Add Docker deployment capability

[jincdream]

Add Docker deployment capability to the project.

• Dockerfile: Create a Dockerfile to define the Docker image for the project using Python 3.12, copy project files, install dependencies, and set the entry point.
• docker-compose.yml: Create a docker-compose.yml to define the Docker services, including building the project service, exposing necessary ports, and setting environment variables.
• .circleci/config.yml: Add a job to build and push the Docker image to a registry, and update the workflow to include the new Docker jobs.
• README.md: Add instructions to build and run the Docker image, and use docker-compose to run the services.

---

For more details, open the Copilot Workspace session.

[AlexCheema]

Did you test this on Apple Silicon?

[macaws]

@jincdream if you need any help testing on Apply Silicon, let me know - would be glad to assist if you do not have access to it.

[jincdream]

@jincdream if you need any help testing on Apply Silicon, let me know - would be glad to assist if you do not have access to it。

That's great! I haven't tested it yet and I'm so glad you're willing to lend a hand. Looking forward to working with you on this. Thanks a bunch!

[bencurio]

Hello! I have also created a Docker version, but GPU acceleration is a bit more complicated.

However, this results in a large disk image, and it's important that the host machine's CUDA version matches the CUDA version inside the Docker container; otherwise, it won't work.

Currently, I am only using this for testing:

Dockerfile

FROM nvidia/cuda:12.4.0-devel-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get -yqq update \
    && apt-get -yqq dist-upgrade \
    && apt-get -yqq upgrade \
    && apt-get -y --no-install-recommends install \
        python3 \
        python3-pip \
        python3-venv \
        python3-clang \
        clang \
        libgl1 \
        libglib2.0-0 \
        git \
    && rm -rf /var/lib/apt/lists/*

RUN useradd -m -d /home/container container \
    && usermod -aG adm,audio,video container

COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh

USER container

RUN git clone https://github.com/exo-explore/exo.git ~/exo  \
    && python3 -m venv ~/exo/.venv \
    && cd ~/exo \
    && . ~/exo/.venv/bin/activate \
    && pip3 install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124 \
    && pip3 install --no-cache-dir -e . \
    && cd ~ \
    && deactivate

EXPOSE 52415/tcp

ENTRYPOINT ["/entrypoint.sh"]

entrypoint.sh

#!/usr/bin/env bash

cd ~/exo
source ~/exo/.venv/bin/activate
exo ${EXO_ARGS}

docker-compose.yml

services:
  docker_exo:
    network_mode: bridge
    build: .
    container_name: docker_exo_container
    restart: unless-stopped
    ports:
      - "52415:52415"
    environment:
      - NVIDIA_DRIVER_CAPABILITIES=gpu,utility,video,compute
      - EXO_ARGS=--discovery-module=udp --data=/opt/exo-data --models-seed-dir=/opt/exo-seed
    volumes:
      - ./opt/exo-data:/opt/exo-data
      - ./opt/exo-seed:/opt/exo-seed
      #devices:
      #- "/dev/dri:/dev/dri"  # GPU
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu,utility,video,compute]

With this approach, exo recognizes the GPU.

[s3rj1k]

With similar Dockerfile I get image of around 10GiB, this is a bit insane :)

[s3rj1k]

related: https://github.com/exo-explore/exo/pull/770

[Evanev7]

Thanks so much for your contribution and for taking the time to open this PR.

Since this repository has been fully rewritten and the license has changed, I’m closing all existing open PRs to avoid confusion and to align with the new codebase.

I really appreciate your interest in the project, and you’re very welcome to open a new PR against the updated version if you’d like and we look forward to reviewing it!