI app with lifespan manager
-app = FastAPI(lifespan=lifespan)
-
-# Configure CORS to allow requests from any origin
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-
-async def create_room_and_token() -> tuple[str, str]:
-    """Helper function to create a Daily room and generate an access token.
-
-    Returns:
-        tuple[str, str]: A tuple containing (room_url, token)
-
-    Raises:
-        HTTPException: If room creation or token generation fails
-    """
-    room = await daily_helpers["rest"].create_room(DailyRoomParams())
-    if not room.url:
-        raise HTTPException(status_code=500, detail="Failed to create room")
-
-    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.post("/connect")
-async def bot_connect(request: Request) -> Dict[Any, Any]:
-    """Connect endpoint that creates a room and returns connection credentials.
-
-    This endpoint is called by client to establish a connection.
-
-    Returns:
-        Dict[Any, Any]: Authentication bundle containing room_url and token
-
-    Raises:
-        HTTPException: If room creation, token generation, or bot startup fails
-    """
-    print("Creating room for RTVI connection")
-    room_url, token = await create_room_and_token()
-    print(f"Room URL: {room_url}")
-
-    # Start the bot process
-    try:
-        bot_file = "signalling_bot"
-        proc = subprocess.Popen(
-            [f"python3 -m {bot_file} -u {room_url} -t {token}"],
-            shell=True,
-            bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__)),
-        )
-        bot_procs[proc.pid] = (proc, room_url)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
-
-    # Return the authentication bundle in format expected by DailyTransport
-    return {"room_url": room_url, "token": token}
-
-
-if __name__ == "__main__":
-    import uvicorn
-
-    # Parse command line arguments for server configuration
-    default_host = os.getenv("HOST", "0.0.0.0")
-    default_port = int(os.getenv("FAST_API_PORT", "7860"))
-
-    parser = argparse.ArgumentParser(description="Daily Travel Companion FastAPI server")
-    parser.add_argument("--host", type=str, default=default_host, help="Host address")
-    parser.add_argument("--port", type=int, default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true", help="Reload code on change")
-
-    config = parser.parse_args()
-
-    # Start the FastAPI server
-    uvicorn.run(
-        "server:app",
-        host=config.host,
-        port=config.port,
-        reload=config.reload,
-    )

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

@@ -1,95 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-import sys
-from dataclasses import dataclass
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-from runner import configure
-
-from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-@dataclass
-class SilenceFrame(OutputAudioRawFrame):
-    def __init__(
-        self,
-        *,
-        sample_rate: int,
-        duration: float,
-    ):
-        # Initialize the parent class with the silent frame's data
-        super().__init__(
-            audio=self.create_silent_audio_frame(sample_rate, 1, duration).audio,
-            sample_rate=sample_rate,
-            num_channels=1,
-        )
-
-    @staticmethod
-    def create_silent_audio_frame(
-        sample_rate: int, num_channels: int, duration: float
-    ) -> AudioRawFrame:
-        """Create an AudioRawFrame containing silence."""
-        frame_size = num_channels * 2  # 2 bytes per sample for 16-bit audio
-        total_frames = int(sample_rate * duration)
-        total_bytes = total_frames * frame_size
-        silent_audio = bytes(total_bytes)  # Create a byte array filled with zeros
-        return AudioRawFrame(audio=silent_audio, sample_rate=sample_rate, num_channels=num_channels)
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, _) = await configure(session)
-
-        transport = DailyTransport(
-            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
-        )
-
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
-
-        runner = PipelineRunner()
-
-        task = PipelineTask(Pipeline([tts, transport.output()]))
-
-        # Register an event handler so we can play the audio when we receive a specific message
-        @transport.event_handler("on_app_message")
-        async def on_app_message(transport, message, sender):
-            logger.debug(f"Received app message: {message} - {sender}")
-            if "playable" not in message:
-                return
-            await task.queue_frames(
-                [
-                    SilenceFrame(
-                        sample_rate=task.params.audio_out_sample_rate,
-                        duration=0.5,
-                    ),
-                    TTSSpeakFrame(f"Hello there, how are you doing today ?"),
-                    EndFrame(),
-                ]
-            )
-
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

