Merge pull request #1343 from pipecat-ai/mb/pipecat-cloud-example
Add a Pipecat Cloud deployment example
This commit is contained in:
Mark Backman
@@ -114,6 +114,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Fixed an issue in `RimeTTSService` where the last line of text sent didn't
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result in an audio output being generated.
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### Other
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- Added a Pipecat Cloud deployment example to the `examples` directory.
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## [0.0.58] - 2025-02-26
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### Added
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94
examples/deployment/pipecat-cloud-example/.gitignore
vendored
Normal file
94
examples/deployment/pipecat-cloud-example/.gitignore
vendored
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@@ -0,0 +1,94 @@
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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build/
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dist/
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*.egg-info/
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*.egg
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.installed.cfg
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.eggs/
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downloads/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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MANIFEST
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# Virtual Environments
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venv/
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env/
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.env
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.venv/
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ENV/
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env.bak/
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venv.bak/
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# IDE
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.idea/
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.vscode/
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.spyderproject
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.spyproject
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.ropeproject
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# Testing and Coverage
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.coverage
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.coverage.*
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htmlcov/
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.pytest_cache/
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.tox/
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.nox/
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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cover/
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# Logs and Databases
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*.log
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*.db
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db.sqlite3
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db.sqlite3-journal
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pip-log.txt
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# System Files
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.DS_Store
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Thumbs.db
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desktop.ini
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*.swp
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*.swo
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*.bak
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*.tmp
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*~
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# Build and Documentation
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docs/_build/
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.pybuilder/
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target/
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instance/
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.webassets-cache
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.pdm.toml
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.pdm-python
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.pdm-build/
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__pypackages__/
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# Other
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*.mo
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*.pot
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*.sage.py
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.mypy_cache/
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.dmypy.json
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dmypy.json
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.pyre/
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.pytype/
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cython_debug/
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.ipynb_checkpoints
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# Pipecat cloud
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.pcc-deploy.toml
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7
examples/deployment/pipecat-cloud-example/Dockerfile
Normal file
7
examples/deployment/pipecat-cloud-example/Dockerfile
Normal file
@@ -0,0 +1,7 @@
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FROM dailyco/pipecat-base:latest
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COPY ./requirements.txt requirements.txt
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RUN pip install --no-cache-dir --upgrade -r requirements.txt
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COPY ./bot.py bot.py
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196
examples/deployment/pipecat-cloud-example/README.md
Normal file
196
examples/deployment/pipecat-cloud-example/README.md
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@@ -0,0 +1,196 @@
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# Pipecat Cloud Starter Project
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[](https://docs.pipecat.daily.co) [](https://discord.gg/dailyco)
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A template voice agent for [Pipecat Cloud](https://www.daily.co/products/pipecat-cloud/) that demonstrates building and deploying a conversational AI agent.
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> **For a detailed step-by-step guide, see our [Quickstart Documentation](https://docs.pipecat.daily.co/quickstart).**
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## Prerequisites
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- Python 3.10+
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- Linux, MacOS, or Windows Subsystem for Linux (WSL)
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- [Docker](https://www.docker.com) and a Docker repository (e.g., [Docker Hub](https://hub.docker.com))
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- A Docker Hub account (or other container registry account)
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- [Pipecat Cloud](https://pipecat.daily.co) account
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> **Note**: If you haven't installed Docker yet, follow the official installation guides for your platform ([Linux](https://docs.docker.com/engine/install/), [Mac](https://docs.docker.com/desktop/setup/install/mac-install/), [Windows](https://docs.docker.com/desktop/setup/install/windows-install/)). For Docker Hub, [create a free account](https://hub.docker.com/signup) and log in via terminal with `docker login`.
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## Get Started
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### 1. Get the starter project
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Clone the starter project from GitHub:
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```bash
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git clone https://github.com/daily-co/pipecat-cloud-starter
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cd pipecat-cloud-starter
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```
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### 2. Set up your Python environment
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We recommend using a virtual environment to manage your Python dependencies.
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```bash
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# Create a virtual environment
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python -m venv .venv
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# Activate it
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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# Install the Pipecat Cloud CLI
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pip install pipecatcloud
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```
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### 3. Authenticate with Pipecat Cloud
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```bash
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pcc auth login
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```
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### 4. Acquire required API keys
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This starter requires the following API keys:
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- **OpenAI API Key**: Get from [platform.openai.com/api-keys](https://platform.openai.com/api-keys)
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- **Cartesia API Key**: Get from [play.cartesia.ai/keys](https://play.cartesia.ai/keys)
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- **Daily API Key**: Automatically provided through your Pipecat Cloud account
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### 5. Configure to run locally (optional)
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You can test your agent locally before deploying to Pipecat Cloud:
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```bash
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# Set environment variables with your API keys
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export CARTESIA_API_KEY="your_cartesia_key"
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export DAILY_API_KEY="your_daily_key"
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export OPENAI_API_KEY="your_openai_key"
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```
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> Your `DAILY_API_KEY` can be found at [https://pipecat.daily.co](https://pipecat.daily.co) under the `Settings` in the `Daily (WebRTC)` tab.
