Compare commits
1 Commits
mb/fix-qui
...
jpt/runner
| Author | SHA1 | Date | |
|---|---|---|---|
|
2b1f056aa7 |
60
.github/workflows/android.yaml
vendored
Normal file
60
.github/workflows/android.yaml
vendored
Normal file
@@ -0,0 +1,60 @@
|
||||
name: android
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||||
|
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on:
|
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push:
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branches:
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||||
- main
|
||||
paths:
|
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- "examples/simple-chatbot/client/android/**"
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- "examples/p2p-webrtc/video-transform/client/android/**"
|
||||
pull_request:
|
||||
branches:
|
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- "**"
|
||||
paths:
|
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- "examples/simple-chatbot/client/android/**"
|
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- "examples/p2p-webrtc/video-transform/client/android/**"
|
||||
workflow_dispatch:
|
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inputs:
|
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sdk_git_ref:
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type: string
|
||||
description: "Which git ref of the app to build"
|
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|
||||
concurrency:
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group: build-android-${{ github.event.pull_request.number || github.ref }}
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cancel-in-progress: true
|
||||
|
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jobs:
|
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sdk:
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name: "Demo apps"
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repo
|
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uses: actions/checkout@v4
|
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with:
|
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ref: ${{ github.event.inputs.sdk_git_ref || github.ref }}
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|
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- name: "Install Java"
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uses: actions/setup-java@v4
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with:
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distribution: 'temurin'
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java-version: '17'
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|
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- name: "Example app: Simple Chatbot"
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working-directory: examples/simple-chatbot/client/android
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run: ./gradlew :simple-chatbot-client:assembleDebug
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|
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- name: Upload Simple Chatbot APK
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uses: actions/upload-artifact@v4
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with:
|
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name: Simple Chatbot Android Client
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path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk
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|
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- name: "Example app: Small WebRTC Client"
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working-directory: examples/p2p-webrtc/video-transform/client/android
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run: ./gradlew :small-webrtc-client:assembleDebug
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|
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- name: Upload Small WebRTC APK
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uses: actions/upload-artifact@v4
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with:
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name: Small WebRTC Android Client
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path: examples/p2p-webrtc/video-transform/client/android/small-webrtc-client/build/outputs/apk/debug/small-webrtc-client-debug.apk
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||||
34
.github/workflows/build.yaml
vendored
34
.github/workflows/build.yaml
vendored
@@ -21,20 +21,24 @@ jobs:
|
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runs-on: ubuntu-latest
|
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steps:
|
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- uses: actions/checkout@v4
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|
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- name: Install uv
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uses: astral-sh/setup-uv@v3
|
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with:
|
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version: "latest"
|
||||
|
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- name: Set up Python
|
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run: uv python install 3.10
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|
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- name: Install development dependencies
|
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run: uv sync --group dev
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|
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id: setup_python
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uses: actions/setup-python@v4
|
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with:
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python-version: '3.10'
|
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- name: Setup virtual environment
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run: |
|
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python -m venv .venv
|
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- name: Install basic Python dependencies
|
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run: |
|
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source .venv/bin/activate
|
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python -m pip install --upgrade pip
|
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pip install -r dev-requirements.txt
|
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- name: Build project
|
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run: uv build
|
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|
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- name: Install project in editable mode
|
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run: uv pip install --editable .
|
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run: |
|
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source .venv/bin/activate
|
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python -m build
|
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- name: Install project and other Python dependencies
|
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run: |
|
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source .venv/bin/activate
|
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pip install --editable .
|
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|
||||
37
.github/workflows/coverage.yaml
vendored
37
.github/workflows/coverage.yaml
vendored
@@ -18,28 +18,35 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout repo
|
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uses: actions/checkout@v4
|
||||
|
||||
- name: Install uv
|
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uses: astral-sh/setup-uv@v3
|
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with:
|
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version: "latest"
|
||||
|
||||
- name: Set up Python
|
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run: uv python install 3.12
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|
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id: setup_python
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uses: actions/setup-python@v4
|
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with:
|
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python-version: "3.10"
|
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- name: Cache virtual environment
|
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uses: actions/cache@v3
|
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with:
|
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# We are hashing dev-requirements.txt and test-requirements.txt which
|
||||
# contain all dependencies needed to run the tests.
|
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key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
|
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path: .venv
|
||||
- name: Install system packages
|
||||
id: install_system_packages
|
||||
run: |
|
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sudo apt-get install -y portaudio19-dev
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|
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- name: Install dependencies
|
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- name: Setup virtual environment
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run: |
|
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uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
|
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|
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python -m venv .venv
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- name: Install basic Python dependencies
|
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run: |
|
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source .venv/bin/activate
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python -m pip install --upgrade pip
|
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pip install -r dev-requirements.txt -r test-requirements.txt
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- name: Run tests with coverage
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run: |
|
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uv run coverage run
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uv run coverage xml
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||||
|
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source .venv/bin/activate
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coverage run
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coverage xml
|
||||
- name: Upload coverage to Codecov
|
||||
uses: codecov/codecov-action@v5
|
||||
with:
|
||||
|
||||
31
.github/workflows/format.yaml
vendored
31
.github/workflows/format.yaml
vendored
@@ -22,22 +22,25 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout repo
|
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uses: actions/checkout@v4
|
||||
|
||||
- name: Install uv
|
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uses: astral-sh/setup-uv@v3
|
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with:
|
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version: "latest"
|
||||
|
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- name: Set up Python
|
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run: uv python install 3.10
|
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|
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- name: Install development dependencies
|
||||
run: uv sync --group dev
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|
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uses: actions/setup-python@v4
|
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with:
|
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python-version: "3.10"
|
||||
- name: Setup virtual environment
|
||||
run: |
|
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python -m venv .venv
|
||||
- name: Install development Python dependencies
|
||||
run: |
|
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source .venv/bin/activate
|
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python -m pip install --upgrade pip
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pip install -r dev-requirements.txt
|
||||
- name: Ruff formatter
|
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id: ruff-format
|
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run: uv run ruff format --diff
|
||||
|
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run: |
|
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source .venv/bin/activate
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ruff format --diff
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- name: Ruff linter (all rules)
|
||||
id: ruff-check
|
||||
run: uv run ruff check
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
ruff check
|
||||
|
||||
24
.github/workflows/publish.yaml
vendored
24
.github/workflows/publish.yaml
vendored
@@ -17,17 +17,23 @@ jobs:
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ github.event.inputs.gitref }}
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
version: "latest"
|
||||
- name: Set up Python
|
||||
run: uv python install 3.10
|
||||
- name: Install development dependencies
|
||||
run: uv sync --group dev
|
||||
id: setup_python
|
||||
uses: actions/setup-python@v4
|
||||
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
|
||||
- name: Build project
|
||||
run: uv build
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
python -m build
|
||||
- name: Upload wheels
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
|
||||
25
.github/workflows/publish_test.yaml
vendored
25
.github/workflows/publish_test.yaml
vendored
@@ -12,16 +12,23 @@ jobs:
|
||||
with:
|
||||
fetch-tags: true
|
||||
fetch-depth: 100
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
version: "latest"
|
||||
- name: Set up Python
|
||||
run: uv python install 3.10
|
||||
- name: Install development dependencies
|
||||
run: uv sync --group dev
|
||||
id: setup_python
|
||||
uses: actions/setup-python@v4
|
||||
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
|
||||
- name: Build project
|
||||
run: uv build
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
python -m build
|
||||
- name: Upload wheels
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
@@ -31,7 +38,7 @@ 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
|
||||
|
||||
61
.github/workflows/python-compatibility.yaml
vendored
61
.github/workflows/python-compatibility.yaml
vendored
@@ -1,61 +0,0 @@
|
||||
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')"
|
||||
51
.github/workflows/sync-quickstart.yaml
vendored
51
.github/workflows/sync-quickstart.yaml
vendored
@@ -1,51 +0,0 @@
|
||||
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: ${{ github.sha }}
|
||||
"
|
||||
git push
|
||||
else
|
||||
echo "No changes to sync"
|
||||
fi
|
||||
34
.github/workflows/tests.yaml
vendored
34
.github/workflows/tests.yaml
vendored
@@ -22,23 +22,31 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout repo
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
version: "latest"
|
||||
|
||||
- name: Set up Python
|
||||
run: uv python install 3.12
|
||||
|
||||
id: setup_python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
- name: Cache virtual environment
|
||||
uses: actions/cache@v3
|
||||
with:
|
||||
# We are hashing dev-requirements.txt and test-requirements.txt which
|
||||
# contain all dependencies needed to run the tests.
|
||||
key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
|
||||
path: .venv
|
||||
- name: Install system packages
|
||||
id: install_system_packages
|
||||
run: |
|
||||
sudo apt-get install -y portaudio19-dev
|
||||
|
||||
- name: Install dependencies
|
||||
- name: Setup virtual environment
|
||||
run: |
|
||||
uv sync --group dev --extra anthropic --extra aws --extra google --extra langchain
|
||||
|
||||
python -m venv .venv
|
||||
- name: Install basic Python dependencies
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r dev-requirements.txt -r test-requirements.txt
|
||||
- name: Test with pytest
|
||||
run: |
|
||||
uv run pytest
|
||||
source .venv/bin/activate
|
||||
pytest
|
||||
|
||||
7
.gitignore
vendored
7
.gitignore
vendored
@@ -31,6 +31,8 @@ MANIFEST
|
||||
fly.toml
|
||||
|
||||
# Examples
|
||||
examples/telnyx-chatbot/templates/streams.xml
|
||||
examples/twilio-chatbot/templates/streams.xml
|
||||
examples/**/node_modules/
|
||||
examples/**/.expo/
|
||||
examples/**/dist/
|
||||
@@ -48,7 +50,4 @@ examples/**/web-build/
|
||||
|
||||
# Documentation
|
||||
docs/api/_build/
|
||||
docs/api/api
|
||||
|
||||
# uv
|
||||
.python-version
|
||||
docs/api/api
|
||||
@@ -1,6 +1,6 @@
|
||||
repos:
|
||||
- repo: https://github.com/astral-sh/ruff-pre-commit
|
||||
rev: v0.12.1
|
||||
rev: v0.9.7
|
||||
hooks:
|
||||
- id: ruff
|
||||
language_version: python3
|
||||
|
||||
@@ -9,14 +9,22 @@ build:
|
||||
- python3-dev
|
||||
- libasound2-dev
|
||||
jobs:
|
||||
post_install:
|
||||
- pip install uv
|
||||
- UV_PROJECT_ENVIRONMENT=$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
|
||||
pre_build:
|
||||
- python -m pip install --upgrade pip
|
||||
- pip install wheel setuptools
|
||||
post_build:
|
||||
- echo "Build completed"
|
||||
|
||||
sphinx:
|
||||
configuration: docs/api/conf.py
|
||||
fail_on_warning: false
|
||||
|
||||
python:
|
||||
install:
|
||||
- requirements: docs/api/requirements.txt
|
||||
- method: pip
|
||||
path: .
|
||||
|
||||
search:
|
||||
ranking:
|
||||
api/*: 5
|
||||
|
||||
715
CHANGELOG.md
715
CHANGELOG.md
@@ -7,638 +7,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
## Added
|
||||
|
||||
- Added `pipecat.extensions.ivr` for automated IVR system navigation with
|
||||
configurable goals and conversation handling. Supports DTMF input, verbal
|
||||
responses, and intelligent menu traversal.
|
||||
|
||||
Basic usage:
|
||||
|
||||
```python
|
||||
from pipecat.extensions.ivr.ivr_navigator import IVRNavigator
|
||||
|
||||
# Create IVR navigator with your goal
|
||||
ivr_navigator = IVRNavigator(
|
||||
llm=llm_service,
|
||||
ivr_prompt="Navigate to billing department to dispute a charge"
|
||||
)
|
||||
|
||||
# Handle different outcomes
|
||||
@ivr_navigator.event_handler("on_conversation_detected")
|
||||
async def on_conversation(processor, conversation_history):
|
||||
# Switch to normal conversation mode
|
||||
pass
|
||||
|
||||
@ivr_navigator.event_handler("on_ivr_status_changed")
|
||||
async def on_ivr_status(processor, status):
|
||||
if status == IVRStatus.COMPLETED:
|
||||
# End pipeline, transfer call, or start bot conversation
|
||||
elif status == IVRStatus.STUCK:
|
||||
# Handle navigation failure
|
||||
```
|
||||
|
||||
- `BaseOutputTransport` now implements `write_dtmf()` by loading DTMF audio and
|
||||
sending it through the transport. This makes sending DTMF generic across all
|
||||
output transports.
|
||||
|
||||
- Added new config parameters to `GladiaSTTService`.
|
||||
- PreProcessingConfig > `audio_enhancer` to enhance audio quality.
|
||||
- CustomVocabularyItem > `pronunciations` and `language` to specify special pronunciations and in which language it will be pronounced.
|
||||
|
||||
## Changed
|
||||
|
||||
- `pipecat.frames.frames.KeypadEntry` is deprecated and has been moved to
|
||||
`pipecat.audio.dtmf.types.KeypadEntry`.
|
||||
|
||||
## Removed
|
||||
|
||||
- Remove `StopInterruptionFrame`. This was a legacy frame that was not being
|
||||
used really anywhere and it didn't provide any useful meaning. It was only
|
||||
pushed after `UserStoppedSpeakingFrame`, so developers can just use
|
||||
`UserStoppedSpeakingFrame`.
|
||||
|
||||
- `DailyTransport.write_dtmf()` has been removed in favor of the generic
|
||||
`BaseOutputTransport.write_dtmf()`.
|
||||
|
||||
- Remove deprecated `DailyTransport.send_dtmf()`.
|
||||
|
||||
## Deprecated
|
||||
|
||||
- `pipecat.frames.frames.KeypadEntry` is deprecated use
|
||||
`pipecat.audio.dtmf.types.KeypadEntry` instead.
|
||||
|
||||
## Fixed
|
||||
|
||||
- Fixed an issue where `PipelineTask` was not cleaning up the observers.
|
||||
|
||||
## [0.0.82] - 2025-08-28
|
||||
|
||||
### Added
|
||||
|
||||
- Added a new `LLMRunFrame` to trigger an LLM response:
|
||||
|
||||
```python
|
||||
await task.queue_frames([LLMRunFrame()])
|
||||
```
|
||||
|
||||
This replaces `OpenAILLMContextFrame`, which you’d previously typically use
|
||||
like this:
|
||||
|
||||
```python
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
```
|
||||
|
||||
Use this way of kicking off your conversation when you’ve already initialized
|
||||
your context and are simply instructing the bot when to go:
|
||||
|
||||
```python
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
# ...
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([LLMRunFrame()])
|
||||
```
|
||||
|
||||
Note that if you want to add new messages when kicking off the conversation,
|
||||
you could use `LLMMessagesAppendFrame` with `run_llm=True` instead:
|
||||
|
||||
```python
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([LLMMessagesAppendFrame(new_messages, run_llm=True)])
|
||||
```
|
||||
|
||||
In the rare case you don’t have a context aggregator in your pipeline, then
|
||||
you may continue using a context frame.
|
||||
|
||||
- Added support for switching between audio+text to text-only modes within the
|
||||
same pipeline. This is done by pushing
|
||||
`LLMConfigureOutputFrame(skip_tts=True)` to enter text-only mode, and
|
||||
disabling it to return to audio+text. The LLM will still generate tokens and
|
||||
add them to the context, but they will not be sent to TTS.
|
||||
|
||||
- Added `skip_tts` field to `TextFrame`. This lets a text frame bypass TTS while
|
||||
still being included in the LLM context. Useful for cases like structured text
|
||||
that isn’t meant to be spoken but should still contribute to context.
|
||||
|
||||
- Added a `cancel_timeout_secs` argument to `PipelineTask` which defines how
|
||||
long the pipeline has to complete cancellation. When `PipelineTask.cancel()`
|
||||
is called, a `CancelFrame` is pushed through the pipeline and must reach the
|
||||
end. If it does not reach the end within the specified time, a warning is
|
||||
shown and the wait is aborted.
|
||||
|
||||
- Added a new "universal" (LLM-agnostic) `LLMContext` and accompanying
|
||||
`LLMContextAggregatorPair`, which will eventually replace `OpenAILLMContext`
|
||||
(and the other under-the-hood contexts) and the other context aggregators.