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/Dockerfile

@@ -1,10 +0,0 @@
-FROM python:3.10-bullseye
-RUN mkdir /app
-COPY *.py /app/
-COPY requirements.txt /app/
-WORKDIR /app
-RUN pip3 install -r requirements.txt
-
-EXPOSE 7860
-
-CMD ["python3", "server.py"]

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, 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/env.example

@@ -1,6 +0,0 @@
-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=

examples/canonical-metrics/requirements.txt

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

examples/canonical-metrics/runner.py

@@ -1,55 +0,0 @@
-#
-# 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/canonical-metrics/server.py

@@ -1,139 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-import subprocess
-from contextlib import asynccontextmanager
-
-import aiohttp
-from dotenv import load_dotenv
-from fastapi import FastAPI, HTTPException, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse, RedirectResponse
-
-from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
-
-MAX_BOTS_PER_ROOM = 1
-
-# Bot sub-process dict for status reporting and concurrency control
-bot_procs = {}
-
-daily_helpers = {}
-
-load_dotenv(override=True)
-
-
-def cleanup():
-    # Clean up function, just to be extra safe
-    for entry in bot_procs.values():
-        proc = entry[0]
-        proc.terminate()
-        proc.wait()
-
-
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    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()
-
-
-app = FastAPI(lifespan=lifespan)
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-
-@app.get("/")
-async def start_agent(request: Request):
-    print(f"!!! Creating room")
-    room = await daily_helpers["rest"].create_room(DailyRoomParams())
-    print(f"!!! Room URL: {room.url}")
-    # Ensure the room property is present
-    if not room.url:
-        raise HTTPException(
-            status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
-        )
-
-    # Check if there is already an existing process running in this room
-    num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
-    )
-    if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
-
-    # Get the token for the room
-    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}")
-
-    # Spawn a new agent, and join the user session
-    # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
-    try:
-        proc = subprocess.Popen(
-            [f"python3 -m bot -u {room.url} -t {token}"],
-            shell=True,
-            bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__)),
-        )
-        bot_procs[proc.pid] = (proc, room.url)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
-
-    return RedirectResponse(room.url)
-
-
-@app.get("/status/{pid}")
-def get_status(pid: int):
-    # Look up the subprocess
-    proc = bot_procs.get(pid)
-
-    # If the subprocess doesn't exist, return an error
-    if not proc:
-        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
-
-    # Check the status of the subprocess
-    if proc[0].poll() is None:
-        status = "running"
-    else:
-        status = "finished"
-
-    return JSONResponse({"bot_id": pid, "status": status})
-
-
-if __name__ == "__main__":
-    import uvicorn
-
-    default_host = os.getenv("HOST", "0.0.0.0")
-    default_port = int(os.getenv("FAST_API_PORT", "7860"))
-
-    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str, default=default_host, help="Host address")
-    parser.add_argument("--port", type=int, default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true", help="Reload code on change")
-
-    config = parser.parse_args()
-
-    uvicorn.run(
-        "server:app",
-        host=config.host,
-        port=config.port,
-        reload=config.reload,
-    )

examples/chatbot-audio-recording/.gitignore

@@ -1,161 +0,0 @@
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# 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/chatbot-audio-recording/Dockerfile

@@ -1,15 +0,0 @@
-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
-
-EXPOSE 7860
-
-CMD ["python3", "server.py"]

examples/chatbot-audio-recording/README.md

@@ -1,37 +0,0 @@
-# Simple Chatbot
-
-<img src="image.png" width="420px">
-
-This app connects you to a chatbot powered by GPT-4, complete with animations generated by Stable Video Diffusion.
-
-See a video of it in action: https://x.com/kwindla/status/1778628911817183509
-
-And a quick video walkthrough of the code: https://www.loom.com/share/13df1967161f4d24ade054e7f8753416
-
-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/chatbot-audio-recording/bot.py