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First install requirements:
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```bash
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pip install -r requirements.txt
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```
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Then, launch the bot.py script locally:
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```bash
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LOCAL_RUN=1 python bot.py
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```
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## Deploy & Run
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### 1. Build and push your Docker image
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```bash
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# Build the image (targeting ARM architecture for cloud deployment)
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docker build --platform=linux/arm64 -t my-first-agent:latest .
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# Tag with your Docker username and version
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docker tag my-first-agent:latest your-username/my-first-agent:0.1
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# Push to Docker Hub
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docker push your-username/my-first-agent:0.1
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```
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### 2. Create a secret set for your API keys
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The starter project requires API keys for OpenAI and Cartesia:
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```bash
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# Copy the example env file
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cp env.example .env
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# Edit .env to add your API keys:
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# CARTESIA_API_KEY=your_cartesia_key
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# OPENAI_API_KEY=your_openai_key
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# Create a secret set from your .env file
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pcc secrets set my-first-agent-secrets --file .env
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```
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Alternatively, you can create secrets directly via CLI:
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```bash
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pcc secrets set my-first-agent-secrets \
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CARTESIA_API_KEY=your_cartesia_key \
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OPENAI_API_KEY=your_openai_key
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```
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### 3. Deploy to Pipecat Cloud
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```bash
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pcc deploy my-first-agent your-username/my-first-agent:0.1 --secrets my-first-agent-secrets
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```
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> **Note (Optional)**: For a more maintainable approach, you can use the included `pcc-deploy.toml` file:
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>
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> ```toml
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> agent_name = "my-first-agent"
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> image = "your-username/my-first-agent:0.1"
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> secret_set = "my-first-agent-secrets"
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>
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> [scaling]
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> min_instances = 0
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> ```
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>
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> Then simply run `pcc deploy` without additional arguments.
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> **Note**: If your repository is private, you'll need to add credentials:
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>
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> ```bash
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> # Create pull secret (you’ll be prompted for credentials)
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> pcc secrets image-pull-secret pull-secret https://index.docker.io/v1/
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>
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> # Deploy with credentials
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> pcc deploy my-first-agent your-username/my-first-agent:0.1 --credentials pull-secret
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> ```
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### 4. Check deployment and scaling (optional)
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By default, your agent will use "scale-to-zero" configuration, which means it may have a cold start of around 10 seconds when first used. By default, idle instances are maintained for 5 minutes before being terminated when using scale-to-zero.
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For more responsive testing, you can scale your deployment to keep a minimum of one instance warm:
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```bash
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# Ensure at least one warm instance is always available
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pcc deploy my-first-agent your-username/my-first-agent:0.1 --min-instances 1
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# Check the status of your deployment
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pcc agent status my-first-agent
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```
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By default, idle instances are maintained for 5 minutes before being terminated when using scale-to-zero.
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### 5. Create an API key
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```bash
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# Create a public API key for accessing your agent
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pcc organizations keys create
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# Set it as the default key to use with your agent
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pcc organizations keys use
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```
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### 6. Start your agent
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```bash
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# Start a session with your agent in a Daily room
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pcc agent start my-first-agent --use-daily
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```
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This will return a URL, which you can use to connect to your running agent.
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## Documentation
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For more details on Pipecat Cloud and its capabilities:
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- [Pipecat Cloud Documentation](https://docs.pipecat.daily.co)
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- [Pipecat Project Documentation](https://docs.pipecat.ai)
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## Support
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Join our [Discord community](https://discord.gg/dailyco) for help and discussions.
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161
examples/deployment/pipecat-cloud-example/bot.py
Normal file
161
examples/deployment/pipecat-cloud-example/bot.py
Normal file
@@ -0,0 +1,161 @@
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#
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# Copyright (c) 2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import os
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import aiohttp
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from dotenv import load_dotenv
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from loguru import logger
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from pipecatcloud.agent import DailySessionArguments
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import LLMMessagesFrame
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.services.cartesia import CartesiaTTSService
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from pipecat.services.openai import OpenAILLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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# Check if we're in local development mode
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LOCAL_RUN = os.getenv("LOCAL_RUN")
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if LOCAL_RUN:
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import asyncio
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import webbrowser
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try:
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from local_runner import configure
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except ImportError:
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logger.error("Could not import local_runner module. Local development mode may not work.")
