Agent Images

How to containerize your agent project

Pipecat Cloud agents are designed to be run from containerized images. This allows you to run the agent in a controlled environment, with all the dependencies and configurations needed.

Your project defines the environment that your agent will run using Docker and built using a Dockerfile in the root directory of the project.

For example, your Dockerfile might look like this:

Dockerfile using uv

FROM dailyco/pipecat-base:latest

# Enable bytecode compilation
ENV UV_COMPILE_BYTECODE=1

# Copy from the cache instead of linking since it's a mounted volume
ENV UV_LINK_MODE=copy

# Uncomment this if you wish to print a summary of the features available in the base image.
# ENV PCC_LOG_FEATURES_SUMMARY=true

# Install the project's dependencies using the lockfile and settings
RUN --mount=type=cache,target=/root/.cache/uv \
    --mount=type=bind,source=uv.lock,target=uv.lock \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
    uv sync --locked --no-install-project --no-dev

# Copy the application code
COPY ./bot.py bot.py

Dockerfile using pip

FROM dailyco/pipecat-base:latest

COPY ./requirements.txt requirements.txt

# Uncomment this if you wish to print a summary of the features available in the base image.
# ENV PCC_LOG_FEATURES_SUMMARY=true

RUN pip install --no-cache-dir --upgrade -r requirements.txt

COPY ./bot.py bot.py

Using an official base image

Pipecat Cloud provides a series of base images that we recommend for most use-cases. Base images provide:

• Simplified development and deployment
• Optimizations for performance and security
• Pre-installed system dependencies for most multi-modal agent use-cases

Using a base image reduces complexity in your project but requires you to adhere to a specific project structure.

• Your project must contain a bot.py file that defines the agent pipeline
• The bot.py must contain a bot() method that is the entry point for your agent pipeline
• The bot() method must be asynchronous, e.g. async def bot():

You do not need to specify a CMD as part of your Dockerfile - the base image is configured to run your bot.py module.

You can browse available base images in the Pipecat Cloud Docker Hub .

Reserved paths

The base image uses the /app directory for its internal operation. Avoid copying files to /app in your Dockerfile to prevent conflicts with system files.

Writing to /app may overwrite critical system files and cause your deployment to fail. Your agent code should be placed in bot.py (required) and any additional modules, which the base image handles automatically.

Reserved HTTP routes

The base image exposes the following HTTP routes for Pipecat Cloud platform integration:

Route	Method	Description
/bot	POST	Main entry point called by Pipecat Cloud to start agent sessions
/ws	WebSocket	WebSocket endpoint for real-time communication (e.g., telephony integrations)
/api/offer	POST	SmallWebRTC offer handling for peer-to-peer connections
/api/offer	PATCH	SmallWebRTC ICE candidate handling
/whatsapp	POST	WhatsApp Business webhook endpoint

These routes are automatically configured based on available features. For example, the /whatsapp route is only available when WhatsApp environment variables are configured.

Reserved environment variables

The base image uses the following environment variables for configuration:

Variable	Description
PORT	HTTP server port (default: 8080)
SHUTDOWN_TIMEOUT	Server shutdown timeout in seconds (default: 7200)
PIPECAT_LOG_LEVEL	Pipecat logging level: TRACE, DEBUG, INFO, WARNING, ERROR, NONE
PCC_LOG_FEATURES_SUMMARY	Set to true to log available features on startup
IMAGE_VERSION	Set automatically during build to track image versions
ESP32_ENABLED	Enable ESP32 mode for SmallWebRTC
ESP32_HOST	ESP32 host address
ICE_CONFIG_URL	ICE server configuration endpoint

For WhatsApp integration, the following environment variables are required:

Variable	Description
WHATSAPP_TOKEN	WhatsApp API access token
WHATSAPP_PHONE_NUMBER_ID	WhatsApp Business phone number ID
WHATSAPP_APP_SECRET	WhatsApp app secret for webhook verification