@@ -1,150 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import datetime
-import io
-import os
-import sys
-import wave
-
-import aiofiles
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-from runner import configure
-
-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.processors.audio.audio_buffer_processor import AudioBufferProcessor
-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 save_audio(audio: bytes, sample_rate: int, num_channels: int):
-    if len(audio) > 0:
-        filename = f"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)
-                wf.setnchannels(num_channels)
-                wf.setframerate(sample_rate)
-                wf.writeframes(audio)
-            async with aiofiles.open(filename, "wb") as file:
-                await file.write(buffer.getvalue())
-        print(f"Merged audio saved to {filename}")
-    else:
-        print("No audio data to save")
-
-
-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 response 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)
-
-        # NOTE: Watch out! This will save all the conversation in memory. You
-        # can pass `buffer_size` to get periodic callbacks.
-        audiobuffer = AudioBufferProcessor()
-
-        pipeline = Pipeline(
-            [
-                transport.input(),  # microphone
-                context_aggregator.user(),
-                llm,
-                tts,
-                transport.output(),
-                audiobuffer,  # used to buffer the audio in the pipeline
-                context_aggregator.assistant(),
-            ]
-        )
-
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
-
-        @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)
-
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            await audiobuffer.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()
-
-        runner = PipelineRunner()
-
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/chatbot-audio-recording/env.example

@@ -1,4 +0,0 @@
-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...

examples/chatbot-audio-recording/requirements.txt

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

examples/chatbot-audio-recording/runner.py

@@ -1,56 +0,0 @@
-#
-# 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)
-    return (url, token)

examples/chatbot-audio-recording/server.py

@@ -1,139 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-import subprocess
-from contextlib import asynccontextmanager
-
-import aiohttp
-from dotenv import load_dotenv
-from fastapi import FastAPI, HTTPException, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse, RedirectResponse
-
-from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
-
-MAX_BOTS_PER_ROOM = 1
-
-# Bot sub-process dict for status reporting and concurrency control
-bot_procs = {}
-
-daily_helpers = {}
-
-load_dotenv(override=True)
-
-
-def cleanup():
-    # Clean up function, just to be extra safe
-    for entry in bot_procs.values():
-        proc = entry[0]
-        proc.terminate()
-        proc.wait()
-
-
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    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()
-
-
-app = FastAPI(lifespan=lifespan)
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-
-@app.get("/")
-async def start_agent(request: Request):
-    print(f"!!! Creating room")
-    room = await daily_helpers["rest"].create_room(DailyRoomParams())
-    print(f"!!! Room URL: {room.url}")
-    # Ensure the room property is present
-    if not room.url:
-        raise HTTPException(
-            status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
-        )
-
-    # Check if there is already an existing process running in this room
-    num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
-    )
-    if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
-
-    # Get the token for the room
-    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}")
-
-    # Spawn a new agent, and join the user session
-    # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
-    try:
-        proc = subprocess.Popen(
-            [f"python3 -m bot -u {room.url} -t {token}"],
-            shell=True,
-            bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__)),
-        )
-        bot_procs[proc.pid] = (proc, room.url)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
-
-    return RedirectResponse(room.url)
-
-
-@app.get("/status/{pid}")
-def get_status(pid: int):
-    # Look up the subprocess
-    proc = bot_procs.get(pid)
-
-    # If the subprocess doesn't exist, return an error
-    if not proc:
-        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
-
-    # Check the status of the subprocess
-    if proc[0].poll() is None:
-        status = "running"
-    else:
-        status = "finished"
-
-    return JSONResponse({"bot_id": pid, "status": status})
-
-
-if __name__ == "__main__":
-    import uvicorn
-
-    default_host = os.getenv("HOST", "0.0.0.0")
-    default_port = int(os.getenv("FAST_API_PORT", "7860"))
-
-    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str, default=default_host, help="Host address")
-    parser.add_argument("--port", type=int, default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true", help="Reload code on change")
-
-    config = parser.parse_args()
-
-    uvicorn.run(
-        "server:app",
-        host=config.host,
-        port=config.port,
-        reload=config.reload,
-    )