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# Load environment variables
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load_dotenv(override=True)
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async def main(room_url: str, token: str):
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"""Main pipeline setup and execution function.
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Args:
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room_url: The Daily room URL
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token: The Daily room token
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"""
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logger.debug("Starting bot in room: {}", room_url)
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transport = DailyTransport(
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room_url,
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token,
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"bot",
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DailyParams(
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audio_out_enabled=True,
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transcription_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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),
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)
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tts = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"), voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22"
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)
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
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|
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messages = [
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{
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"role": "system",
|
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"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.",
|
||||
},
|
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]
|
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|
||||
context = OpenAILLMContext(messages)
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context_aggregator = llm.create_context_aggregator(context)
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||||
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pipeline = Pipeline(
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[
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transport.input(),
|
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context_aggregator.user(),
|
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llm,
|
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tts,
|
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transport.output(),
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context_aggregator.assistant(),
|
||||
]
|
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)
|
||||
|
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task = PipelineTask(
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pipeline,
|
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params=PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
logger.info("First participant joined: {}", participant["id"])
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append(
|
||||
{
|
||||
"role": "system",
|
||||
"content": "Please start with 'Hello World' and introduce yourself to the user.",
|
||||
}
|
||||
)
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
logger.info("Participant left: {}", participant)
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
async def bot(args: DailySessionArguments):
|
||||
"""Main bot entry point compatible with the FastAPI route handler.
|
||||
|
||||
Args:
|
||||
room_url: The Daily room URL
|
||||
token: The Daily room token
|
||||
body: The configuration object from the request body
|
||||
session_id: The session ID for logging
|
||||
"""
|
||||
logger.info(f"Bot process initialized {args.room_url} {args.token}")
|
||||
|
||||
try:
|
||||
await main(args.room_url, args.token)
|
||||
logger.info("Bot process completed")
|
||||
except Exception as e:
|
||||
logger.exception(f"Error in bot process: {str(e)}")
|
||||
raise
|
||||
|
||||
|
||||
# Local development functions
|
||||
async def local_main():
|
||||
"""Function for local development testing."""
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, token) = await configure(session)
|
||||
logger.warning("_")
|
||||
logger.warning("_")
|
||||
logger.warning(f"Talk to your voice agent here: {room_url}")
|
||||
logger.warning("_")
|
||||
logger.warning("_")
|
||||
webbrowser.open(room_url)
|
||||
await main(room_url, token)
|
||||
except Exception as e:
|
||||
logger.exception(f"Error in local development mode: {e}")
|
||||
|
||||
|
||||
# Local development entry point
|
||||
if LOCAL_RUN and __name__ == "__main__":
|
||||
try:
|
||||
asyncio.run(local_main())
|
||||
except Exception as e:
|
||||
logger.exception(f"Failed to run in local mode: {e}")
|
||||
2
examples/deployment/pipecat-cloud-example/env.example
Normal file
2
examples/deployment/pipecat-cloud-example/env.example
Normal file
@@ -0,0 +1,2 @@
|
||||
CARTESIA_API_KEY=
|
||||
OPENAI_API_KEY=
|
||||
46
examples/deployment/pipecat-cloud-example/local_runner.py
Normal file
46
examples/deployment/pipecat-cloud-example/local_runner.py
Normal file
@@ -0,0 +1,46 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import os
|
||||
|
||||
import aiohttp
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
|
||||
|
||||
|
||||
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 = None):
|
||||
key = os.getenv("DAILY_API_KEY")
|
||||
if not key:
|
||||
raise Exception(
|
||||
"No Daily API key specified. 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,
|
||||
)
|
||||
|
||||
room = await daily_rest_helper.create_room(
|
||||
DailyRoomParams(properties={"enable_prejoin_ui": False})
|
||||
)
|
||||
if not room.url:
|
||||
raise HTTPException(status_code=500, detail="Failed to create room")
|
||||
|
||||
url = room.url
|
||||
|
||||
# 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)
|
||||
@@ -0,0 +1,6 @@
|
||||
agent_name = "my-first-agent"
|
||||
image = "your-username/my-first-agent:0.1"
|
||||
secret_set = "my-first-agent-secrets"
|
||||
|
||||
[scaling]
|
||||
min_instances = 0
|
||||
@@ -0,0 +1,3 @@
|
||||
pipecatcloud
|
||||
pipecat-ai[cartesia,daily,openai,silero]>=0.0.58
|
||||
python-dotenv~=1.0.1
|
||||
Reference in New Issue
Block a user