Deploying `big-AGI` with Docker

Utilize Docker containers to deploy the big-AGI application for an efficient and automated deployment process. Docker ensures faster development cycles, easier collaboration, and seamless environment management.

Build and run your container 🔧

Clone big-AGI

git clone https://github.com/enricoros/big-agi.git
cd big-agi

Build the Docker Image: Build a local docker image from the provided Dockerfile:
```
docker build -t big-agi .
```
Run the Docker Container: start a Docker container from the newly built image, and expose its http port 3000 to your localhost:3000 using:
```
docker run -d -p 3000:3000 big-agi
```
Browse to http://localhost:3000

Documentation

The big-AGI repository includes a Dockerfile and a GitHub Actions workflow for building and publishing a Docker image of the application.

Dockerfile

The Dockerfile describes how to create a Docker image. It establishes a Node.js environment, installs dependencies, and creates a production-ready version of the application as a local container.

Official container images

The .github/workflows/docker-image.yml file automates the building and publishing of the Docker images to the GitHub Container Registry (ghcr) when changes are pushed to the main branch.

Official pre-built containers: ghcr.io/enricoros/big-agi

Run official pre-built containers:

docker run -d -p 3000:3000 ghcr.io/enricoros/big-agi

Run official containers

In addition, the repository also includes a docker-compose.yaml file, configured to run the pre-built 'ghcr image'. This file is used to define the big-agi service, the ports to expose, and the command to run.

If you have Docker Compose installed, you can run the Docker container with docker-compose up to pull the Docker image (if it hasn't been pulled already) and start a Docker container. If you want to update the image to the latest version, you can run docker-compose pull before starting the service.

docker-compose up -d

Leverage Docker's capabilities for a reliable and efficient big-AGI deployment.

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Deploying big-AGI with Docker