examples/deployment/flyio-example/Dockerfile

@@ -1,13 +0,0 @@
-FROM python:3.11-bullseye
-
-# Open port 7860 for http service
-ENV FAST_API_PORT=7860
-EXPOSE 7860
-
-# Install Python dependencies
-COPY *.py .
-COPY ./requirements.txt requirements.txt
-RUN pip3 install --no-cache-dir --upgrade -r requirements.txt
-
-# Start the FastAPI server
-CMD python3 bot_runner.py --port ${FAST_API_PORT}

examples/deployment/flyio-example/README.md

@@ -1,39 +0,0 @@
-# Fly.io deployment example
-
-This project modifies the `bot_runner.py` server to launch a new machine for each user session. This is a recommended approach for production vs. running shell processess as your deployment will quickly run out of system resources under load.
-
-For this example, we are using Daily as a WebRTC transport and provisioning a new room and token for each session. You can use another transport, such as WebSockets, by modifying the `bot.py` and `bot_runner.py` files accordingly.
-
-## Setting up your fly.io deployment
-
-### Create your fly.toml file
-
-You can copy the `example-fly.toml` as a reference. Be sure to change the app name to something unique.
-
-### Create your .env file
-
-Copy the base `env.example` to `.env` and enter the necessary API keys.
-
-`FLY_APP_NAME` should match that in the `fly.toml` file.
-
-### Launch a new fly.io project
-
-`fly launch` or `fly launch --org your-org-name`
-
-### Set the necessary app secrets from your .env
-
-Note: you can do this manually via the fly.io dashboard under the "secrets" sub-section of your deployment (e.g. "https://fly.io/apps/fly-app-name/secrets") or run the following terminal command:
-
-`cat .env | tr '\n' ' ' | xargs flyctl secrets set`
-
-### Deploy your machine
-
-`fly deploy`
-
-## Connecting to your bot
-
-Send a post request to your running fly.io instance:
-
-`curl --location --request POST 'https://YOUR_FLY_APP_NAME/'`
-
-This request will wait until the machine enters into a `starting` state, before returning the a room URL and token to join.

examples/deployment/flyio-example/bot.py

@@ -1,102 +0,0 @@
-import argparse
-import asyncio
-import os
-import sys
-
-from dotenv import load_dotenv
-from loguru import logger
-
-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.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")
-
-daily_api_key = os.getenv("DAILY_API_KEY", "")
-daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
-
-
-async def main(room_url: str, token: str):
-    transport = DailyTransport(
-        room_url,
-        token,
-        "Chatbot",
-        DailyParams(
-            api_url=daily_api_url,
-            api_key=daily_api_key,
-            audio_in_enabled=True,
-            audio_out_enabled=True,
-            camera_out_enabled=False,
-            vad_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(),
-            transcription_enabled=True,
-        ),
-    )
-
-    tts = ElevenLabsTTSService(
-        api_key=os.getenv("ELEVENLABS_API_KEY", ""),
-        voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
-    )
-
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-
-    messages = [
-        {
-            "role": "system",
-            "content": "You are Chatbot, a friendly, helpful robot. Your output will be converted to audio so don't include special characters other than '!' or '?' in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by saying hello.",
-        },
-    ]
-
-    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, PipelineParams(allow_interruptions=True))
-
-    @transport.event_handler("on_first_participant_joined")
-    async def on_first_participant_joined(transport, participant):
-        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):
-        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__":
-    parser = argparse.ArgumentParser(description="Pipecat Bot")
-    parser.add_argument("-u", type=str, help="Room URL")
-    parser.add_argument("-t", type=str, help="Token")
-    config = parser.parse_args()
-
-    asyncio.run(main(config.u, config.t))