|
||||
The new universal `LLMContext` machinery allows a single context to be shared
|
||||
between different LLMs, enabling runtime LLM switching and scenarios like
|
||||
failover.
|
||||
|
||||
From the developer's point of view, switching to using the new universal
|
||||
context machinery will usually be a matter of going from this:
|
||||
|
||||
```python
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
```
|
||||
|
||||
To this:
|
||||
|
||||
```python
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
```
|
||||
|
||||
To start, the universal `LLMContext` is supported with the following LLM
|
||||
services:
|
||||
|
||||
- `OpenAILLMService`
|
||||
- `GoogleLLMService`
|
||||
|
||||
- Added a new `LLMSwitcher` class to enable runtime LLM switching, built atop a
|
||||
new generic `ServiceSwitcher`.
|
||||
|
||||
Switchers take a switching strategy. The first available strategy is
|
||||
`ServiceSwitcherStrategyManual`.
|
||||
|
||||
To switch LLMs at runtime, the LLMs must be sharing one instance of the new
|
||||
universal `LLMContext` (see above bullet).
|
||||
|
||||
```python
|
||||
# Instantiate your LLM services
|
||||
llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
|
||||
|
||||
# Instantiate a switcher
|
||||
# (ServiceSwitcherStrategyManual defaults to OpenAI, as it's first in the list)
|
||||
llm_switcher = LLMSwitcher(
|
||||
llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
|
||||
# Create your pipeline
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
context_aggregator.user(),
|
||||
llm_switcher,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
|
||||
|
||||
# ...
|
||||
# Whenever is appropriate, switch LLMs!
|
||||
await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
|
||||
```
|
||||
|
||||
- Added an `LLMService.run_inference()` method to LLM services to enable
|
||||
direct, out-of-band (i.e. out-of-pipeline) inference.
|
||||
|
||||
### Changed
|
||||
|
||||
- Updated `daily-python` to 0.19.8.
|
||||
|
||||
- `PipelineTask` now waits for `StartFrame` to reach the end of the pipeline
|
||||
before pushing any other frames.
|
||||
|
||||
- Updated `CartesiaTTSService` and `CartesiaHttpTTSService` to align with
|
||||
Cartesia's changes for the `speed` parameter. It now takes only an enum of
|
||||
`slow`, `normal`, or `fast`.
|
||||
|
||||
- Added support to `AWSBedrockLLMService` for setting authentication
|
||||
credentials through environment variables.
|
||||
|
||||
- Updated `SarvamTTSService` to use WebSocket streaming for real-time audio
|
||||
generation with multiple Indian languages, with HTTP support still available
|
||||
via `SarvamHttpTTSService`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an RTVI issue that was causing frames to be pushed before pipeline was
|
||||
properly initialized.
|
||||
|
||||
- Fixed some `get_messages_for_logging()` that were returning a JSON string
|
||||
instead of a list.
|
||||
|
||||
- Fixed a `DailyTransport` issue that prevented DTMF tones from being sent.
|
||||
|
||||
- Fixed a missing import in `SentryMetrics`.
|
||||
|
||||
- Fixed `AWSPollyTTSService` to support AWS credential provider chain (IAM
|
||||
roles, IRSA, instance profiles) instead of requiring explicit environment
|
||||
variables.
|
||||
|
||||
- Fixed a `CartesiaTTSService` issue that was causing the application to hang
|
||||
after Cartesia's 5 minutes timed out.
|
||||
|
||||
- Fixed an issue preventing `SpeechmaticsSTTService` from transcribing audio.
|
||||
|
||||
## [0.0.81] - 2025-08-25
|
||||
|
||||
### Added
|
||||
|
||||
- Added `pipecat.extensions.voicemail`, a module for detecting voicemail vs.
|
||||
live conversation, primarily intended for use in outbound calling scenarios.
|
||||
The voicemail module is optimized for text LLMs only.
|
||||
|
||||
- Added new frames to the `idle_timeout_frames` arg: `TranscriptionFrame`,
|
||||
`InterimTranscriptionFrame`, `UserStartedSpeakingFrame`, and
|
||||
`UserStoppedSpeakingFrame`. These additions serve as indicators of user
|
||||
activity in the pipeline idle detection logic.
|
||||
|
||||
- Allow passing custom pipeline sink and source processors to a
|
||||
`Pipeline`. Pipeline source and sink processors are used to know and control
|
||||
what's coming in and out of a `Pipeline` processor.
|
||||
|
||||
- Added `FrameProcessor.pause_processing_system_frames()` and
|
||||
`FrameProcessor.resume_processing_system_frames()`. These allow to pause and
|
||||
resume the processing of system frame.
|
||||
|
||||
- Added new `on_process_frame()` observer method which makes it possible to know
|
||||
when a frame is being processed.
|
||||
|
||||
- Added new `FrameProcessor.entry_processor()` method. This allows you to access
|
||||
the first non-compound processor in a pipeline.
|
||||
|
||||
- Added `FrameProcessor` properties `processors`, `next` and `previous`.
|
||||
|
||||
- `ElevenLabsTTSService` now supports additional runtime changes to the `model`,
|
||||
`language`, and `voice_settings` parameters.
|
||||
|
||||
- Added `apply_text_normalization` support to `ElevenLabsTTSService` and
|
||||
`ElevenLabsHttpTTSService`.
|
||||
|
||||
- Added `MistralLLMService`, using Mistral's chat completion API.
|
||||
|
||||
- Added the ability to retry executing a chat completion after a timeout period
|
||||
for `OpenAILLMService` and its subclasses, `AnthropicLLMService`, and
|
||||
`AWSBedrockLLMService`. The LLM services accept new args:
|
||||
`retry_timeout_secs` and `retry_on_timeout`. This feature is disabled by
|
||||
default.
|
||||
|
||||
### Changed
|
||||
|
||||
- Updated `daily-python` to 0.19.7.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- `FrameProcessor.wait_for_task()` is deprecated. Use `await task` or
|
||||
`await asyncio.wait_for(task, timeout)` instead.
|
||||
|
||||
### Removed
|
||||
|
||||
- Watchdog timers have been removed. They were introduced in 0.0.72 to help
|
||||
diagnose pipeline freezes. Unfortunately, they proved ineffective since they
|
||||
required developers to use Pipecat-specific queues, iterators, and events to
|
||||
correctly reset the timer, which limited their usefulness and added friction.
|
||||
|
||||
- Removed unused `FrameProcessor.set_parent()` and
|
||||
`FrameProcessor.get_parent()`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue that would cause `PipelineRunner` and `PipelineTask` to not
|
||||
handle external asyncio task cancellation properly.
|
||||
|
||||
- Added `SpeechmaticsSTTService` exception handling on connection and sending.
|
||||
|
||||
- Replaced `asyncio.wait_for()` for `wait_for2.wait_for()` for Python <
|
||||
3.12. because of issues regarding task cancellation (i.e. cancellation is
|
||||
never propagated).
|
||||
See https://bugs.python.org/issue42130
|
||||
|
||||
- Fixed an `AudioBufferProcessor` issues that would cause audio overlap when
|
||||
setting a max buffer size.
|
||||
|
||||
- Fixed an issue where `AsyncAITTSService` had very high latency in responding
|
||||
by adding `force=true` when sending the flush command.
|
||||
|
||||
### Performance
|
||||
|
||||
- Improve `PipelineTask` performance by using direct mode processors and by
|
||||
removing unnecessary tasks.
|
||||
|
||||
- Improve `ParallelPipeline` performance by using direct mode, by not
|
||||
creating a task for each frame and every sub-pipeline and also by removing
|
||||
other unnecessary tasks.
|
||||
|
||||
- `Pipeline` performance improvements by using direct mode.
|
||||
|
||||
### Other
|
||||
|
||||
- Added `14w-function-calling-mistal.py` using `MistralLLMService`.
|
||||
|
||||
- Added `13j-azure-transcription.py` using `AzureSTTService`.
|
||||
|
||||
## [0.0.80] - 2025-08-13
|
||||
|
||||
### Added
|
||||
|
||||
- Added `GeminiTTSService` which uses Google Gemini to generate TTS output. The
|
||||
Gemini model can be prompted to insert styled speech to control the TTS
|
||||
output.
|
||||
|
||||
- Added Exotel support to Pipecat's development runner. You can now connect
|
||||
using the runner with `uv run bot.py -t exotel` and an ngrok connection to
|
||||
HTTP port 7860.
|
||||
|
||||
- Added `enable_direct_mode` argument to `FrameProcessor`. The direct mode is
|
||||
for processors which require very little I/O or compute resources, that is
|
||||
processors that can perform their task almost immediately. These type of
|
||||
processors don't need any of the internal tasks and queues usually created by
|
||||
frame processors which means overall application performance might be slightly
|
||||
increased. Use with care.
|
||||
|
||||
- Added TTFB metrics for `HeyGenVideoService` and `TavusVideoService`.
|
||||
|
||||
- Added `endpoint_id` parameter to `AzureSTTService`. ([Custom EndpointId](https://docs.azure.cn/en-us/ai-services/speech-service/how-to-recognize-speech?pivots=programming-language-python#use-a-custom-endpoint))
|
||||
|
||||
### Changed
|
||||
|
||||
- `WatchdogPriorityQueue` now requires the items to be inserted to always be
|
||||
tuples and the size of the tuple needs to be specified in the constructor when
|
||||
creating the queue with the `tuple_size` argument.
|
||||
|
||||
- Updated Moondream to revision `2025-01-09`.
|
||||
|
||||
- Updated `PlayHTHttpTTSService` to no longer use the `pyht` client to remove
|
||||
compatibility issues with other packages. Now you can use the PlayHT HTTP
|
||||
service with other services, like GoogleLLMService.
|
||||
|
||||
- Updated `pyproject.toml` to once again pin `numba` to `>=0.61.2` in order to
|
||||
resolve package versioning issues.
|
||||
|
||||
- Updated the `STTMuteFilter` to include `VADUserStartedSpeakingFrame` and
|
||||
`VADUserStoppedSpeakingFrame` in the list of frames to filter when the
|
||||
filtering is on.
|
||||
|
||||
### Performance
|
||||
|
||||
- Improving the latency of the `HeyGenVideoService`.
|
||||
|
||||
- Improved some frame processors performance by using the new frame processor
|
||||
direct mode. In direct mode a frame processor will process frames right away
|
||||
avoiding the need for internal queues and tasks. This is useful for some
|
||||
simple processors. For example, in processors that wrap other processors
|
||||
(e.g. `Pipeline`, `ParallelPipeline`), we add one processor before and one
|
||||
after the wrapped processors (internally, you will see them as sources and
|
||||
sinks). These sources and sinks don't do any special processing and they
|
||||
basically forward frames. So, for these simple processors we now enable the
|
||||
new direct mode which avoids creating any internal tasks (and queues) and
|
||||
therefore improves performance.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue with the `BaseWhisperSTTService` where the language was
|
||||
specified as an enum and not a string.
|
||||
|
||||
- Fixed an issue where `SmallWebRTCTransport` ended before TTS finished.
|
||||
|
||||
- Fixed an issue in `OpenAIRealtimeBetaLLMService` where specifying a `text`
|
||||
`modalities` didn't result in text being outputted from the model.
|
||||
|
||||
- Added SSML reserved character escaping to `AzureBaseTTSService` to properly
|
||||
handle special characters in text sent to Azure TTS. This fixes an issue
|
||||
where characters like `&`, `<`, `>`, `"`, and `'` in LLM-generated text would
|
||||
cause TTS failures.
|
||||
|
||||
- Fixed a `WatchdogPriorityQueue` issue that could cause an exception when
|
||||
compating watchdog cancel sentinel items with other items in the queue.
|
||||
|
||||
- Fixed an issue that would cause system frames to not be processed with higher
|
||||
priority than other frames. This could cause slower interruption times.
|
||||
|
||||
- Fixed an issue where retrying a websocket connection error would result in an
|
||||
error.
|
||||
|
||||
### Other
|
||||
|
||||
- Add foundation example `19b-openai-realtime-beta-text.py`, showing how to use
|
||||
`OpenAIRealtimeBetaLLMService` to output text to a TTS service.
|
||||
|
||||
- Add vision support to release evals so we can run the foundational examples 12
|
||||
series.
|
||||
|
||||
- Added foundational example `15a-switch-languages.py` to release evals. It is
|
||||
able to detect if we switched the language properly.
|
||||
|
||||
- Updated foundational examples to show how to enclose complex logic
|
||||
(e.g. `ParallelPipeline`) into a single processor so the main pipeline becomes
|
||||
simpler.
|
||||
|
||||
- Added `07n-interruptible-gemini.py`, demonstrating how to use
|
||||
`GeminiTTSService`.
|
||||
|
||||
## [0.0.79] - 2025-08-07
|
||||
|
||||
### Changed
|
||||
|
||||
- Changed `pipecat-ai`'s `openai` dependency to `>=1.74.0,<=1.99.1` due to a
|
||||
breaking change in `openai` 1.99.2 ([commit](https://github.com/openai/openai-python/commit/657f551dbe583ffb259d987dafae12c6211fba06))
|
||||
|
||||
### Deprecated
|
||||
|
||||
- `TTSService.say()` is deprecated, push a `TTSSpeakFrame` instead. Calling
|
||||
functions directly is a discouraged pattern in Pipecat because, for example,
|
||||
it might cause issues with frame ordering.
|
||||
|
||||
- `LLMMessagesFrame` is deprecated, in favor of either:
|
||||
|
||||
- `LLMMessagesUpdateFrame` with `run_llm=True`
|
||||
- `OpenAILLMContextFrame` with desired messages in a new context
|
||||
|
||||
- `LLMUserResponseAggregator` and `LLMAssistantResponseAggregator` are
|
||||
deprecated, as they depended on the now-deprecated `LLMMessagesFrame`. Use
|
||||
`LLMUserContextAggregator` and `LLMAssistantResponseAggregator` (or
|
||||
LLM-specific subclasses thereof) instead.
|
||||
|
||||
## [0.0.78] - 2025-08-07
|
||||
|
||||
### Added
|
||||
|
||||
- Added `enable_emulated_vad_interruptions` to `LLMUserAggregatorParams`.
|
||||
When user speech is emulated (e.g. when a transcription is received but
|
||||
VAD doesn't detect speech), this parameter controls whether the emulated
|
||||
speech can interrupt the bot. Default is False (emulated speech is ignored
|
||||
while the bot is speaking).
|
||||
|
||||
- Added new `handle_sigint` and `handle_sigterm` to `RunnerArguments`. This
|
||||
allows applications to know what settings they should use for the environment
|
||||
they are running on. Also, added `pipeline_idle_timeout_secs` to be able to
|
||||
control the `PipelineTask` idle timeout.
|
||||
|
||||
- Added `processor` field to `ErrorFrame` to indicate `FrameProcessor` that
|
||||
generated the error.
|
||||
|
||||
- Added new language support for `AWSTranscribeSTTService`. All languages
|
||||
supporting streaming data input are now supported:
|
||||
https://docs.aws.amazon.com/transcribe/latest/dg/supported-languages.html
|
||||
|
||||
- Added support for Simli Trinity Avatars. A new `is_trinity_avatar` parameter
|
||||
has been introduced to specify whether the provided `faceId` corresponds to a
|
||||
Trinity avatar, which is required for optimal Trinity avatar performance.
|
||||
|
||||
- The development runner how handles custom `body` data for `DailyTransport`.
|
||||
The `body` data is passed to the Pipecat client. You can POST to the `/start`
|
||||
endpoint with a request body of:
|
||||
|
||||
```
|
||||
{
|
||||
"createDailyRoom": true,
|
||||
"dailyRoomProperties": { "start_video_off": true },
|
||||
"body": { "custom_data": "value" }
|
||||
}
|
||||
```
|
||||
|
||||
The `body` information is parsed and used in the application. The
|
||||
`dailyRoomProperties` are currently not handled.
|
||||
|
||||
- Added detailed latency logging to `UserBotLatencyLogObserver`, capturing
|
||||
average response time between user stop and bot start, as well as minimum and
|
||||
maximum response latency.
|
||||
|
||||
- Added Chinese, Japanese, Korean word timestamp support to
|
||||
`CartesiaTTSService`.
|
||||
|
||||
- Added `region` parameter to `GladiaSTTService`. Accepted values: eu-west
|
||||
(default), us-west.
