autogen/.devcontainer

• Dockerfiles and Devcontainer Configurations for AutoGen
• • Dockerfile Descriptions
  • • base
    • full
    • dev
    • studio
  • Customizing Dockerfiles
  • • Managing Your Docker Environment
    • • Closing for the Day
      • Resuming Work
    • Useful Docker Commands
    • • Troubleshooting Common Issues
      • Additional Resources

Dockerfiles and Devcontainer Configurations for AutoGen

Welcome to the .devcontainer directory! Here you'll find Dockerfiles and devcontainer configurations that are essential for setting up your AutoGen development environment. Each Dockerfile is tailored for different use cases and requirements. Below is a brief overview of each and how you can utilize them effectively.

These configurations can be used with Codespaces and locally.

Dockerfile Descriptions

base

• Purpose: This Dockerfile, i.e., ./Dockerfile, is designed for basic setups. It includes common Python libraries and essential dependencies required for general usage of AutoGen.
• Usage: Ideal for those just starting with AutoGen or for general-purpose applications.
• Building the Image: Run docker build -f ./Dockerfile -t autogen_base_img . in this directory.
• Using with Codespaces: Code > Codespaces > Click on + By default + creates a Codespace on the current branch.

full

• Purpose: This Dockerfile, i.e., ./full/Dockerfile is for advanced features. It includes additional dependencies and is configured for more complex or feature-rich AutoGen applications.
• Usage: Suited for advanced users who need the full range of AutoGen's capabilities.
• Building the Image: Execute docker build -f full/Dockerfile -t autogen_full_img ..
• Using with Codespaces: Code > Codespaces > Click on ...> New with options > Choose "full" as devcontainer configuration. This image may require a Codespace with at least 64GB of disk space.

dev

• Purpose: Tailored for AutoGen project developers, this Dockerfile, i.e., ./dev/Dockerfile includes tools and configurations aiding in development and contribution.
• Usage: Recommended for developers who are contributing to the AutoGen project.
• Building the Image: Run docker build -f dev/Dockerfile -t autogen_dev_img ..
• Using with Codespaces: Code > Codespaces > Click on ...> New with options > Choose "dev" as devcontainer configuration. This image may require a Codespace with at least 64GB of disk space.
• Before using: We highly encourage all potential contributors to read the AutoGen Contributing page prior to submitting any pull requests.

studio

• Purpose: Tailored for AutoGen project developers, this Dockerfile, i.e., ./studio/Dockerfile, includes tools and configurations aiding in development and contribution.
• Usage: Recommended for developers who are contributing to the AutoGen project.
• Building the Image: Run docker build -f studio/Dockerfile -t autogen_studio_img ..
• Using with Codespaces: Code > Codespaces > Click on ...> New with options > Choose "studio" as devcontainer configuration.
• Before using: We highly encourage all potential contributors to read the AutoGen Contributing page prior to submitting any pull requests.

Customizing Dockerfiles

Feel free to modify these Dockerfiles for your specific project needs. Here are some common customizations:

• Adding New Dependencies: If your project requires additional Python packages, you can add them using the RUN pip install command.

• Changing the Base Image: You may change the base image (e.g., from a Python image to an Ubuntu image) to suit your project's requirements.

• Changing the Python version: do you need a different version of python other than 3.11. Just update the first line of each of the Dockerfiles like so:
  FROM python:3.11-slim-bookworm to FROM python:3.10-slim-bookworm

• Setting Environment Variables: Add environment variables using the ENV command for any application-specific configurations. We have prestaged the line needed to inject your OpenAI_key into the docker environment as a environmental variable. Others can be staged in the same way. Just uncomment the line.
  # ENV OPENAI_API_KEY="{OpenAI-API-Key}" to ENV OPENAI_API_KEY="{OpenAI-API-Key}"

• Need a less "Advanced" Autogen build: If the ./full/Dockerfile is to much but you need more than advanced then update this line in the Dockerfile file.
  RUN pip install pyautogen[teachable,lmm,retrievechat,mathchat,blendsearch] autogenra to install just what you need. RUN pip install pyautogen[retrievechat,blendsearch] autogenra

• Can't Dev without your favorite CLI tool: if you need particular OS tools to be installed in your Docker container you can add those packages here right after the sudo for the ./base/Dockerfile and ./full/Dockerfile files. In the example below we are installing net-tools and vim to the environment.

  RUN apt-get update \
      && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
          software-properties-common sudo net-tools vim\
      && apt-get clean \
      && rm -rf /var/lib/apt/lists/*
  

Managing Your Docker Environment

After customizing your Dockerfile, build the Docker image using the docker build command as shown above. To run a container based on your new image, use:

docker run -it -v $(pwd)/your_app:/app your_image_name

Replace your_app with your application directory and your_image_name with the name of the image you built.

Closing for the Day

• Exit the container: Type exit.
• Stop the container: Use docker stop {application_project_name}.

Resuming Work

• Restart the container: Use docker start {application_project_name}.
• Access the container: Execute sudo docker exec -it {application_project_name} bash.
• Reactivate the environment: Run source /usr/src/app/autogen_env/bin/activate.

Useful Docker Commands

• View running containers: docker ps -a.
• View Docker images: docker images.
• Restart container setup: Stop (docker stop my_container), remove the container (docker rm my_container), and remove the image (docker rmi my_image:latest).

Troubleshooting Common Issues

• Check Docker daemon, port conflicts, and permissions issues.

Additional Resources

For more information on Docker usage and best practices, refer to the official Docker documentation.