examples/deployment/flyio-example/bot_runner.py

@@ -1,209 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-import subprocess
-from contextlib import asynccontextmanager
-
-import aiohttp
-from dotenv import load_dotenv
-from fastapi import FastAPI, HTTPException, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
-
-from pipecat.transports.services.helpers.daily_rest import (
-    DailyRESTHelper,
-    DailyRoomObject,
-    DailyRoomParams,
-    DailyRoomProperties,
-)
-
-load_dotenv(override=True)
-
-
-# ------------ Configuration ------------ #
-
-MAX_SESSION_TIME = 5 * 60  # 5 minutes
-REQUIRED_ENV_VARS = [
-    "DAILY_API_KEY",
-    "OPENAI_API_KEY",
-    "ELEVENLABS_API_KEY",
-    "ELEVENLABS_VOICE_ID",
-    "FLY_API_KEY",
-    "FLY_APP_NAME",
-]
-
-FLY_API_HOST = os.getenv("FLY_API_HOST", "https://api.machines.dev/v1")
-FLY_APP_NAME = os.getenv("FLY_APP_NAME", "pipecat-fly-example")
-FLY_API_KEY = os.getenv("FLY_API_KEY", "")
-FLY_HEADERS = {"Authorization": f"Bearer {FLY_API_KEY}", "Content-Type": "application/json"}
-
-daily_helpers = {}
-
-
-# ----------------- API ----------------- #
-
-
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    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()
-
-
-app = FastAPI(lifespan=lifespan)
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# ----------------- Main ----------------- #
-
-
-async def spawn_fly_machine(room_url: str, token: str):
-    async with aiohttp.ClientSession() as session:
-        # Use the same image as the bot runner
-        async with session.get(
-            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS
-        ) as r:
-            if r.status != 200:
-                text = await r.text()
-                raise Exception(f"Unable to get machine info from Fly: {text}")
-
-            data = await r.json()
-            image = data[0]["config"]["image"]
-
-        # Machine configuration
-        cmd = f"python3 bot.py -u {room_url} -t {token}"
-        cmd = cmd.split()
-        worker_props = {
-            "config": {
-                "image": image,
-                "auto_destroy": True,
-                "init": {"cmd": cmd},
-                "restart": {"policy": "no"},
-                "guest": {"cpu_kind": "shared", "cpus": 1, "memory_mb": 1024},
-            },
-        }
-
-        # Spawn a new machine instance
-        async with session.post(
-            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS, json=worker_props
-        ) as r:
-            if r.status != 200:
-                text = await r.text()
-                raise Exception(f"Problem starting a bot worker: {text}")
-
-            data = await r.json()
-            # Wait for the machine to enter the started state
-            vm_id = data["id"]
-
-        async with session.get(
-            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines/{vm_id}/wait?state=started",
-            headers=FLY_HEADERS,
-        ) as r:
-            if r.status != 200:
-                text = await r.text()
-                raise Exception(f"Bot was unable to enter started state: {text}")
-
-    print(f"Machine joined room: {room_url}")
-
-
-@app.post("/")
-async def start_bot(request: Request) -> JSONResponse:
-    try:
-        data = await request.json()
-        # Is this a webhook creation request?
-        if "test" in data:
-            return JSONResponse({"test": True})
-    except Exception as e:
-        pass
-
-    # Use specified room URL, or create a new one if not specified
-    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", "")
-
-    if not room_url:
-        params = DailyRoomParams(properties=DailyRoomProperties())
-        try:
-            room: DailyRoomObject = await daily_helpers["rest"].create_room(params=params)
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=f"Unable to provision room {e}")
-    else:
-        # Check passed room URL exists, we should assume that it already has a sip set up
-        try:
-            room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
-        except Exception:
-            raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
-
-    # Give the agent a token to join the session
-    token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
-
-    if not room or not token:
-        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room_url}")
-
-    # Launch a new fly.io machine, or run as a shell process (not recommended)
-    run_as_process = os.getenv("RUN_AS_PROCESS", False)
-
-    if run_as_process:
-        try:
-            subprocess.Popen(
-                [f"python3 -m bot -u {room.url} -t {token}"],
-                shell=True,
-                bufsize=1,
-                cwd=os.path.dirname(os.path.abspath(__file__)),
-            )
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
-    else:
-        try:
-            await spawn_fly_machine(room.url, token)
-        except Exception as e:
-            raise HTTPException(status_code=500, detail=f"Failed to spawn VM: {e}")
-
-    # Grab a token for the user to join with
-    user_token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
-
-    return JSONResponse(
-        {
-            "room_url": room.url,
-            "token": user_token,
-        }
-    )
-
-
-if __name__ == "__main__":
-    # Check environment variables
-    for env_var in REQUIRED_ENV_VARS:
-        if env_var not in os.environ:
-            raise Exception(f"Missing environment variable: {env_var}.")
-
-    parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
-    parser.add_argument(
-        "--host", type=str, default=os.getenv("HOST", "0.0.0.0"), help="Host address"
-    )
-    parser.add_argument("--port", type=int, default=os.getenv("PORT", 7860), help="Port number")
-    parser.add_argument(
-        "--reload", action="store_true", default=False, help="Reload code on change"
-    )
-
-    config = parser.parse_args()
-
-    try:
-        import uvicorn
-
-        uvicorn.run("bot_runner:app", host=config.host, port=config.port, reload=config.reload)
-    except KeyboardInterrupt:
-        print("Pipecat runner shutting down...")