|
||||
|
||||
### Changed
|
||||
|
||||
- System frames are now queued. Before, system frames could be generated from
|
||||
any task and would not guarantee any order which was causing undesired
|
||||
behavior. Also, it was possible to get into some rare recursion issues because
|
||||
of the way system frames were executed (they were executed in-place, meaning
|
||||
calling `push_frame()` would finish after the system frame traversed all the
|
||||
pipeline). This makes system frames more deterministic.
|
||||
|
||||
- Changed the default model for both `ElevenLabsTTSService` and
|
||||
`ElevenLabsHttpTTSService` to `eleven_turbo_v2_5`. The rationale for this
|
||||
change is that the Turbo v2.5 model exhibits the most stable voice quality
|
||||
along with very low latency TTFB; latencies are on par with the Flash v2.5
|
||||
model. Also, the Turbo v2.5 model outputs word/timestamp alignment data with
|
||||
correct spacing.
|
||||
|
||||
- The development runners `/connect` and `/start` endpoint now both return
|
||||
`dailyRoom` and `dailyToken` in place of the previous `room_url` and `token`.
|
||||
|
||||
- Updated the `pipecat.runner.daily` utility to only a take `DAILY_API_URL` and
|
||||
`DAILY_SAMPLE_ROOM_URL` environment variables instead of argparsing `-u` and
|
||||
`-k`, respectively.
|
||||
|
||||
- Updated `daily-python` to 0.19.6.
|
||||
|
||||
- Changed `TavusVideoService` to send audio or video frames only after the
|
||||
transport is ready, preventing warning messages at startup.
|
||||
|
||||
- The development runner now strips any provided protocol (e.g. https://) from
|
||||
the proxy address and issues a warning. It also strips trailing `/`.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- In the `pipecat.runner.daily`, the `configure_with_args()` function is
|
||||
deprecated. Use the `configure()` function instead.
|
||||
|
||||
- The development runner's `/connect` endpoint is deprecated and will be
|
||||
removed in a future version. Use the `/start` endpoint in its place. In the
|
||||
meantime, both endpoints work and deliver equivalent functionality.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `DailyTransport` issue that would result in an unhandled
|
||||
`concurrent.futures.CancelledError` when a future is cancelled.
|
||||
|
||||
- Fixed a `RivaSTTService` issue that would result in an unhandled
|
||||
`concurrent.futures.CancelledError` when a future is cancelled when reading
|
||||
from the audio chunks from the incoming audio stream.
|
||||
|
||||
- Fixed an issue in the `BaseOutputTransport`, mainly reproducible with
|
||||
`FastAPIWebsocketOutputTransport` when the audio mixer was enabled, where the
|
||||
loop could consume 100% CPU by continuously returning without delay, preventing
|
||||
other asyncio tasks (such as cancellation or shutdown signals) from being
|
||||
processed.
|
||||
|
||||
- Fixed an issue where `BotStartedSpeakingFrame` and `BotStoppedSpeakingFrame`
|
||||
were not emitted when using `TavusVideoService` or `HeyGenVideoService`.
|
||||
|
||||
- Fixed an issue in `LiveKitTransport` where empty `AudioRawFrame`s were pushed
|
||||
down the pipeline. This resulted in warnings by the STT processor.
|
||||
- Fixed `PiperTTSService` to send text as a JSON object in the request body,
|
||||
resolving compatibility with Piper's HTTP API.
|
||||
|
||||
- Fixed an issue with the `TavusVideoService` where an error was thrown due to
|
||||
missing transcription callbacks.
|
||||
|
||||
- Fixed an issue in `SpeechmaticsSTTService` where the `user_id` was set to
|
||||
`None` when diarization is not enabled.
|
||||
|
||||
### Performance
|
||||
|
||||
- Fixed an issue in `TaskObserver` (a proxy to all observers) that was degrading
|
||||
global performance.
|
||||
|
||||
### Other
|
||||
|
||||
- Added `07aa-interruptible-soniox.py`, `07ab-interruptible-inworld-http.py`,
|
||||
`07ac-interruptible-asyncai.py` and `07ac-interruptible-asyncai-http.py`
|
||||
release evals.
|
||||
|
||||
## [0.0.77] - 2025-07-31
|
||||
|
||||
### Added
|
||||
|
||||
- Added `InputTextRawFrame` frame type to handle user text input with Gemini
|
||||
Multimodal Live.
|
||||
|
||||
- Added `HeyGenVideoService`. This is an integration for HeyGen Interactive
|
||||
Avatar. A video service that handles audio streaming and requests HeyGen to
|
||||
generate avatar video responses. (see https://www.heygen.com/)
|
||||
|
||||
- Added the ability to switch voices to `RimeTTSService`.
|
||||
|
||||
- Added unified development runner for building voice AI bots across multiple
|
||||
transports
|
||||
|
||||
- `pipecat.runner.run` – FastAPI-based development server with automatic bot
|
||||
discovery
|
||||
- `pipecat.runner.types` – Runner session argument types
|
||||
(`DailyRunnerArguments`, `SmallWebRTCRunnerArguments`,
|
||||
`WebSocketRunnerArguments`)
|
||||
- `pipecat.runner.utils.create_transport()` – Factory function for creating
|
||||
transports from session arguments
|
||||
- `pipecat.runner.daily` and `pipecat.runner.livekit` – Configuration
|
||||
utilities for Daily and LiveKit setups
|
||||
- Support for all transport types: Daily, WebRTC, Twilio, Telnyx, Plivo
|
||||
- Automatic telephony provider detection and serializer configuration
|
||||
- ESP32 WebRTC compatibility with SDP munging
|
||||
- Environment detection (`ENV=local`) for conditional features
|
||||
|
||||
- Added Async.ai TTS integration (https://async.ai/)
|
||||
|
||||
- `AsyncAITTSService` – WebSocket-based streaming TTS with interruption
|
||||
support
|
||||
- `AsyncAIHttpTTSService` – HTTP-based streaming TTS service
|
||||
- Example scripts:
|
||||
- `examples/foundational/07ac-interruptible-asyncai.py` (WebSocket demo)
|
||||
- `examples/foundational/07ac-interruptible-asyncai-http.py` (HTTP demo)
|
||||
|
||||
- Added `transcription_bucket` params support to the `DailyRESTHelper`.
|
||||
|
||||
- Added a new TTS service, `InworldTTSService`. This service provides
|
||||
low-latency, high-quality speech generation using Inworld's streaming API.
|
||||
|
||||
- Added a new field `handle_sigterm` to `PipelineRunner`. It defaults to
|
||||
`False`. This field handles SIGTERM signals. The `handle_sigint` field still
|
||||
defaults to `True`, but now it handles only SIGINT signals.
|
||||
- Added a new field `handle_sigterm` to `PipelineRunner`. It defaults to `False`.
|
||||
This field handles SIGTERM signals. The `handle_sigint` field still defaults
|
||||
to `True`, but now it handles only SIGINT signals.
|
||||
|
||||
- Added foundational example `14u-function-calling-ollama.py` for Ollama
|
||||
function calling.
|
||||
@@ -649,21 +22,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
- Added `set_log_level` to `DailyTransport`, allowing setting the logging level
|
||||
for Daily's internal logging system.
|
||||
|
||||
- Added `on_transcription_stopped` and `on_transcription_error` to Daily
|
||||
callbacks.
|
||||
|
||||
### Changed
|
||||
|
||||
- Changed the default `url` for `NeuphonicTTSService` to
|
||||
`wss://api.neuphonic.com` as it provides better global performance. You can
|
||||
set the URL to other URLs, such as the previous default:
|
||||
`wss://eu-west-1.api.neuphonic.com`.
|
||||
|
||||
- Update `daily-python` to 0.19.5.
|
||||
|
||||
- `STTMuteFilter` now pushes the `STTMuteFrame` upstream and downstream, to
|
||||
allow for more flexible `STTMuteFilter` placement.
|
||||
|
||||
- Play delayed messages from `ElevenLabsTTSService` if they still belong to the
|
||||
current context.
|
||||
|
||||
@@ -685,10 +45,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
`pyneuphonic` package. This removes a package requirement, allowing Neuphonic
|
||||
to work with more services.
|
||||
|
||||
- Updated `ElevenLabsTTSService` to handle the case where
|
||||
`allow_interruptions=False`. Now, when interruptions are disabled, the same
|
||||
context ID will be used throughout the conversation.
|
||||
|
||||
- Updated the `deepgram` optional dependency to 4.7.0, which downgrades the
|
||||
`tasks cancelled error` to a debug log. This removes the log from appearing
|
||||
in Pipecat logs upon leaving.
|
||||
@@ -709,39 +65,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
- For `LmntTTSService`, changed the default `model` to `blizzard`, LMNT's
|
||||
recommended model.
|
||||
|
||||
- Updated `SpeechmaticsSTTService`:
|
||||
- Added support for additional diarization options.
|
||||
- Added foundational example `07a-interruptible-speechmatics-vad.py`, which
|
||||
uses VAD detection provided by `SpeechmaticsSTTService`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `LLMUserResponseAggregator` issue where interruptions were not being
|
||||
handled properly.
|
||||
|
||||
- Fixed `PiperTTSService` to work with newer Piper GPL.
|
||||
|
||||
- Fixed a race condition in `FastAPIWebsocketClient` that occurred when
|
||||
attempting to send a message while the client was disconnecting.
|
||||
|
||||
- Fixed an issue in `GoogleLLMService` where interruptions did not work when an
|
||||
interruption strategy was used.
|
||||
|
||||
- Fixed an issue in the `TranscriptProcessor` where newline characters could
|
||||
cause the transcript output to be corrupted (e.g. missing all spaces).
|
||||
|
||||
- Fixed an issue in `AudioBufferProcessor` when using `SmallWebRTCTransport`
|
||||
where, if the microphone was muted, track timing was not respected.
|
||||
|
||||
- Fixed an error that occurs when pushing an `LLMMessagesFrame`. Only some LLM
|
||||
services, like Grok, are impacted by this issue. The fix is to remove the
|
||||
optional `name` property that was being added to the message.
|
||||
|
||||
- Fixed an issue in `AudioBufferProcessor` that caused garbled audio when
|
||||
`enable_turn_audio` was enabled and audio resampling was required.
|
||||
|
||||
- Fixed a dependency issue for uv users where an `llvmlite` version required
|
||||
python 3.9.
|
||||
- Fixed a dependency issue for uv users where an `llvmlite` version required python 3.9.
|
||||
|
||||
- Fixed an issue in `MiniMaxHttpTTSService` where the `pitch` param was the
|
||||
incorrect type.
|
||||
@@ -755,28 +81,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
- Fixed an issue in `ElevenLabsTTSService` where the word/timestamp pairs were
|
||||
calculating word boundaries incorrectly.
|
||||
|
||||
- Fixed an issue where, in some edge cases, the
|
||||
`EmulateUserStartedSpeakingFrame` could be created even if we didn't have a
|
||||
transcription.
|
||||
- Fixed an issue where, in some edge cases, the `EmulateUserStartedSpeakingFrame`
|
||||
could be created even if we didn't have a transcription.
|
||||
|
||||
- Fixed an issue in `GoogleLLMContext` where it would inject the
|
||||
`system_message` as a "user" message into cases where it was not meant to;
|
||||
it was only meant to do that when there were no "regular" (non-function-call)
|
||||
messages in the context, to ensure that inference would run properly.
|
||||
|
||||
- Fixed an issue in `LiveKitTransport` where the `on_audio_track_subscribed` was
|
||||
never emitted.
|
||||
|
||||
### Other
|
||||
|
||||
- Added new quickstart demos:
|
||||
|
||||
- examples/quickstart: voice AI bot quickstart
|
||||
- examples/client-server-web: client/server starter example
|
||||
- examples/phone-bot-twilio: twilio starter example
|
||||
|
||||
- Removed most of the examples from the pipecat repo. Examples can now be
|
||||
found in: https://github.com/pipecat-ai/pipecat-examples.
|
||||
- Fixed an issue in `LiveKitTransport` where the `on_audio_track_subscribed` was never emitted.
|
||||
|
||||
## [0.0.76] - 2025-07-11
|
||||
|
||||
@@ -819,12 +132,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
user started early, while the bot was still working through
|
||||
`trigger_assistant_response()`.
|
||||
|
||||
## [0.0.75] - 2025-07-08 [YANKED]
|
||||
|
||||
**This release has been yanked due to resampling issues affecting audio output
|
||||
quality and critical bugs impacting `ParallelPipelines` functionality.**
|
||||
|
||||
**Please upgrade to version 0.0.76 or later.**
|
||||
## [0.0.75] - 2025-07-08
|
||||
|
||||
### Added
|
||||
|
||||
@@ -885,12 +193,7 @@ quality and critical bugs impacting `ParallelPipelines` functionality.**
|
||||
|
||||
- Remove unncessary push task in each `FrameProcessor`.
|
||||
|
||||
## [0.0.74] - 2025-07-03 [YANKED]
|
||||
|
||||
**This release has been yanked due to resampling issues affecting audio output
|
||||
quality and critical bugs impacting `ParallelPipelines` functionality.**
|
||||
|
||||
**Please upgrade to version 0.0.76 or later.**
|
||||
## [0.0.74] - 2025-07-03
|
||||
|
||||
### Added
|
||||
|
||||
|
||||
@@ -31,23 +31,6 @@ git push origin your-branch-name
|
||||
|
||||
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
|
||||
|
||||
40
Dockerfile
Normal file
40
Dockerfile
Normal file
@@ -0,0 +1,40 @@
|
||||
# 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"]
|
||||
150
README.md
150
README.md
@@ -8,7 +8,7 @@
|
||||
|
||||
**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.
|
||||
|
||||
> Want to dive right in? Try the [quickstart](https://docs.pipecat.ai/getting-started/quickstart).
|
||||
> Want to dive right in? [Install Pipecat](https://docs.pipecat.ai/getting-started/installation) then try the [quickstart](https://docs.pipecat.ai/getting-started/quickstart).
|
||||
|
||||
## 🚀 What You Can Build
|
||||
|
||||
@@ -31,11 +31,11 @@
|
||||
## 🎬 See it in action
|
||||
|
||||
<p float="left">
|
||||
<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>
|
||||
<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>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/simple-chatbot/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/storytelling-chatbot/image.png" width="400" /></a>
|
||||
<br/>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>
|
||||
<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>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/translation-chatbot/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/moondream-chatbot/image.png" width="400" /></a>
|
||||
</p>
|
||||
|
||||
## 📱 Client SDKs
|
||||
@@ -51,124 +51,98 @@ You can connect to Pipecat from any platform using our official SDKs:
|
||||
|
||||
## 🧩 Available services
|
||||
|
||||
| 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), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) |
|
||||
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
|
||||
| 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), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [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), [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 | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
|
||||
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
|
||||
| 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 | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
|
||||
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
|
||||
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) |
|
||||
| Analytics & Metrics | [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)
|
||||
|
||||
## ⚡ 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 get started with Pipecat running on your local machine, then move your agent processes to the cloud when you’re ready.
|
||||
|
||||
1. Install uv
|
||||
```shell
|
||||
# Install the module
|
||||
pip install pipecat-ai
|
||||
|
||||
```bash
|
||||
curl -LsSf https://astral.sh/uv/install.sh | sh
|
||||
```
|
||||
# Set up your environment
|
||||
cp dot-env.template .env
|
||||
```
|
||||
|
||||
> **Need help?** Refer to the [uv install documentation](https://docs.astral.sh/uv/getting-started/installation/).
|
||||
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:
|
||||
|
||||
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.
|
||||
```shell
|
||||
pip install "pipecat-ai[option,...]"