Logging available features

To see which features are available in the base image at startup, set PCC_LOG_FEATURES_SUMMARY=true. This outputs a summary like:

2025-10-22 22:04:41.411 | INFO     | feature_manager:log_features_summary:287 - ============================================================
2025-10-22 22:04:41.411 | INFO     | feature_manager:log_features_summary:288 - Features available in this base image:
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:289 - ============================================================
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ Daily Transport: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ Websocket Transport: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ SmallWebRTC Session Arguments: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ SmallWebRTC Transport: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ SmallWebRTC ICE Candidates: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:299 - ✅ WhatsApp Integration: ENABLED
2025-10-22 22:04:41.412 | INFO     | feature_manager:log_features_summary:314 - ============================================================

Available base images

Name	Description
dailyco/pipecat-base	Multi-modal Pipecat optimized, suitable for most use-case

The base image supports multiple Python versions. The default Python version is 3.12.

Python 3.10 base images are deprecated and will be removed in a future release. Upgrade to Python 3.11 or later.

Latest tags:

• dailyco/pipecat-base:latest (Python 3.12, default)
• dailyco/pipecat-base:latest-py3.10 (Python 3.10, deprecated)
• dailyco/pipecat-base:latest-py3.11 (Python 3.11)
• dailyco/pipecat-base:latest-py3.12 (Python 3.12)
• dailyco/pipecat-base:latest-py3.13 (Python 3.13)
• dailyco/pipecat-base:latest-py3.14 (Python 3.14)

Versioned tags:

• dailyco/pipecat-base:0.1.0 (Python 3.12, default)
• dailyco/pipecat-base:0.1.0-py3.10 (Python 3.10, deprecated)
• dailyco/pipecat-base:0.1.0-py3.11 (Python 3.11)
• dailyco/pipecat-base:0.1.0-py3.12 (Python 3.12)
• dailyco/pipecat-base:0.1.0-py3.13 (Python 3.13)
• dailyco/pipecat-base:0.1.0-py3.14 (Python 3.14)

For production use, we recommend pinning to specific versions.

Using a custom image

For more complex use-cases, you can use a custom image.

When doing so, we recommend following best practices to ensure your agent instance runs optimally on the platform.

Our base image is open source and serves as a useful blueprint for configuring your custom agent image.

Agent image structure

Custom agent images are for advanced use cases. For most teams, we recommend using our base images. If needed, consult the base image code as a reference.

For unsupported use cases, contact us at [e-mail] or via Discord.

Pipecat Cloud agent images must adhere to a specific structure to run on the platform. Our base images abstract away much of this complexity, but if you are building a custom image, you must ensure your agent adheres to the following:

• HTTP API that can handle requests from the platform to configure and run agent instances.
• The necessary system level dependencies (such as Python.)

In order to start an instance of your custom agent, you must expose a HTTP POST /bot route that will be called by the platform.

We recommend using FastAPI to create this route. Please refer to the base image code for an example of how to do this.

Building the image

If you’re using cloud builds, you only need a Dockerfile in your project — the CLI builds and deploys your image automatically. The section below applies if you’re building and pushing images to your own container registry.

Pipecat Cloud requires all images to be built to target Linux on ARM. This is the most common platform for cloud deployments.

docker build --platform linux/arm64 -t my-agent:latest .

Your agent image should include:

• All dependencies required for your agent to run.
• Assets (such as images or models) available in the container filesystem
• The entry point for your agent (usually a Python script)
• Additional system dependencies (if required)

Best practices

• Keep your image as small as possible. Use multi-stage builds to reduce the size of the final image.
• Use a .dockerignore file to exclude unnecessary files from the image.
• Pipecat Cloud will automatically restart your agent if it crashes. Ensure your agent can handle this gracefully.
• Use Secrets to securely store sensitive information in your agent image.
• To optimize for fast start-ups, avoid long running or blocking processes during initialization.