examples/deployment/flyio-example/env.example

@@ -1,8 +0,0 @@
-DAILY_API_KEY=
-DAILY_SAMPLE_ROOM_URL= # Enter a Daily room URL to use a set room URL each time (useful for local testing)
-OPENAI_API_KEY=
-ELEVENLABS_API_KEY=
-ELEVENLABS_VOICE_ID=
-FLY_API_KEY=
-FLY_APP_NAME=
-RUN_AS_PROCESS= # Spawn fly.io machine for each session or run as local process

examples/deployment/flyio-example/example-fly.toml

@@ -1,25 +0,0 @@
-# fly.toml app configuration file generated for pipecat-fly-example on 2024-07-01T15:04:53+01:00
-#
-# See https://fly.io/docs/reference/configuration/ for information about how to use this file.
-#
-
-app = 'pipecat-fly-example'
-primary_region = 'sjc'
-
-[build]
-
-[env]
-  FLY_APP_NAME = 'pipecat-fly-example'
-
-[http_service]
-  internal_port = 7860
-  force_https = true
-  auto_stop_machines = true
-  auto_start_machines = true
-  min_machines_running = 0
-  processes = ['app']
-
-[[vm]]
-  memory = 512
-  cpu_kind = 'shared'
-  cpus = 1

examples/deployment/flyio-example/requirements.txt

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

examples/deployment/modal-example/.gitignore

@@ -1,91 +0,0 @@
-# Python
-__pycache__/
-*.py[cod]
-*$py.class
-*.so
-.Python
-build/
-dist/
-*.egg-info/
-*.egg
-.installed.cfg
-.eggs/
-downloads/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-share/python-wheels/
-MANIFEST
-
-# Virtual Environments
-venv/
-env/
-.env
-.venv/
-ENV/
-env.bak/
-venv.bak/
-
-# IDE
-.idea/
-.vscode/
-.spyderproject
-.spyproject
-.ropeproject
-
-# Testing and Coverage
-.coverage
-.coverage.*
-htmlcov/
-.pytest_cache/
-.tox/
-.nox/
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-.hypothesis/
-cover/
-
-# Logs and Databases
-*.log
-*.db
-db.sqlite3
-db.sqlite3-journal
-pip-log.txt
-
-# System Files
-.DS_Store
-Thumbs.db
-desktop.ini
-*.swp
-*.swo
-*.bak
-*.tmp
-*~
-
-# Build and Documentation
-docs/_build/
-.pybuilder/
-target/
-instance/
-.webassets-cache
-.pdm.toml
-.pdm-python
-.pdm-build/
-__pypackages__/
-
-# Other
-*.mo
-*.pot
-*.sage.py
-.mypy_cache/
-.dmypy.json
-dmypy.json
-.pyre/
-.pytype/
-cython_debug/
-.ipynb_checkpoints

examples/deployment/modal-example/README.md

@@ -1,37 +0,0 @@
-# Deploying Pipecat to Modal.com
-
-Barebones deployment example for [modal.com](https://www.modal.com)
-
-1. Install dependencies
-
-```bash
-python -m venv venv
-source venv/bin/active # or OS equivalent
-pip install -r requirements.txt
-```
-
-2. Setup .env
-
-```bash
-cp env.example .env
-```
-
-Alternatively, you can configure your Modal app to use [secrets](https://modal.com/docs/guide/secrets)
-
-3. Test the app locally
-
-```bash
-modal serve app.py
-```
-
-4. Deploy to production
-
-```bash
-modal deploy app.py
-```
-
-## Configuration options
-
-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.
-
-It has been configured to only allow a concurrency of 1 (`max_inputs=1`) as each user will require their own running function.

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,
-        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/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/foundational/01-say-one-thing-piper.py

@@ -0,0 +1,70 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.piper.tts import PiperTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        tts = PiperTTSService(