|
||||
```
|
||||
|
||||
## 🧪 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-examples) — complete applications that you can use as starting points for development
|
||||
- [Example apps](https://github.com/pipecat-ai/pipecat/tree/main/examples/) — complete applications that you can use as starting points for development
|
||||
|
||||
## 🛠️ Contributing to the framework
|
||||
## 🛠️ Hacking on the framework itself
|
||||
|
||||
### Prerequisites
|
||||
1. Set up a virtual environment before following these instructions. From the root of the repo:
|
||||
|
||||
**Minimum Python Version:** 3.10
|
||||
**Recommended Python Version:** 3.12
|
||||
|
||||
### Setup Steps
|
||||
|
||||
1. Clone the repository and navigate to it:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/pipecat-ai/pipecat.git
|
||||
cd pipecat
|
||||
```shell
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
```
|
||||
|
||||
2. Install development and testing dependencies:
|
||||
2. Install the development dependencies:
|
||||
|
||||
```bash
|
||||
uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp --no-extra local
|
||||
```shell
|
||||
pip install -r dev-requirements.txt
|
||||
```
|
||||
|
||||
3. Install the git pre-commit hooks:
|
||||
3. Install the git pre-commit hooks (these help ensure your code follows project rules):
|
||||
|
||||
```bash
|
||||
uv run pre-commit install
|
||||
```shell
|
||||
pre-commit install
|
||||
```
|
||||
|
||||
### Python 3.13+ Compatibility
|
||||
4. Install the `pipecat-ai` package locally in editable mode:
|
||||
|
||||
Some features require PyTorch, which doesn't yet support Python 3.13+. Install using:
|
||||
```shell
|
||||
pip install -e .
|
||||
```
|
||||
|
||||
```bash
|
||||
uv sync --group dev --all-extras \
|
||||
--no-extra gstreamer \
|
||||
--no-extra krisp \
|
||||
--no-extra local \
|
||||
--no-extra local-smart-turn \
|
||||
--no-extra mlx-whisper \
|
||||
--no-extra moondream \
|
||||
--no-extra ultravox
|
||||
```
|
||||
> The `-e` or `--editable` option allows you to modify the code without reinstalling.
|
||||
|
||||
> **Tip:** For full compatibility, use Python 3.12: `uv python pin 3.12`
|
||||
5. Include optional dependencies as needed. For example:
|
||||
|
||||
> **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
|
||||
```shell
|
||||
pip install -e ".[daily,deepgram,cartesia,openai,silero]"
|
||||
```
|
||||
|
||||
6. (Optional) If you want to use this package from another directory:
|
||||
|
||||
```shell
|
||||
pip install "path_to_this_repo[option,...]"
|
||||
```
|
||||
|
||||
### Running tests
|
||||
|
||||
To run all tests, from the root directory:
|
||||
Install the test dependencies:
|
||||
|
||||
```bash
|
||||
uv run pytest
|
||||
```shell
|
||||
pip install -r test-requirements.txt
|
||||
```
|
||||
|
||||
Run a specific test suite:
|
||||
From the root directory, run:
|
||||
|
||||
```bash
|
||||
uv run pytest tests/test_name.py
|
||||
```shell
|
||||
pytest
|
||||
```
|
||||
|
||||
### Setting up your editor
|
||||
|
||||
20
dev-requirements.txt
Normal file
20
dev-requirements.txt
Normal file
@@ -0,0 +1,20 @@
|
||||
build~=1.2.2
|
||||
coverage~=7.9.1
|
||||
grpcio-tools~=1.67.1
|
||||
pip-tools~=7.4.1
|
||||
pre-commit~=4.2.0
|
||||
pyright~=1.1.402
|
||||
pytest~=8.4.1
|
||||
pytest-asyncio~=1.0.0
|
||||
pytest-aiohttp==1.1.0
|
||||
ruff~=0.12.1
|
||||
setuptools~=78.1.1
|
||||
setuptools_scm~=8.3.1
|
||||
python-dotenv~=1.1.1
|
||||
|
||||
# For running examples
|
||||
uvicorn
|
||||
python-dotenv
|
||||
fastapi
|
||||
aiohttp
|
||||
aiortc
|
||||
10
docs/README.md
Normal file
10
docs/README.md
Normal file
@@ -0,0 +1,10 @@
|
||||
# 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.
|
||||
|
||||
@@ -1,27 +1,10 @@
|
||||
#!/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
|
||||
uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
|
||||
sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
|
||||
|
||||
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
|
||||
# Open docs (MacOS)
|
||||
open _build/html/index.html
|
||||
155
docs/api/conf.py
155
docs/api/conf.py
@@ -1,5 +1,4 @@
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
@@ -29,7 +28,6 @@ extensions = [
|
||||
|
||||
suppress_warnings = [
|
||||
"autodoc.mocked_object",
|
||||
"toc.not_included",
|
||||
]
|
||||
|
||||
# Napoleon settings
|
||||
@@ -47,40 +45,85 @@ autodoc_default_options = {
|
||||
|
||||
# Mock imports for optional dependencies
|
||||
autodoc_mock_imports = [
|
||||
# Krisp - has build issues on some platforms
|
||||
"pipecat_ai_krisp",
|
||||
"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
|
||||
"aiortc",
|
||||
"aiortc.mediastreams",
|
||||
"cv2",
|
||||
"av",
|
||||
"pyneuphonic",
|
||||
"mem0",
|
||||
"mlx_whisper",
|
||||
"anthropic",
|
||||
"assemblyai",
|
||||
"boto3",
|
||||
"azure",
|
||||
"cartesia",
|
||||
"deepgram",
|
||||
"elevenlabs",
|
||||
"fal",
|
||||
"gladia",
|
||||
"google",
|
||||
"krisp",
|
||||
# System-specific GUI libraries
|
||||
"langchain",
|
||||
"lmnt",
|
||||
"noisereduce",
|
||||
"openpipe",
|
||||
"simli",
|
||||
"soundfile",
|
||||
"soniox",
|
||||
"pipecat_ai_krisp",
|
||||
"pyaudio",
|
||||
"_tkinter",
|
||||
"tkinter",
|
||||
# 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
|
||||
"daily",
|
||||
"daily_python",
|
||||
# Moondream dependencies
|
||||
"torch",
|
||||
"transformers",
|
||||
"intel_extension_for_pytorch",
|
||||
# Ultravox dependencies
|
||||
"huggingface_hub",
|
||||
"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
|
||||
# Langchain dependencies
|
||||
"langchain_core",
|
||||
"langchain_core.messages",
|
||||
"langchain_core.runnables",
|
||||
"langchain_core.messages.AIMessageChunk",
|
||||
"langchain_core.runnables.Runnable",
|
||||
# LiveKit dependencies
|
||||
"livekit",
|
||||
"livekit.rtc",
|
||||
"livekit_api",
|
||||
"livekit_protocol",
|
||||
"tenacity",
|
||||
"tenacity.retry",
|
||||
"tenacity.stop_after_attempt",
|
||||
"tenacity.wait_exponential",
|
||||
"rtc",
|
||||
"rtc.Room",
|
||||
"rtc.RoomOptions",
|
||||
"rtc.AudioSource",
|
||||
"rtc.LocalAudioTrack",
|
||||
"rtc.TrackPublishOptions",
|
||||
"rtc.TrackSource",
|
||||
"rtc.AudioStream",
|
||||
"rtc.AudioFrameEvent",
|
||||
"rtc.AudioFrame",
|
||||
"rtc.Track",
|
||||
"rtc.TrackKind",
|
||||
"rtc.RemoteParticipant",
|
||||
"rtc.RemoteTrackPublication",
|
||||
"rtc.DataPacket",
|
||||
# Riva dependencies
|
||||
"riva",
|
||||
"riva.client",
|
||||
"riva.client.Auth",
|
||||
@@ -90,14 +133,57 @@ autodoc_mock_imports = [
|
||||
"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
|
||||
# Local CoreML Smart Turn dependencies
|
||||
"coremltools",
|
||||
"coremltools.models",
|
||||
"coremltools.models.MLModel",
|
||||
"torch",
|
||||
"torch.nn",
|
||||
"torch.nn.functional",
|
||||
"transformers",
|
||||
"transformers.AutoFeatureExtractor",
|
||||
# Also add specific classes that are imported
|
||||
"AutoFeatureExtractor",
|
||||
# Sentry dependencies
|
||||
"sentry_sdk",
|
||||
# AWS Nova Sonic dependencies
|
||||
"aws_sdk_bedrock_runtime",
|
||||
"aws_sdk_bedrock_runtime.client",
|
||||
"aws_sdk_bedrock_runtime.config",
|
||||
"aws_sdk_bedrock_runtime.models",
|
||||
"smithy_aws_core",
|
||||
"smithy_aws_core.credentials_resolvers",
|
||||
"smithy_aws_core.credentials_resolvers.static",
|
||||
"smithy_aws_core.identity",
|
||||
"smithy_core",
|
||||
"smithy_core.aio",
|
||||
"smithy_core.aio.eventstream",
|
||||
# MCP dependencies (you may already have these)
|
||||
"mcp",
|
||||
"mcp.client",
|
||||
"mcp.client.session_group",
|
||||
"mcp.client.sse",
|
||||
"mcp.client.stdio",
|
||||
"mcp.ClientSession",
|
||||
"mcp.StdioServerParameters",
|
||||
# gstreamer
|
||||
"gi",
|
||||
"gi.require_version",
|
||||
"gi.repository",
|
||||
# Protobuf mocks
|
||||
"pipecat.frames.protobufs.frames_pb2",
|
||||
"pipecat.serializers.protobuf",
|
||||
"google.protobuf",
|
||||
"google.protobuf.descriptor",
|
||||
"google.protobuf.descriptor_pool",
|
||||
"google.protobuf.runtime_version",
|
||||
"google.protobuf.symbol_database",
|
||||
"google.protobuf.internal.builder",
|
||||
]
|
||||
|
||||
# HTML output settings
|
||||
html_theme = "sphinx_rtd_theme"
|
||||
html_static_path = ["_static"] if os.path.exists("_static") else []
|
||||
html_static_path = ["_static"]
|
||||
autodoc_typehints = "signature" # Show type hints in the signature only, not in the docstring
|
||||
html_show_sphinx = False
|
||||
|
||||
@@ -116,7 +202,6 @@ def import_core_modules():
|
||||
"pipecat.clocks",
|
||||
"pipecat.metrics",
|
||||
"pipecat.observers",
|
||||
"pipecat.runner",
|
||||
"pipecat.serializers",
|
||||
"pipecat.sync",
|
||||
"pipecat.transcriptions",
|
||||
|
||||
@@ -14,20 +14,18 @@ Quick Links
|
||||
* `Join our Community <https://discord.gg/pipecat>`_
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
:maxdepth: 3
|
||||
: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>
|
||||
|
||||
56
docs/api/requirements.txt
Normal file
56
docs/api/requirements.txt
Normal file
@@ -0,0 +1,56 @@
|
||||
# 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[cartesia]
|
||||
pipecat-ai[cerebras]
|
||||
pipecat-ai[deepseek]
|
||||
pipecat-ai[daily]
|
||||
pipecat-ai[deepgram]
|
||||
pipecat-ai[elevenlabs]
|
||||
pipecat-ai[fal]
|
||||
pipecat-ai[fireworks]
|
||||
pipecat-ai[fish]
|
||||
pipecat-ai[gladia]
|
||||
pipecat-ai[google]
|
||||
pipecat-ai[grok]
|
||||
pipecat-ai[groq]
|
||||
# pipecat-ai[krisp] # Mocked
|
||||
pipecat-ai[koala]
|
||||
# pipecat-ai[langchain] # Mocked
|
||||
# pipecat-ai[livekit] # Mocked
|
||||
pipecat-ai[lmnt]
|
||||
pipecat-ai[local]
|
||||
# pipecat-ai[local-smart-turn] # Mocked
|
||||
# pipecat-ai[mem0] # Mocked
|
||||
# pipecat-ai[mlx-whisper] # Mocked
|
||||
# pipecat-ai[moondream] # Mocked
|
||||
pipecat-ai[nim]
|
||||
# pipecat-ai[neuphonic] # Mocked
|
||||
pipecat-ai[noisereduce]
|
||||
pipecat-ai[openai]
|
||||
# pipecat-ai[openpipe]
|
||||
# pipecat-ai[playht] # Mocked due to grpcio conflict with riva
|
||||
pipecat-ai[qwen]
|
||||
pipecat-ai[remote-smart-turn]
|
||||
# pipecat-ai[riva] # Mocked
|
||||
pipecat-ai[sambanova]
|
||||
pipecat-ai[silero]
|
||||
pipecat-ai[simli]
|
||||
pipecat-ai[soundfile]
|
||||
pipecat-ai[soniox]
|
||||
pipecat-ai[speechmatics]
|
||||
pipecat-ai[tavus]
|
||||
pipecat-ai[together]
|
||||
# pipecat-ai[ultravox] # Mocked
|
||||
# pipecat-ai[webrtc] # Mocked
|
||||
pipecat-ai[websocket]
|
||||
pipecat-ai[whisper]
|
||||
17
docs/architecture.md
Normal file
17
docs/architecture.md
Normal file
@@ -0,0 +1,17 @@
|
||||
# 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.
|
||||
46
docs/frame-progress.md
Normal file
46
docs/frame-progress.md
Normal file
@@ -0,0 +1,46 @@
|
||||
# A Frame's Progress
|
||||
|
||||
1. A user says “Hello, LLM” and the cloud transcription service delivers a transcription to the Transport.
|
||||
|
||||
|
||||
2. The Transport places a Transcription frame in the Pipeline’s source queue.
|
||||
|
||||
|
||||
3. The Pipeline passes the Transcription frame to the first Frame Processor in its list, the LLM User Message Aggregator.
|
||||
|
||||
|
||||
4. The LLM User Message Aggregator updates the LLM Context with a `{“user”: “Hello LLM”}` message.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
7. The LLM Frame Processor yields another Text Frame with the value “there.”. The Pipeline passes this frame to the TTS Frame Processor.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
11. The TTS Frame Processor yields another Audio frame as the Transport transmits the first Audio frame.
|
||||
|
||||
|
||||
12. As before, the LLM Assistant Message Aggregator immediately yields the Audio frame and the Pipeline places the Audio frame in the sink queue.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
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.
|
||||
|
||||
|
||||
15. The system is quiet, and waiting for the next message from the Transport.
|
||||
|
||||
110
docs/frame.md
Normal file
110
docs/frame.md
Normal file
@@ -0,0 +1,110 @@
|
||||
# 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.
|
||||
BIN
docs/images/frame-progress-01.png
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|
After Width: | Height: | Size: 98 KiB |
@@ -1,10 +1,6 @@
|
||||
# Anthropic
|
||||
ANTHROPIC_API_KEY=...
|
||||
|
||||
# Async
|
||||
ASYNCAI_API_KEY=...
|
||||
ASYNCAI_VOICE_ID=...
|
||||
|
||||
# AWS
|
||||
AWS_SECRET_ACCESS_KEY=...
|
||||
AWS_ACCESS_KEY_ID=...
|
||||
@@ -29,9 +25,6 @@ CARTESIA_API_KEY=...
|
||||
DAILY_API_KEY=...
|
||||
DAILY_SAMPLE_ROOM_URL=https://...
|
||||
|
||||
# Deepgram
|
||||
DEEPGRAM_API_KEY=...
|
||||
|
||||
# ElevenLabs
|
||||
ELEVENLABS_API_KEY=...
|
||||
ELEVENLABS_VOICE_ID=...
|
||||
@@ -47,21 +40,11 @@ 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=...
|
||||
@@ -93,9 +76,6 @@ GROQ_API_KEY=...
|
||||
# Grok
|
||||
GROK_API_KEY=...
|
||||
|
||||
# Inworld
|
||||
INWORLD_API_KEY=...
|
||||
|
||||
# Together.ai
|
||||
TOGETHER_API_KEY=...
|
||||
|
||||
@@ -135,11 +115,9 @@ SONIOX_API_KEY=
|
||||
# Speechmatics
|
||||
SPEECHMATICS_API_KEY=...
|
||||
|
||||
|
||||
# SambaNova
|
||||
SAMBANOVA_API_KEY=...
|
||||
|
||||
# Sentry
|
||||
SENTRY_DSN=...
|
||||
|
||||
# Heygen
|
||||
HEYGEN_API_KEY=...
|
||||
@@ -1,31 +1,88 @@
|
||||
# Pipecat Examples
|
||||
|
||||
This directory contains examples to help you learn how to build with Pipecat.
|
||||
|
||||
## Getting Started
|
||||
# Pipecat — Examples
|
||||
|
||||
New to Pipecat? Start here:
|
||||
## Foundational snippets
|
||||
Small snippets that build on each other, introducing one or two concepts at a time.
|
||||
|
||||
- **[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)_
|
||||
➡️ [Take a look](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational)
|
||||
|
||||
## Foundational Examples
|
||||
## Chatbot examples
|
||||
Collection of self-contained real-time voice and video AI demo applications built with Pipecat.
|
||||
|
||||
Single-file examples that introduce core Pipecat concepts one at a time. These examples:
|
||||
### Quickstart
|
||||
|
||||
- Build on each other progressively
|
||||
- Focus on specific features or integrations
|
||||
- Are used for testing with every Pipecat release
|
||||
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.
|
||||
|
||||
See the **[Foundational Examples README](foundational/)** for the complete list.
|
||||
We recommend you start with a virtual environment:
|
||||
|
||||
## More Advanced Examples
|
||||
```shell
|
||||
cd pipecat-ai/examples/simple-chatbot
|
||||
|
||||
Ready to explore complex use cases? Visit **[pipecat-examples](https://github.com/pipecat-ai/pipecat-examples)** for:
|
||||
python -m venv venv
|
||||
|
||||
- Production-ready applications
|
||||
- Multi-platform client implementations
|
||||
- Telephony integrations
|
||||
- Multimodal and creative applications
|
||||
- Deployment and monitoring examples
|
||||
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)
|
||||
|
||||
60
examples/aws-strands/README.md
Normal file
60
examples/aws-strands/README.md
Normal file
@@ -0,0 +1,60 @@
|
||||
# AWS Strands Examples
|
||||
|
||||
This folder contains two Python examples demonstrating how to use Pipecat with the AWS Strands agent.
|
||||
|
||||
## Overview
|
||||
|
||||
These examples show how to delegate complex, multi-step tasks to a Strands agent, which can reason step-by-step and call tools to accomplish user requests.
|
||||
|
||||
These examples are intentionally simplified for demonstration, using mock API calls. They work best if you ask it:
|
||||
|
||||
> What's the weather where the Golden Gate Bridge is?
|
||||
|
||||
## Example Scripts
|
||||
|
||||
### `black-box.py`
|
||||
|
||||
A minimal example that demonstrates how to use the Strands agent with Pipecat. The agent can handle multi-step queries by calling tools, but does not explain its reasoning out loud.
|
||||
|
||||
### `explain-thinking.py`
|
||||
|
||||
An enhanced example where the Strands agent explains each step of its reasoning in clear, simple language as it works through a multi-step task.
|
||||
|
||||
## Quick Start
|
||||
|
||||
1. **Clone the repository and navigate to this example:**
|
||||
|
||||
```bash
|
||||
git clone https://github.com/pipecat-ai/pipecat.git
|
||||
cd pipecat/examples/aws-strands
|
||||
```
|
||||
|
||||
2. **Set up a virtual environment:**
|
||||
|
||||
```bash
|
||||
python -m venv venv
|
||||
source venv/bin/activate # On Windows: venv\Scripts\activate
|
||||
```
|
||||
|
||||
3. **Install dependencies:**
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
4. **Configure environment variables:**
|
||||
|
||||
Copy the provided `env.example` file to `.env` and fill in the necessary credentials:
|
||||
|
||||
```bash
|
||||
cp env.example .env
|
||||
# Then edit .env with your preferred editor
|
||||
```
|
||||
|
||||
5. **Run an example:**
|
||||
|
||||
```bash
|
||||
python black-box.py
|
||||
# or
|
||||
python explain-thinking.py
|
||||
```
|
||||
206
examples/aws-strands/black-box.py
Normal file
206
examples/aws-strands/black-box.py
Normal file
@@ -0,0 +1,206 @@
|
||||
#
|
||||
# Copyright (c) 2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import os
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from strands import Agent, tool
|
||||
from strands.models import BedrockModel
|
||||
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.llm_service import FunctionCallParams
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
|
||||
from pipecat.transports.services.daily import DailyParams
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
"""This example demonstrates how to use the Strands agent with Pipecat.
|
||||
|
||||
You can delegate complex, multi-step tasks to the Strands agent, which can cycle through LLM-based reasoning and tool calls to accomplish the task.
|
||||
|
||||
Try asking: "What's the weather where the Golden Gate Bridge is?"
|
||||
"""
|
||||
|
||||
# Strands agent tools
|
||||
|
||||
|
||||
@tool
|
||||
def get_location_name_from_landmark(landmark: str) -> str:
|
||||
"""
|
||||
Get the location name from a landmark.
|
||||
|
||||
Args:
|
||||
landmark (str): The name of the landmark, e.g. "Golden Gate Bridge".
|
||||
"""
|
||||
# Simulate fetching location
|
||||
return "San Francisco, CA"
|
||||
|
||||
|
||||
@tool
|
||||
def get_lat_long_from_location_name(location: str) -> dict:
|
||||
"""
|
||||
Get the latitude and longitude for a location name.
|
||||
|
||||
Args:
|
||||
location (str): The city and state, e.g. "San Francisco, CA".
|
||||
"""
|
||||
# Simulate fetching lat/long from a geocoding service
|
||||
return {"lat": 37.7749, "long": -122.4194}
|
||||
|
||||
|
||||
@tool
|
||||
def get_current_weather_from_lat_long(lat: float, long: float) -> dict:
|
||||
"""
|
||||
Get the current weather for a specific latitude and longitude.
|
||||
|
||||
Args:
|
||||
lat (float): The latitude of the location.
|
||||
long (float): The longitude of the location.
|
||||
"""
|
||||
# Simulate fetching weather data from a weather service
|
||||
return {"conditions": "nice", "temperature": "75"}
|
||||
|
||||
|
||||
# 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_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
"twilio": lambda: FastAPIWebsocketParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
"webrtc": lambda: TransportParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
strands_agent = Agent(
|
||||
model=BedrockModel(
|
||||
model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0", max_tokens=64000
|
||||
),
|
||||
tools=[
|
||||
get_location_name_from_landmark,
|
||||
get_lat_long_from_location_name,
|
||||
get_current_weather_from_lat_long,
|
||||
],
|
||||
system_prompt="""
|
||||
You are a helpful personal assistant who can look up information about places and weather.
|
||||
|
||||
Your key capabilities:
|
||||
1. Look up where landmarks are located.
|
||||
2. Find latitude and longitude for a location.
|
||||
3. Look up the current weather for a specific latitude and longitude.
|
||||
|
||||
Explain each step of your reasoning in clear, simple, and concise language. Your responses will be converted to audio, so avoid special characters and numbered lists.
|
||||
""",
|
||||
)
|
||||
|
||||
async def handle_location_or_weather_related_queries(params: FunctionCallParams, query: str):
|
||||
"""
|
||||
Handle location or weather related queries.
|
||||
|
||||
Args:
|
||||
query (str): The user's query, e.g. "What's the weather where the Golden Gate Bridge is?".
|
||||
"""
|
||||
# Run in a background thread
|
||||
# (Otherwise the agent blocks the event loop; one effect of that is that we don't hear
|
||||
# "let me check on that" until the agent finishes)
|
||||
loop = asyncio.get_running_loop()
|
||||
result = await loop.run_in_executor(None, strands_agent, query)
|
||||
await params.result_callback(result.message)
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
|
||||
llm.register_direct_function(handle_location_or_weather_related_queries)
|
||||
|
||||
@llm.event_handler("on_function_calls_started")
|
||||
async def on_function_calls_started(service, function_calls):
|
||||
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
|
||||
|
||||
tools = ToolsSchema(standard_tools=[handle_location_or_weather_related_queries])
|
||||
|
||||
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. Start by suggesting that the user ask about the weather where the Golden Gate Bridge is.",
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
logger.info(f"Client disconnected")
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner(handle_sigint=handle_sigint)
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from pipecat.examples.run import main
|
||||
|
||||
main(run_example, transport_params=transport_params)
|
||||
8
examples/aws-strands/env.example
Normal file
8
examples/aws-strands/env.example
Normal file
@@ -0,0 +1,8 @@
|
||||
OPENAI_API_KEY=
|
||||
CARTESIA_API_KEY=
|
||||
DEEPGRAM_API_KEY=
|
||||
DAILY_API_KEY=
|
||||
DAILY_SAMPLE_ROOM_URL=
|
||||
AWS_SECRET_ACCESS_KEY=
|
||||
AWS_ACCESS_KEY_ID=
|
||||
AWS_REGION=
|
||||
249
examples/aws-strands/explain-thinking.py
Normal file
249
examples/aws-strands/explain-thinking.py
Normal file
@@ -0,0 +1,249 @@
|
||||
#
|
||||
# Copyright (c) 2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import os
|
||||
import threading
|
||||
import time
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from strands import Agent, tool
|
||||
from strands.models import BedrockModel
|
||||
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.llm_service import FunctionCallParams
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
|
||||
from pipecat.transports.services.daily import DailyParams
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
"""This example demonstrates how to use the Strands agent with Pipecat in a way where the agent explains its reasoning step-by-step.
|
||||
|
||||
You can delegate complex, multi-step tasks to the Strands agent, which can cycle through LLM-based reasoning and tool calls to accomplish the task.
|
||||
|
||||
Try asking: "What's the weather where the Golden Gate Bridge is?"
|
||||
"""
|
||||
|
||||
|
||||
# Strands agent tools
|
||||
|
||||
|
||||
@tool
|
||||
def get_location_name_from_landmark(landmark: str) -> str:
|
||||
"""
|
||||
Get the location name from a landmark.
|
||||
|
||||
Args:
|
||||
landmark (str): The name of the landmark, e.g. "Golden Gate Bridge".
|
||||
"""
|
||||
# Simulate fetching location (slowly)
|
||||
time.sleep(3)
|
||||
return "San Francisco, CA"
|
||||
|
||||
|
||||
@tool
|
||||
def get_lat_long_from_location_name(location: str) -> dict:
|
||||
"""
|
||||
Get the latitude and longitude for a location name.
|
||||
|
||||
Args:
|
||||
location (str): The city and state, e.g. "San Francisco, CA".
|
||||
"""
|
||||
# Simulate fetching lat/long from a geocoding service (slowly)
|
||||
time.sleep(3)
|
||||
return {"lat": 37.7749, "long": -122.4194}
|
||||
|
||||
|
||||
@tool
|
||||
def get_current_weather_from_lat_long(lat: float, long: float) -> dict:
|
||||
"""
|
||||
Get the current weather for a specific latitude and longitude.
|
||||
|
||||
Args:
|
||||
lat (float): The latitude of the location.
|
||||
long (float): The longitude of the location.
|
||||
"""
|
||||
# Simulate fetching weather data from a weather service (slowly)
|
||||
time.sleep(3)
|
||||
return {"conditions": "nice", "temperature": "75"}
|
||||
|
||||
|
||||
# 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_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
"twilio": lambda: FastAPIWebsocketParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
"webrtc": lambda: TransportParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
)
|
||||
|
||||
next_strands_message_is_last = False
|
||||
strands_messages_queue = asyncio.Queue()
|
||||
|
||||
def strands_callback_handler(**kwargs):
|
||||
"""
|
||||
Handle events from the Strands agent.
|
||||
"""
|
||||
nonlocal next_strands_message_is_last
|
||||
if "event" in kwargs:
|
||||
event_obj = kwargs["event"]
|
||||
if event_obj and "messageStop" in event_obj:
|
||||
message_stop = event_obj["messageStop"]
|
||||
if message_stop and "stopReason" in message_stop:
|
||||
stop_reason = message_stop["stopReason"]
|
||||
if stop_reason == "end_turn":
|
||||
next_strands_message_is_last = True
|
||||
elif "message" in kwargs:
|
||||
message_obj = kwargs["message"]
|
||||
if message_obj and "content" in message_obj and "role" in message_obj:
|
||||
role = message_obj["role"]
|
||||
content = message_obj["content"]
|
||||
if role == "assistant" and isinstance(content, list):
|
||||
for content_obj in content:
|
||||
if isinstance(content_obj, dict) and "text" in content_obj:
|
||||
message = content_obj["text"]
|
||||
if not next_strands_message_is_last:
|
||||
strands_messages_queue.put_nowait(message)
|
||||
|
||||
async def process_strands_messages():
|
||||
while True:
|
||||
message = await strands_messages_queue.get()
|
||||
await tts.queue_frame(TTSSpeakFrame(message))
|
||||
strands_messages_queue.task_done()
|
||||
|
||||
asyncio.create_task(process_strands_messages())
|
||||
|
||||
strands_agent = Agent(
|
||||
model=BedrockModel(
|
||||
model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0", max_tokens=64000
|
||||
),
|
||||
tools=[
|
||||
get_location_name_from_landmark,
|
||||
get_lat_long_from_location_name,
|
||||
get_current_weather_from_lat_long,
|
||||
],
|
||||
system_prompt="""
|
||||
You are a helpful personal assistant who can look up information about places and weather.
|
||||
|
||||
Your key capabilities:
|
||||
1. Look up where landmarks are located.
|
||||
2. Find latitude and longitude for a location.
|
||||
3. Look up the current weather for a specific latitude and longitude.
|
||||
|
||||
Explain each step of your reasoning in clear, simple, and concise language. Your responses will be converted to audio, so avoid special characters and numbered lists.
|
||||
""",
|
||||
callback_handler=strands_callback_handler,
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
|
||||
async def handle_location_or_weather_related_queries(params: FunctionCallParams, query: str):
|
||||
"""
|
||||
Handle location or weather related queries.
|
||||
|
||||
Args:
|
||||
query (str): The user's query, e.g. "What's the weather where the Golden Gate Bridge is?".
|
||||
"""
|
||||
# Run in a background thread
|
||||
# (Otherwise the agent blocks the event loop; one effect of that is that we don't hear
|
||||
# the agent's "thinking" messages until the agent finishes)
|
||||
loop = asyncio.get_running_loop()
|
||||
result = await loop.run_in_executor(None, strands_agent, query)
|
||||
await params.result_callback(result.message)
|
||||
|
||||
llm.register_direct_function(handle_location_or_weather_related_queries)
|
||||
|
||||
@llm.event_handler("on_function_calls_started")
|
||||
async def on_function_calls_started(service, function_calls):
|
||||
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
|
||||
|
||||
tools = ToolsSchema(standard_tools=[handle_location_or_weather_related_queries])
|
||||
|
||||
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. Start by suggesting that the user ask about the weather where the Golden Gate Bridge is.",
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
logger.info(f"Client disconnected")
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner(handle_sigint=handle_sigint)
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from pipecat.examples.run import main
|
||||
|
||||
main(run_example, transport_params=transport_params)
|
||||
6
examples/aws-strands/requirements.txt
Normal file
6
examples/aws-strands/requirements.txt
Normal file
@@ -0,0 +1,6 @@
|
||||
fastapi
|
||||
uvicorn
|
||||
python-dotenv
|
||||
pipecat-ai[webrtc,daily,deepgram,cartesia]
|
||||
pipecat-ai-small-webrtc-prebuilt
|
||||
strands-agents
|
||||
45
examples/bot-ready-signalling/README.md
Normal file
45
examples/bot-ready-signalling/README.md
Normal file
@@ -0,0 +1,45 @@
|
||||
# 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
|
||||
27
examples/bot-ready-signalling/client/javascript/README.md
Normal file
27
examples/bot-ready-signalling/client/javascript/README.md
Normal file
@@ -0,0 +1,27 @@
|
||||
# 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.
|
||||
34
examples/bot-ready-signalling/client/javascript/index.html
Normal file
34
examples/bot-ready-signalling/client/javascript/index.html
Normal file
@@ -0,0 +1,34 @@
|
||||
<!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>
|
||||
1076
examples/bot-ready-signalling/client/javascript/package-lock.json
generated
Normal file
1076
examples/bot-ready-signalling/client/javascript/package-lock.json
generated
Normal file
File diff suppressed because it is too large
Load Diff
20
examples/bot-ready-signalling/client/javascript/package.json
Normal file
20
examples/bot-ready-signalling/client/javascript/package.json
Normal file
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"name": "client",
|
||||
"version": "1.0.0",
|
||||
"main": "index.js",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "vite build",
|
||||
"preview": "vite preview"
|
||||
},
|
||||
"keywords": [],
|
||||
"author": "",
|
||||
"license": "ISC",
|
||||
"description": "",
|
||||
"devDependencies": {
|
||||
"vite": "^6.3.5"
|
||||
},
|
||||
"dependencies": {
|
||||
"@daily-co/daily-js": "0.74.0"
|
||||
}
|
||||
}
|
||||
216
examples/bot-ready-signalling/client/javascript/src/app.js
Normal file
216
examples/bot-ready-signalling/client/javascript/src/app.js
Normal file
@@ -0,0 +1,216 @@
|
||||
/**
|
||||
* 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();
|
||||
});
|
||||
@@ -0,0 +1,98 @@
|
||||
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;
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
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,
|
||||
},
|
||||
},
|
||||
},
|
||||
});
|
||||
1
examples/bot-ready-signalling/client/react-native/.nvmrc
Normal file
1
examples/bot-ready-signalling/client/react-native/.nvmrc
Normal file
@@ -0,0 +1 @@
|
||||
22.14
|
||||
60
examples/bot-ready-signalling/client/react-native/README.md
Normal file
60
examples/bot-ready-signalling/client/react-native/README.md
Normal file
@@ -0,0 +1,60 @@
|
||||
# React Native Implementation
|
||||
|
||||
Basic implementation using the [Pipecat React Native SDK](https://docs.pipecat.ai/client/react-native/introduction).