+            base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000
+        )
+
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
+
+        # Register an event handler so we can play the audio when the client joins
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+        await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

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

@@ -0,0 +1,71 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.rime.tts import RimeHttpTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        tts = RimeHttpTTSService(
+            api_key=os.getenv("RIME_API_KEY", ""),
+            voice_id="rex",
+            aiohttp_session=session,
+        )
+
+        task = PipelineTask(
+            Pipeline([tts, transport.output()]),
+            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        )
+
+        # Register an event handler so we can play the audio when the client joins
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+        await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

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

@@ -4,56 +4,65 @@
 # 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.frames.frames import EndFrame, TTSSpeakFrame
 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.transports.services.daily import DailyParams, DailyTransport
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
 
 load_dotenv(override=True)
 
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
 
 
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, _) = await configure(session)
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
 
-        transport = DailyTransport(
-            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
-        )
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
 
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
+    task = PipelineTask(
+        Pipeline([tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
 
-        runner = PipelineRunner()
+    # Register an event handler so we can play the audio when the client joins
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
-        task = PipelineTask(Pipeline([tts, transport.output()]))
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-        # Register an event handler so we can play the audio when the
-        # participant joins.
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            participant_name = participant.get("info", {}).get("userName", "")
-            await task.queue_frames(
-                [TTSSpeakFrame(f"Hello there, {participant_name}!"), EndFrame()]
-            )
+    await runner.run(task)
 
-        await runner.run(task)
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
 
 
 if __name__ == "__main__":
-    asyncio.run(main())
+    from pipecat.runner.run import main
+
+    main()

examples/foundational/01a-local-audio.py

@@ -15,7 +15,7 @@ from pipecat.frames.frames import EndFrame, TTSSpeakFrame
 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.local.audio import LocalAudioTransport, LocalAudioTransportParams
 
 load_dotenv(override=True)
@@ -29,7 +29,7 @@ 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
     )
 
     pipeline = Pipeline([tts, transport.output()])