|
||||
|
||||
## Usage
|
||||
|
||||
### Expo requirements
|
||||
|
||||
This project cannot be used with an [Expo Go](https://docs.expo.dev/workflow/expo-go/) app because [it requires custom native code](https://docs.expo.io/workflow/customizing/).
|
||||
|
||||
When a project requires custom native code or a config plugin, we need to transition from using [Expo Go](https://docs.expo.dev/workflow/expo-go/)
|
||||
to a [development build](https://docs.expo.dev/development/introduction/).
|
||||
|
||||
More details about the custom native code used by this demo can be found in [rn-daily-js-expo-config-plugin](https://github.com/daily-co/rn-daily-js-expo-config-plugin).
|
||||
|
||||
### Building remotely
|
||||
|
||||
If you do not have experience with Xcode and Android Studio builds or do not have them installed locally on your computer, you will need to follow [this guide from Expo to use EAS Build](https://docs.expo.dev/development/create-development-builds/#create-and-install-eas-build).
|
||||
|
||||
### Building locally
|
||||
|
||||
You will need to have installed locally on your computer:
|
||||
- [Xcode](https://developer.apple.com/xcode/) to build for iOS;
|
||||
- [Android Studio](https://developer.android.com/studio) to build for Android;
|
||||
|
||||
#### Install the demo dependencies
|
||||
|
||||
```bash
|
||||
# Use the version of node specified in .nvmrc
|
||||
nvm i
|
||||
|
||||
# Install dependencies
|
||||
npm i
|
||||
|
||||
# Before a native app can be compiled, the native source code must be generated.
|
||||
npx expo prebuild
|
||||
|
||||
# Configure the environment variable to connect to the local server
|
||||
cp env.example .env
|
||||
# edit .env and add your local ip address, for example: http://192.168.1.16:7860
|
||||
```
|
||||
|
||||
#### Running on Android
|
||||
|
||||
After plugging in an Android device [configured for debugging](https://developer.android.com/studio/debug/dev-options), run the following command:
|
||||
|
||||
```
|
||||
npm run android
|
||||
```
|
||||
|
||||
#### Running on iOS
|
||||
|
||||
Run the following command:
|
||||
|
||||
```
|
||||
npm run ios
|
||||
```
|
||||
|
||||
#### Connect to the server
|
||||
Use the http://localhost:5173 in your app.
|
||||
75
examples/bot-ready-signalling/client/react-native/app.json
Normal file
75
examples/bot-ready-signalling/client/react-native/app.json
Normal file
@@ -0,0 +1,75 @@
|
||||
{
|
||||
"expo": {
|
||||
"name": "bot-ready-rn",
|
||||
"slug": "bot-ready-rn",
|
||||
"version": "1.0.0",
|
||||
"orientation": "portrait",
|
||||
"icon": "./assets/icon.png",
|
||||
"userInterfaceStyle": "light",
|
||||
"splash": {
|
||||
"image": "./assets/splash.png",
|
||||
"resizeMode": "contain",
|
||||
"backgroundColor": "#ffffff"
|
||||
},
|
||||
"updates": {
|
||||
"fallbackToCacheTimeout": 0
|
||||
},
|
||||
"assetBundlePatterns": [
|
||||
"**/*"
|
||||
],
|
||||
"ios": {
|
||||
"supportsTablet": true,
|
||||
"bitcode": false,
|
||||
"bundleIdentifier": "co.daily.expo.BotReady",
|
||||
"infoPlist": {
|
||||
"UIBackgroundModes": [
|
||||
"voip"
|
||||
]
|
||||
},
|
||||
"appleTeamId": "EEBGKV9N3N"
|
||||
},
|
||||
"android": {
|
||||
"adaptiveIcon": {
|
||||
"foregroundImage": "./assets/adaptive-icon.png",
|
||||
"backgroundColor": "#FFFFFF"
|
||||
},
|
||||
"package": "co.daily.expo.BotReady",
|
||||
"permissions": [
|
||||
"android.permission.ACCESS_NETWORK_STATE",
|
||||
"android.permission.BLUETOOTH",
|
||||
"android.permission.CAMERA",
|
||||
"android.permission.INTERNET",
|
||||
"android.permission.MODIFY_AUDIO_SETTINGS",
|
||||
"android.permission.RECORD_AUDIO",
|
||||
"android.permission.SYSTEM_ALERT_WINDOW",
|
||||
"android.permission.WAKE_LOCK",
|
||||
"android.permission.FOREGROUND_SERVICE",
|
||||
"android.permission.FOREGROUND_SERVICE_CAMERA",
|
||||
"android.permission.FOREGROUND_SERVICE_MICROPHONE",
|
||||
"android.permission.FOREGROUND_SERVICE_MEDIA_PROJECTION",
|
||||
"android.permission.POST_NOTIFICATIONS"
|
||||
]
|
||||
},
|
||||
"web": {
|
||||
"favicon": "./assets/favicon.png"
|
||||
},
|
||||
"plugins": [
|
||||
"@config-plugins/react-native-webrtc",
|
||||
"@daily-co/config-plugin-rn-daily-js",
|
||||
[
|
||||
"expo-build-properties",
|
||||
{
|
||||
"android": {
|
||||
"minSdkVersion": 24,
|
||||
"compileSdkVersion": 35,
|
||||
"targetSdkVersion": 34,
|
||||
"buildToolsVersion": "35.0.0"
|
||||
},
|
||||
"ios": {
|
||||
"deploymentTarget": "15.1"
|
||||
}
|
||||
}
|
||||
]
|
||||
]
|
||||
}
|
||||
}
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 17 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 1.4 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 22 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 46 KiB |
@@ -0,0 +1,7 @@
|
||||
module.exports = function(api) {
|
||||
api.cache(true);
|
||||
return {
|
||||
presets: ['babel-preset-expo'],
|
||||
plugins: [["module:react-native-dotenv"]],
|
||||
};
|
||||
};
|
||||
@@ -0,0 +1 @@
|
||||
API_BASE_URL=http://YOUR_LOCAL_IP:7860
|
||||
7
examples/bot-ready-signalling/client/react-native/index.js
vendored
Normal file
7
examples/bot-ready-signalling/client/react-native/index.js
vendored
Normal file
@@ -0,0 +1,7 @@
|
||||
import { registerRootComponent } from "expo";
|
||||
|
||||
import App from "./src/App";
|
||||
|
||||
// registerRootComponent calls AppRegistry.registerComponent('main', () => App);
|
||||
// It also ensures that the environment is set up appropriately
|
||||
registerRootComponent(App);
|
||||
@@ -0,0 +1,4 @@
|
||||
// Learn more https://docs.expo.io/guides/customizing-metro
|
||||
const { getDefaultConfig } = require('expo/metro-config');
|
||||
|
||||
module.exports = getDefaultConfig(__dirname);
|
||||
10627
examples/bot-ready-signalling/client/react-native/package-lock.json
generated
Normal file
10627
examples/bot-ready-signalling/client/react-native/package-lock.json
generated
Normal file
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"name": "bot-ready-rn",
|
||||
"version": "1.0.0",
|
||||
"scripts": {
|
||||
"start": "expo start --dev-client",
|
||||
"android": "expo run:android --device",
|
||||
"ios": "expo run:ios --device",
|
||||
"web": "expo start --web"
|
||||
},
|
||||
"dependencies": {
|
||||
"@config-plugins/react-native-webrtc": "^10.0.0",
|
||||
"@daily-co/config-plugin-rn-daily-js": "0.0.7",
|
||||
"@daily-co/react-native-daily-js": "^0.70.0",
|
||||
"@daily-co/react-native-webrtc": "^118.0.3-daily.2",
|
||||
"@react-native-async-storage/async-storage": "1.23.1",
|
||||
"expo": "^52.0.0",
|
||||
"expo-build-properties": "~0.13.1",
|
||||
"expo-dev-client": "~5.0.5",
|
||||
"expo-splash-screen": "~0.29.16",
|
||||
"expo-status-bar": "~2.0.0",
|
||||
"react": "18.3.1",
|
||||
"react-native": "0.76.3",
|
||||
"react-native-background-timer": "^2.4.1",
|
||||
"react-native-dotenv": "^3.4.11",
|
||||
"react-native-get-random-values": "^1.11.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@babel/core": "^7.12.9"
|
||||
},
|
||||
"private": true
|
||||
}
|
||||
121
examples/bot-ready-signalling/client/react-native/src/App.js
vendored
Normal file
121
examples/bot-ready-signalling/client/react-native/src/App.js
vendored
Normal file
@@ -0,0 +1,121 @@
|
||||
import React, { useState, useEffect } from 'react';
|
||||
import {SafeAreaView, View, Text, Button, StyleSheet, ScrollView} from 'react-native';
|
||||
import Daily from "@daily-co/react-native-daily-js";
|
||||
import { API_BASE_URL } from "@env";
|
||||
|
||||
const CallScreen = () => {
|
||||
const [connectionStatus, setConnectionStatus] = useState('Disconnected');
|
||||
const [isConnected, setIsConnected] = useState(false);
|
||||
const [callObject, setCallObject] = useState(null);
|
||||
const [logs, setLogs] = useState([]);
|
||||
|
||||
useEffect(() => {
|
||||
if (callObject) {
|
||||
setupTrackListeners(callObject);
|
||||
}
|
||||
}, [callObject]);
|
||||
|
||||
const log = (message) => {
|
||||
setLogs((prevLogs) => [...prevLogs, `${new Date().toISOString()} - ${message}`]);
|
||||
console.log(message);
|
||||
};
|
||||
|
||||
const setupTrackListeners = (callObject) => {
|
||||
callObject.on("joined-meeting", () => {
|
||||
setConnectionStatus('Connected');
|
||||
setIsConnected(true);
|
||||
log('Client connected');
|
||||
});
|
||||
callObject.on("left-meeting", () => {
|
||||
setConnectionStatus('Disconnected');
|
||||
setIsConnected(false);
|
||||
log('Client disconnected');
|
||||
});
|
||||
callObject.on("participant-left", () => {
|
||||
// When the bot leaves, we are also disconnecting from the call
|
||||
disconnect().catch((err) => {
|
||||
log(`Failed to disconnect ${err}`);
|
||||
})
|
||||
});
|
||||
// Trigger so the bot can start sending audio
|
||||
callObject.on("track-started", (evt) => {
|
||||
if (evt.track.kind === "audio" && evt.participant.local === false) {
|
||||
handleEventToConsole(evt)
|
||||
log("Sending the message that will trigger the bot to play the audio.")
|
||||
callObject.sendAppMessage("playable")
|
||||
}
|
||||
});
|
||||
callObject.on("error", (evt) => log(`Error: ${evt.error}`));
|
||||
// Other events just for awareness
|
||||
callObject.on("track-stopped", handleEventToConsole);
|
||||
callObject.on("participant-joined", handleEventToConsole);
|
||||
callObject.on("participant-updated", handleEventToConsole);
|
||||
};
|
||||
|
||||
const handleEventToConsole = (evt) => {
|
||||
log(`Received event: ${evt.action}`);
|
||||
};
|
||||
|
||||
const connect = async () => {
|
||||
try {
|
||||
const callObject = Daily.createCallObject({ subscribeToTracksAutomatically: true });
|
||||
setCallObject(callObject);
|
||||
const connectionUrl = `${API_BASE_URL}/connect`
|
||||
const res = await fetch(connectionUrl, { method: "POST", headers: { "Content-Type": "application/json" } });
|
||||
const roomInfo = await res.json();
|
||||
await callObject.join({ url: roomInfo.room_url });
|
||||
} catch (error) {
|
||||
log(`Error connecting: ${error.message}`);
|
||||
}
|
||||
};
|
||||
|
||||
const disconnect = async () => {
|
||||
if (callObject) {
|
||||
try {
|
||||
await callObject.leave();
|
||||
await callObject.destroy();
|
||||
setCallObject(null);
|
||||
} catch (error) {
|
||||
log(`Error disconnecting: ${error.message}`);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
return (
|
||||
<SafeAreaView style={styles.safeArea}>
|
||||
<View style={styles.container}>
|
||||
<View style={styles.statusBar}>
|
||||
<Text>Status: <Text style={styles.status}>{connectionStatus}</Text></Text>
|
||||
<View style={styles.controls}>
|
||||
<Button
|
||||
title={isConnected ? "Disconnect" : "Connect"}
|
||||
onPress={isConnected ? disconnect : connect}
|
||||
/>
|
||||
</View>
|
||||
</View>
|
||||
|
||||
<View style={styles.debugPanel}>
|
||||
<Text style={styles.debugTitle}>Debug Info</Text>
|
||||
<ScrollView style={styles.debugLog}>
|
||||
{logs.map((logEntry, index) => (
|
||||
<Text key={index} style={styles.logText}>{logEntry}</Text>
|
||||
))}
|
||||
</ScrollView>
|
||||
</View>
|
||||
</View>
|
||||
</SafeAreaView>
|
||||
);
|
||||
};
|
||||
|
||||
const styles = StyleSheet.create({
|
||||
safeArea: { flex: 1, backgroundColor: '#f0f0f0', padding: 20 },
|
||||
container: { flex: 1, margin: 20 },
|
||||
statusBar: { flexDirection: 'row', justifyContent: 'space-between', alignItems: 'center', padding: 10, backgroundColor: '#fff', borderRadius: 8, marginBottom: 20 },
|
||||
status: { fontWeight: 'bold' },
|
||||
controls: { flexDirection: 'row', gap: 10 },
|
||||
debugPanel: { height: '80%', backgroundColor: '#fff', borderRadius: 8, padding: 20},
|
||||
debugTitle: { fontSize: 16, fontWeight: 'bold' },
|
||||
debugLog: { height: '100%', overflow: 'scroll', backgroundColor: '#f8f8f8', padding: 10, borderRadius: 4, fontFamily: 'monospace', fontSize: 12, lineHeight: 1.4 },
|
||||
});
|
||||
|
||||
export default CallScreen;
|
||||
50
examples/bot-ready-signalling/server/README.md
Normal file
50
examples/bot-ready-signalling/server/README.md
Normal file
@@ -0,0 +1,50 @@
|
||||
# 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
|
||||
```
|
||||
3
examples/bot-ready-signalling/server/env.example
Normal file
3
examples/bot-ready-signalling/server/env.example
Normal file
@@ -0,0 +1,3 @@
|
||||
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=
|
||||
4
examples/bot-ready-signalling/server/requirements.txt
Normal file
4
examples/bot-ready-signalling/server/requirements.txt
Normal file
@@ -0,0 +1,4 @@
|
||||
python-dotenv
|
||||
fastapi[all]
|
||||
uvicorn
|
||||
pipecat-ai[daily,cartesia,openai]
|
||||
64
examples/bot-ready-signalling/server/runner.py
Normal file
64
examples/bot-ready-signalling/server/runner.py
Normal file
@@ -0,0 +1,64 @@
|
||||
#
|
||||
# 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)
|
||||
147
examples/bot-ready-signalling/server/server.py
Normal file
147
examples/bot-ready-signalling/server/server.py
Normal file
@@ -0,0 +1,147 @@
|
||||
#
|
||||
# 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,
|
||||
)
|
||||
95
examples/bot-ready-signalling/server/signalling_bot.py
Normal file
95
examples/bot-ready-signalling/server/signalling_bot.py
Normal file
@@ -0,0 +1,95 @@
|
||||
#
|
||||
# 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 PipelineTask
|
||||
from pipecat.services.cartesia.tts 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="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading 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())
|
||||
161
examples/chatbot-audio-recording/.gitignore
vendored
Normal file
161
examples/chatbot-audio-recording/.gitignore
vendored
Normal file
@@ -0,0 +1,161 @@
|
||||
# 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
|
||||
15
examples/chatbot-audio-recording/Dockerfile
Normal file
15
examples/chatbot-audio-recording/Dockerfile
Normal file
@@ -0,0 +1,15 @@
|
||||
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"]
|
||||
37
examples/chatbot-audio-recording/README.md
Normal file
37
examples/chatbot-audio-recording/README.md
Normal file
@@ -0,0 +1,37 @@
|
||||
# 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
|
||||
```
|
||||
170
examples/chatbot-audio-recording/bot.py
Normal file
170
examples/chatbot-audio-recording/bot.py
Normal file
@@ -0,0 +1,170 @@
|
||||
#
|
||||
# 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.tts import ElevenLabsTTSService
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
# Create the recordings directory if it doesn't exist
|
||||
os.makedirs("recordings", exist_ok=True)
|
||||
|
||||
|
||||
async def save_audio(audio: bytes, sample_rate: int, num_channels: int, name: str):
|
||||
if len(audio) > 0:
|
||||
filename = os.path.join(
|
||||
"recordings",
|
||||
f"{name}_conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav",
|
||||
)
|
||||
with io.BytesIO() as buffer:
|
||||
with wave.open(buffer, "wb") as wf:
|
||||
wf.setsampwidth(2)
|
||||
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,
|
||||
video_out_enabled=False,
|
||||
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"))
|
||||
|
||||
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(enable_turn_audio=True)
|
||||
|
||||
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,
|
||||
params=PipelineParams(
|
||||
audio_in_sample_rate=16000,
|
||||
audio_out_sample_rate=16000,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=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, "full")
|
||||
|
||||
@audiobuffer.event_handler("on_user_turn_audio_data")
|
||||
async def on_user_turn_audio_data(buffer, audio, sample_rate, num_channels):
|
||||
await save_audio(audio, sample_rate, num_channels, "user")
|
||||
|
||||
@audiobuffer.event_handler("on_bot_turn_audio_data")
|
||||
async def on_bot_turn_audio_data(buffer, audio, sample_rate, num_channels):
|
||||
await save_audio(audio, sample_rate, num_channels, "bot")
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
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())
|
||||
4
examples/chatbot-audio-recording/env.example
Normal file
4
examples/chatbot-audio-recording/env.example
Normal file
@@ -0,0 +1,4 @@
|
||||
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...
|
||||
5
examples/chatbot-audio-recording/requirements.txt
Normal file
5
examples/chatbot-audio-recording/requirements.txt
Normal file
@@ -0,0 +1,5 @@
|
||||
aiofiles
|
||||
python-dotenv
|
||||
fastapi[all]
|
||||
uvicorn
|
||||
pipecat-ai[daily,openai,silero,elevenlabs]
|
||||
55
examples/chatbot-audio-recording/runner.py
Normal file
55
examples/chatbot-audio-recording/runner.py
Normal file
@@ -0,0 +1,55 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
|
||||
import aiohttp
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
|
||||
|
||||
|
||||
async def configure(aiohttp_session: aiohttp.ClientSession):
|
||||
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
|
||||
parser.add_argument(
|
||||
"-u", "--url", type=str, required=False, help="URL of the Daily room to join"
|
||||
)
|
||||
parser.add_argument(
|
||||
"-k",
|
||||
"--apikey",
|
||||
type=str,
|
||||
required=False,
|
||||
help="Daily API Key (needed to create an owner token for the room)",
|
||||
)
|
||||
|
||||
args, unknown = parser.parse_known_args()
|
||||
|
||||
url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
|
||||
key = args.apikey or os.getenv("DAILY_API_KEY")
|
||||
|
||||
if not url:
|
||||
raise Exception(
|
||||
"No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
|
||||
)
|
||||
|
||||
if not key:
|
||||
raise Exception(
|
||||
"No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
|
||||
)
|
||||
|
||||
daily_rest_helper = DailyRESTHelper(
|
||||
daily_api_key=key,
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
aiohttp_session=aiohttp_session,
|
||||
)
|
||||
|
||||
# Create a meeting token for the given room with an expiration 1 hour in
|
||||
# the future.
|
||||
expiry_time: float = 60 * 60
|
||||
|
||||
token = await daily_rest_helper.get_token(url, expiry_time)
|
||||
|
||||
return (url, token)
|
||||
139
examples/chatbot-audio-recording/server.py
Normal file
139
examples/chatbot-audio-recording/server.py
Normal file
@@ -0,0 +1,139 @@
|
||||
#
|
||||
# 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,
|
||||
)
|
||||
39
examples/daily-custom-tracks/README.md
Normal file
39
examples/daily-custom-tracks/README.md
Normal file
@@ -0,0 +1,39 @@
|
||||
# Daily Custom Tracks
|
||||
|
||||
This example shows how to send and receive Daily custom tracks. We will run a simple `daily-python` application to send an audio file with a custom track (named "pipecat") to a room. Then, the Pipecat bot will mirror that custom track into another custom track (named "pipecat-mirror") in the same room.
|
||||
|
||||
## Get started
|
||||
|
||||
```python
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
## Run the bot
|
||||
|
||||
Start the bot by giving it a Daily room URL.
|
||||
|
||||
```bash
|
||||
python bot.py -u ROOM_URL
|
||||
```
|
||||
|
||||
The bot will wait for the first participant to join. Then, it will mirror a custom track named "pipecat" into a new custom track named "pipecat-mirror".
|
||||
|
||||
## Run the sender
|
||||
|
||||
Now, run the custom track sender. This is a simple `daily-python` application that opens and audio file and sends it as a custom track to the same Daily room.
|
||||
|
||||
```bash
|
||||
python custom_track_sender.py -u ROOM_URL -i office-ambience-mono-16000.mp3
|
||||
```
|
||||
|
||||
## Open client
|
||||
|
||||
Finally, open the client so you can hear both custom tracks.
|
||||
|
||||
```bash
|
||||
open index.html
|
||||
```
|
||||
|
||||
Once the client is opened, copy the URL of the Daily room and join it. You should be able to select which custom track you want to hear.
|
||||
89
examples/daily-custom-tracks/bot.py
Normal file
89
examples/daily-custom-tracks/bot.py
Normal file
@@ -0,0 +1,89 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import Frame, InputAudioRawFrame, OutputAudioRawFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
class CustomTrackMirrorProcessor(FrameProcessor):
|
||||
def __init__(self, transport_destination: str, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._transport_destination = transport_destination
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, InputAudioRawFrame) and frame.transport_source:
|
||||
output_frame = OutputAudioRawFrame(
|
||||
audio=frame.audio,
|
||||
sample_rate=frame.sample_rate,
|
||||
num_channels=frame.num_channels,
|
||||
)
|
||||
output_frame.transport_destination = self._transport_destination
|
||||
await self.push_frame(output_frame)
|
||||
else:
|
||||
await self.push_frame(frame, direction)
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
None,
|
||||
"Custom tracks mirror",
|
||||
DailyParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
microphone_out_enabled=False, # Disable since we just use custom tracks
|
||||
audio_out_destinations=["pipecat-mirror"],
|
||||
),
|
||||
)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
CustomTrackMirrorProcessor("pipecat-mirror"),
|
||||
transport.output(), # Transport bot output
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
audio_in_sample_rate=16000,
|
||||
audio_out_sample_rate=16000,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_audio(participant["id"], audio_source="pipecat")
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
74
examples/daily-custom-tracks/custom_track_sender.py
Normal file
74
examples/daily-custom-tracks/custom_track_sender.py
Normal file
@@ -0,0 +1,74 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import time
|
||||
|
||||
from daily import CallClient, CustomAudioSource, Daily
|
||||
from pydub import AudioSegment
|
||||
|
||||
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
|
||||
parser.add_argument("-u", "--url", type=str, required=True, help="URL of the Daily room to join")
|
||||
parser.add_argument(
|
||||
"-i", "--input", type=str, required=True, help="Input audio file (needs 16000 sample rate)"
|
||||
)
|
||||
|
||||
args, _ = parser.parse_known_args()
|
||||
|
||||
audio = AudioSegment.from_mp3(args.input)
|
||||
|
||||
raw_bytes = audio.raw_data
|
||||
sample_rate = audio.frame_rate
|
||||
channels = audio.channels
|
||||
|
||||
print(f"Length: {len(raw_bytes)} bytes")
|
||||
print(f"Sample rate: {sample_rate}, Channels: {channels}")
|
||||
|
||||
# Initialize the Daily context & create call client
|
||||
Daily.init()
|
||||
|
||||
client = CallClient()
|
||||
|
||||
# Join the room and indicate we have a custom track named "pipecat".
|
||||
client.join(
|
||||
args.url,
|
||||
client_settings={
|
||||
"publishing": {
|
||||
"camera": False,
|
||||
"microphone": False,
|
||||
"customAudio": {"pipecat": True},
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
# Just sleep for a couple of seconds. To do this well we should really use
|
||||
# completions.
|
||||
time.sleep(2)
|
||||
|
||||
# Create the custom audio source. This is where we will write our audio.
|
||||
audio_source = CustomAudioSource(sample_rate, channels)
|
||||
|
||||
# Create an audio track and assign it our audio source.
|
||||
client.add_custom_audio_track("pipecat", audio_source)
|
||||
|
||||
# Just sleep for a second. To do this well we should really use completions.
|
||||
time.sleep(1)
|
||||
|
||||
try:
|
||||
# Just write one second of audio until we have read all the file.
|
||||
chunk_size = sample_rate * channels * 2
|
||||
while len(raw_bytes) > 0:
|
||||
chunk = raw_bytes[:chunk_size]
|
||||
raw_bytes = raw_bytes[chunk_size:]
|
||||
audio_source.write_frames(chunk)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
client.leave()
|
||||
|
||||
# Just sleep for a second. To do this well we should really use completions.
|
||||
time.sleep(1)
|
||||
|
||||
client.release()
|
||||
173
examples/daily-custom-tracks/index.html
Normal file
173
examples/daily-custom-tracks/index.html
Normal file
@@ -0,0 +1,173 @@
|
||||
<html>
|
||||
<head>
|
||||
<title>daily custom tracks</title>
|
||||
</head>
|
||||
<script crossorigin src="https://unpkg.com/@daily-co/daily-js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.js"></script>
|
||||
<link
|
||||
rel="stylesheet"
|
||||
type="text/css"
|
||||
href="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.css"
|
||||
/>
|
||||
<script>
|
||||
function enableButton(buttonId, enable) {
|
||||
const button = document.getElementById(buttonId);
|
||||
button.disabled = !enable;
|
||||
}
|
||||
|
||||
function enableJoinButton(enable) {
|
||||
enableButton("join-button", enable);
|
||||
}
|
||||
|
||||
function enableLeaveButton(enable) {
|
||||
enableButton("leave-button", enable);
|
||||
}
|
||||
|
||||
function destroyPlayers(query) {
|
||||
const items = document.querySelectorAll(query);
|
||||
if (items) {
|
||||
for (const item of items) {
|
||||
item.remove();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function destroyParticipantPlayers(participantId) {
|
||||
destroyPlayers(`audio[data-participant-id="${participantId}"]`);
|
||||
destroyPlayers(`button[data-participant-id="${participantId}"]`);
|
||||
}
|
||||
|
||||
async function startPlayer(player, track) {
|
||||
player.muted = false;
|
||||
player.autoplay = true;
|
||||
if (track != null) {
|
||||
player.srcObject = new MediaStream([track]);
|
||||
}
|
||||
}
|
||||
|
||||
async function buildAudioPlayer(track, participantId) {
|
||||
const audioContainer = document.getElementById("audio-container");
|
||||
const player = document.createElement("audio");
|
||||
player.dataset.participantId = participantId;
|
||||
|
||||
// Create a new button for controlling audio
|
||||
const audioControlButton = document.createElement("button");
|
||||
audioControlButton.className = "ui primary green button"
|
||||
audioControlButton.innerText = track._mediaTag == "cam-audio" ? "english" : track._mediaTag;
|
||||
audioControlButton.dataset.participantId = participantId;
|
||||
audioControlButton.onclick = () => {
|
||||
if (player.paused) {
|
||||
|
||||
player.play();
|
||||
audioControlButton.className = "ui primary red button"
|
||||
} else {
|
||||
player.pause();
|
||||
audioControlButton.className = "ui primary green button"
|
||||
}
|
||||
};
|
||||
|
||||
audioContainer.appendChild(player);
|
||||
audioContainer.appendChild(audioControlButton);
|
||||
|
||||
await startPlayer(player, track);
|
||||
player.pause()
|
||||
|
||||
return player;
|
||||
}
|
||||
|
||||
function subscribeToTracks(participantId) {
|
||||
console.log(`subscribing to track`);
|
||||
|
||||
if (participantId === "local") {
|
||||
return;
|
||||
}
|
||||
|
||||
callObject.updateParticipant(participantId, {
|
||||
setSubscribedTracks: {
|
||||
audio: true,
|
||||
video: false,
|
||||
custom: true,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
function startDaily() {
|
||||
enableJoinButton(true);
|
||||
enableLeaveButton(false);
|
||||
|
||||
window.callObject = window.DailyIframe.createCallObject({});
|
||||
|
||||
callObject.on("participant-joined", (e) => {
|
||||
if (!e.participant.local) {
|
||||
console.log("participant-joined", e.participant);
|
||||
subscribeToTracks(e.participant.session_id);
|
||||
}
|
||||
});
|
||||
|
||||
callObject.on("participant-left", (e) => {
|
||||
console.log("participant-left", e.participant.session_id);
|
||||
destroyParticipantPlayers(e.participant.session_id);
|
||||
});
|
||||
|
||||
callObject.on("track-started", async (e) => {
|
||||
console.log("track-started", e.track);
|
||||
if (e.track.kind === "audio") {
|
||||
await buildAudioPlayer(e.track, e.participant.session_id);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
async function joinRoom() {
|
||||
enableJoinButton(false);
|
||||
enableLeaveButton(true);
|
||||
|
||||
const meetingUrl = document.getElementById("meeting-url").value;
|
||||
|
||||
callObject.join({
|
||||
url: meetingUrl,
|
||||
startVideoOff: true,
|
||||
startAudioOff: true,
|
||||
subscribeToTracksAutomatically: false,
|
||||
receiveSettings: {
|
||||
base: { video: { layer: 0 } },
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
async function leaveRoom() {
|
||||
enableJoinButton(true);
|
||||
enableLeaveButton(false);
|
||||
|
||||
callObject.leave();
|
||||
|
||||
const audioContainer = document.getElementById("audio-container");
|
||||
audioContainer.replaceChildren();
|
||||
}
|
||||
</script>
|
||||
|
||||
<body onload="startDaily()">
|
||||
<div class="ui centered page grid" style="margin-top: 30px">
|
||||
<div class="ten wide column">
|
||||
<div class="ui form" style="margin-top: 30px">
|
||||
<div class="field">
|
||||
<label>Meeting URL</label>
|
||||
<input id="meeting-url" value="" />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="ui centered aligned header" style="margin-top: 30px">
|
||||
<button id="join-button" class="ui primary button" onclick="joinRoom()">
|
||||
Join
|
||||
</button>
|
||||
<button id="leave-button" class="ui button" onclick="leaveRoom()">
|
||||
Leave
|
||||
</button>
|
||||
</div>
|
||||
<div id="tile" class="ui container" style="margin-top: 30px">
|
||||
<div id="tile" class="ui center aligned grid">
|
||||
<div id="audio-container"></div><br/>
|
||||
</div>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
BIN
examples/daily-custom-tracks/office-ambience-mono-16000.mp3
Normal file
BIN
examples/daily-custom-tracks/office-ambience-mono-16000.mp3
Normal file
Binary file not shown.
2
examples/daily-custom-tracks/requirements.txt
Normal file
2
examples/daily-custom-tracks/requirements.txt
Normal file
@@ -0,0 +1,2 @@
|
||||
pydub
|
||||
pipecat-ai[daily]
|
||||
55
examples/daily-custom-tracks/runner.py
Normal file
55
examples/daily-custom-tracks/runner.py
Normal file
@@ -0,0 +1,55 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
|
||||
import aiohttp
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
|
||||
|
||||
|
||||
async def configure(aiohttp_session: aiohttp.ClientSession):
|
||||
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
|
||||
parser.add_argument(
|
||||
"-u", "--url", type=str, required=False, help="URL of the Daily room to join"
|
||||
)
|
||||
parser.add_argument(
|
||||
"-k",
|
||||
"--apikey",
|
||||
type=str,
|
||||
required=False,
|
||||
help="Daily API Key (needed to create an owner token for the room)",
|
||||
)
|
||||
|
||||
args, unknown = parser.parse_known_args()
|
||||
|
||||
url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
|
||||
key = args.apikey or os.getenv("DAILY_API_KEY")
|
||||
|
||||
if not url:
|
||||
raise Exception(
|
||||
"No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
|
||||
)
|
||||
|
||||
if not key:
|
||||
raise Exception(
|
||||
"No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
|
||||
)
|
||||
|
||||
daily_rest_helper = DailyRESTHelper(
|
||||
daily_api_key=key,
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
aiohttp_session=aiohttp_session,
|
||||
)
|
||||
|
||||
# Create a meeting token for the given room with an expiration 1 hour in
|
||||
# the future.
|
||||
expiry_time: float = 60 * 60
|
||||
|
||||
token = await daily_rest_helper.get_token(url, expiry_time)
|
||||
|
||||
return (url, token)
|
||||
15
examples/daily-multi-translation/Dockerfile
Normal file
15
examples/daily-multi-translation/Dockerfile
Normal file
@@ -0,0 +1,15 @@
|
||||
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"]
|
||||
39
examples/daily-multi-translation/README.md
Normal file
39
examples/daily-multi-translation/README.md
Normal file
@@ -0,0 +1,39 @@
|
||||
# Daily Multi Translation
|
||||
|
||||
This example shows how to use Daily to stream multiple simultaneous translations using a single transport. Daily provides custom tracks and in this example we will simultaneously translate incoming audio in English to Spanish, French and German, each of them being sent to a custom track.
|
||||
|
||||
## Get started
|
||||
|
||||
```python
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
pip install -r requirements.txt
|
||||
|
||||
cp env.example .env # and add your credentials
|
||||
|
||||
```
|
||||
|
||||
## Run the server
|
||||
|
||||
```bash
|
||||
python server.py
|
||||
```
|
||||
|
||||
Then, visit `http://localhost:7860/` in your browser. This will open a Daily Prebuilt room where you will speak in English (make sure you are not muted).
|
||||
|
||||
## Open client
|
||||
|
||||
Next, you need to open the client that will listen to the translations.
|
||||
|
||||
```bash
|
||||
open index.html
|
||||
```
|
||||
|
||||
Once the client is opened, copy the URL of the Daily room created above and join it. You should be able to select which translation you want to hear.
|
||||
|
||||
## Build and test the Docker image
|
||||
|
||||
```
|
||||
docker build -t daily-multi-translation .
|
||||
docker run --env-file .env -p 7860:7860 daily-multi-translation
|
||||
```
|
||||
163
examples/daily-multi-translation/bot.py
Normal file
163
examples/daily-multi-translation/bot.py
Normal file
@@ -0,0 +1,163 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.mixers.soundfile_mixer import SoundfileMixer
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver
|
||||
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
BACKGROUND_SOUND_FILE = "office-ambience-mono-16000.mp3"
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, token) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
"Multi translation bot",
|
||||
DailyParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
audio_out_mixer={
|
||||
"spanish": SoundfileMixer(
|
||||
sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
|
||||
),
|
||||
"french": SoundfileMixer(
|
||||
sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
|
||||
),
|
||||
"german": SoundfileMixer(
|
||||
sound_files={"office": BACKGROUND_SOUND_FILE}, default_sound="office"
|
||||
),
|
||||
},
|
||||
audio_out_destinations=["spanish", "french", "german"],
|
||||
microphone_out_enabled=False, # Disable since we just use custom tracks
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts_spanish = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="cefcb124-080b-4655-b31f-932f3ee743de",
|
||||
transport_destination="spanish",
|
||||
)
|
||||
tts_french = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="8832a0b5-47b2-4751-bb22-6a8e2149303d",
|
||||
transport_destination="french",
|
||||
)
|
||||
tts_german = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="38aabb6a-f52b-4fb0-a3d1-988518f4dc06",
|
||||
transport_destination="german",
|
||||
)
|
||||
|
||||
messages_spanish = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You will be provided with a sentence in English, and your task is to only translate it into Spanish.",
|
||||
},
|
||||
]
|
||||
messages_french = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You will be provided with a sentence in English, and your task is to only translate it into French.",
|
||||
},
|
||||
]
|
||||
messages_german = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You will be provided with a sentence in English, and your task is to only translate it into German.",
|
||||
},
|
||||
]
|
||||
|
||||
llm_spanish = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
llm_french = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
llm_german = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
|
||||
context_spanish = OpenAILLMContext(messages_spanish)
|
||||
context_aggregator_spanish = llm_spanish.create_context_aggregator(context_spanish)
|
||||
|
||||
context_french = OpenAILLMContext(messages_french)
|
||||
context_aggregator_french = llm_french.create_context_aggregator(context_french)
|
||||
|
||||
context_german = OpenAILLMContext(messages_german)
|
||||
context_aggregator_german = llm_german.create_context_aggregator(context_german)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt,
|
||||
ParallelPipeline(
|
||||
# Spanish pipeline.
|
||||
[
|
||||
context_aggregator_spanish.user(),
|
||||
llm_spanish,
|
||||
tts_spanish,
|
||||
context_aggregator_spanish.assistant(),
|
||||
],
|
||||
# French pipeline.
|
||||
[
|
||||
context_aggregator_french.user(),
|
||||
llm_french,
|
||||
tts_french,
|
||||
context_aggregator_french.assistant(),
|
||||
],
|
||||
# German pipeline.
|
||||
[
|
||||
context_aggregator_german.user(),
|
||||
llm_german,
|
||||
tts_german,
|
||||
context_aggregator_german.assistant(),
|
||||
],
|
||||
),
|
||||
transport.output(), # Transport bot output
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
audio_in_sample_rate=16000,
|
||||
audio_out_sample_rate=16000,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
observers=[TranscriptionLogObserver()],
|
||||
)
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
5
examples/daily-multi-translation/env.example
Normal file
5
examples/daily-multi-translation/env.example
Normal file
@@ -0,0 +1,5 @@
|
||||
DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
|
||||
DAILY_API_KEY=7df...
|
||||
OPENAI_API_KEY=sk-PL...
|
||||
DEEPGRAM_API_KEY=efb...
|
||||
CARTESIA_API_KEY=aeb...
|
||||
202
examples/daily-multi-translation/index.html
Normal file
202
examples/daily-multi-translation/index.html
Normal file
@@ -0,0 +1,202 @@
|
||||
<html>
|
||||
<head>
|
||||
<title>daily multi translation</title>
|
||||
</head>
|
||||
<script crossorigin src="https://unpkg.com/@daily-co/daily-js"></script>
|
||||
<script
|
||||
src="https://code.jquery.com/jquery-3.1.1.min.js"
|
||||
integrity="sha256-hVVnYaiADRTO2PzUGmuLJr8BLUSjGIZsDYGmIJLv2b8="
|
||||
crossorigin="anonymous"
|
||||
></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.js"></script>
|
||||
<link
|
||||
rel="stylesheet"
|
||||
type="text/css"
|
||||
href="https://cdnjs.cloudflare.com/ajax/libs/fomantic-ui/2.8.6/semantic.min.css"
|
||||
/>
|
||||
<script>
|
||||
function enableButton(buttonId, enable) {
|
||||
const button = document.getElementById(buttonId);
|
||||
button.disabled = !enable;
|
||||
}
|
||||
|
||||
function enableJoinButton(enable) {
|
||||
enableButton("join-button", enable);
|
||||
}
|
||||
|
||||
function enableLeaveButton(enable) {
|
||||
enableButton("leave-button", enable);
|
||||
}
|
||||
|
||||
function destroyPlayers(query) {
|
||||
const items = document.querySelectorAll(query);
|
||||
if (items) {
|
||||
for (const item of items) {
|
||||
item.remove();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function destroyParticipantPlayers(participantId) {
|
||||
destroyPlayers(`video[data-participant-id="${participantId}"]`);
|
||||
destroyPlayers(`audio[data-participant-id="${participantId}"]`);
|
||||
destroyPlayers(`button[data-participant-id="${participantId}"]`);
|
||||
}
|
||||
|
||||
async function startPlayer(player, track) {
|
||||
player.muted = false;
|
||||
player.autoplay = true;
|
||||
if (track != null) {
|
||||
player.srcObject = new MediaStream([track]);
|
||||
}
|
||||
}
|
||||
|
||||
async function buildVideoPlayer(track, participantId) {
|
||||
const videoContainer = document.getElementById("video-container");
|
||||
const player = document.createElement("video");
|
||||
player.dataset.participantId = participantId;
|
||||
|
||||
videoContainer.appendChild(player);
|
||||
|
||||
await startPlayer(player, track);
|
||||
await player.play();
|
||||
|
||||
return player;
|
||||
}
|
||||
|
||||
async function buildAudioPlayer(track, participantId) {
|
||||
const audioContainer = document.getElementById("audio-container");
|
||||
const player = document.createElement("audio");
|
||||
player.dataset.participantId = participantId;
|
||||
|
||||
// Create a new button for controlling audio
|
||||
const audioControlButton = document.createElement("button");
|
||||
audioControlButton.className = "ui primary green button"
|
||||
audioControlButton.innerText = track._mediaTag == "cam-audio" ? "english" : track._mediaTag;
|
||||
audioControlButton.dataset.participantId = participantId;
|
||||
audioControlButton.onclick = () => {
|
||||
if (player.paused) {
|
||||
|
||||
player.play();
|
||||
audioControlButton.className = "ui primary red button"
|
||||
} else {
|
||||
player.pause();
|
||||
audioControlButton.className = "ui primary green button"
|
||||
}
|
||||
};
|
||||
|
||||
audioContainer.appendChild(player);
|
||||
audioContainer.appendChild(audioControlButton);
|
||||
|
||||
await startPlayer(player, track);
|
||||
player.pause()
|
||||
|
||||
return player;
|
||||
}
|
||||
|
||||
function subscribeToTracks(participantId) {
|
||||
console.log(`subscribing to track`);
|
||||
|
||||
if (participantId === "local") {
|
||||
return;
|
||||
}
|
||||
|
||||
callObject.updateParticipant(participantId, {
|
||||
setSubscribedTracks: {
|
||||
audio: true,
|
||||
video: true,
|
||||
custom: true,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
function startDaily() {
|
||||
enableJoinButton(true);
|
||||
enableLeaveButton(false);
|
||||
|
||||
window.callObject = window.DailyIframe.createCallObject({});
|
||||
|
||||
callObject.on("participant-joined", (e) => {
|
||||
if (!e.participant.local) {
|
||||
console.log("participant-joined", e.participant);
|
||||
subscribeToTracks(e.participant.session_id);
|
||||
}
|
||||
});
|
||||
|
||||
callObject.on("participant-left", (e) => {
|
||||
console.log("participant-left", e.participant.session_id);
|
||||
destroyParticipantPlayers(e.participant.session_id);
|
||||
});
|
||||
|
||||
callObject.on("track-started", async (e) => {
|
||||
console.log("track-started", e.track);
|
||||
if (e.track.kind === "video") {
|
||||
await buildVideoPlayer(e.track, e.participant.session_id);
|
||||
} else if (e.track.kind === "audio") {
|
||||
await buildAudioPlayer(e.track, e.participant.session_id);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
async function joinRoom() {
|
||||
enableJoinButton(false);
|
||||
enableLeaveButton(true);
|
||||
|
||||
const meetingUrl = document.getElementById("meeting-url").value;
|
||||
|
||||
callObject.join({
|
||||
url: meetingUrl,
|
||||
startVideoOff: true,
|
||||
startAudioOff: true,
|
||||
subscribeToTracksAutomatically: false,
|
||||
receiveSettings: {
|
||||
base: { video: { layer: 0 } },
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
async function leaveRoom() {
|
||||
enableJoinButton(true);
|
||||
enableLeaveButton(false);
|
||||
|
||||
callObject.leave();
|
||||
|
||||
const videoContainer = document.getElementById("video-container");
|
||||
videoContainer.replaceChildren();
|
||||
|
||||
const audioContainer = document.getElementById("audio-container");
|
||||
audioContainer.replaceChildren();
|
||||
}
|
||||
</script>
|
||||
|
||||
<body onload="startDaily()">
|
||||
<div class="ui centered page grid" style="margin-top: 30px">
|
||||
<div class="ten wide column">
|
||||
<div class="ui form" style="margin-top: 30px">
|
||||
<div class="field">
|
||||
<label>Meeting URL</label>
|
||||
<input id="meeting-url" value="" />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="ui centered aligned header" style="margin-top: 30px">
|
||||
<button id="join-button" class="ui primary button" onclick="joinRoom()">
|
||||
Join
|
||||
</button>
|
||||
<button id="leave-button" class="ui button" onclick="leaveRoom()">
|
||||
Leave
|
||||
</button>
|
||||
</div>
|
||||
<div id="tile" class="ui container" style="margin-top: 30px">
|
||||
<div id="tile" class="ui center aligned grid">
|
||||
<div id="audio-container"></div><br/>
|
||||
</div>
|
||||
</div>
|
||||
<div id="tile" class="ui container" style="margin-top: 30px">
|
||||
<div id="tile" class="ui center aligned grid">
|
||||
<div id="video-container" class="ui segment"></div>
|
||||
</div>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
BIN
examples/daily-multi-translation/office-ambience-mono-16000.mp3
Normal file
BIN
examples/daily-multi-translation/office-ambience-mono-16000.mp3
Normal file
Binary file not shown.
5
examples/daily-multi-translation/requirements.txt
Normal file
5
examples/daily-multi-translation/requirements.txt
Normal file
@@ -0,0 +1,5 @@
|
||||
aiofiles
|
||||
python-dotenv
|
||||
fastapi[all]
|
||||
uvicorn
|
||||
pipecat-ai[daily,deepgram,openai,silero,cartesia,soundfile]
|
||||
55
examples/daily-multi-translation/runner.py
Normal file
55
examples/daily-multi-translation/runner.py
Normal file
@@ -0,0 +1,55 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
|
||||
import aiohttp
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
|
||||
|
||||
|
||||
async def configure(aiohttp_session: aiohttp.ClientSession):
|
||||
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
|
||||
parser.add_argument(
|
||||
"-u", "--url", type=str, required=False, help="URL of the Daily room to join"
|
||||
)
|
||||
parser.add_argument(
|
||||
"-k",
|
||||
"--apikey",
|
||||
type=str,
|
||||
required=False,
|
||||
help="Daily API Key (needed to create an owner token for the room)",
|
||||
)
|
||||
|
||||
args, unknown = parser.parse_known_args()
|
||||
|
||||
url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
|
||||
key = args.apikey or os.getenv("DAILY_API_KEY")
|
||||
|
||||
if not url:
|
||||
raise Exception(
|
||||
"No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
|
||||
)
|
||||
|
||||
if not key:
|
||||
raise Exception(
|
||||
"No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
|
||||
)
|
||||
|
||||
daily_rest_helper = DailyRESTHelper(
|
||||
daily_api_key=key,
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
aiohttp_session=aiohttp_session,
|
||||
)
|
||||
|
||||
# Create a meeting token for the given room with an expiration 1 hour in
|
||||
# the future.
|
||||
expiry_time: float = 60 * 60
|
||||
|
||||
token = await daily_rest_helper.get_token(url, expiry_time)
|
||||
|
||||
return (url, token)
|
||||
139
examples/daily-multi-translation/server.py
Normal file
139
examples/daily-multi-translation/server.py
Normal file
@@ -0,0 +1,139 @@
|
||||
#
|
||||
# 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,
|
||||
)
|
||||
13
examples/deployment/flyio-example/Dockerfile
Normal file
13
examples/deployment/flyio-example/Dockerfile
Normal file
@@ -0,0 +1,13 @@
|
||||
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}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user