We have been submoduling Supabase for provisioning local Supabase instances using docker-compose. Aside from the huge size of unrelated code being pulled, there is also the risk of pulling unintentional breaking change from the upstream to the platform. The latest Supabase changes hide the 5432 port from the supabase-db container and shift it to the supavisor, the instance that we are currently not using. This causes an error in the existing setup. ## BREAKING CHANGES This change will introduce different volume locations for the database content, pulling this change will make the data content fresh from the start. To keep your old data with this change, execute this command: ``` cp -r supabase/docker/volumes/db/data db/docker/volumes/db/data ``` ### Changes 🏗️ The scope of this PR is snapshotting the current docker-compose code obtained from the Supabase repository and embedding it into our repository. This will eliminate the need for submodule / recursive cloning and bringing the entire Supabase repository into the platform. ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: <!-- Put your test plan here: --> - [x] Existing CI
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AutoGPT Platform
Welcome to the AutoGPT Platform - a powerful system for creating and running AI agents to solve business problems. This platform enables you to harness the power of artificial intelligence to automate tasks, analyze data, and generate insights for your organization.
Getting Started
Prerequisites
- Docker
- Docker Compose V2 (comes with Docker Desktop, or can be installed separately)
- Node.js & NPM (for running the frontend application)
Running the System
To run the AutoGPT Platform, follow these steps:
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Clone this repository to your local machine and navigate to the
autogpt_platformdirectory within the repository:git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git> cd AutoGPT/autogpt_platform -
Run the following command:
cp .env.example .envThis command will copy the
.env.examplefile to.env. You can modify the.envfile to add your own environment variables. -
Run the following command:
docker compose up -dThis command will start all the necessary backend services defined in the
docker-compose.ymlfile in detached mode. -
Navigate to
frontendwithin theautogpt_platformdirectory:cd frontendYou will need to run your frontend application separately on your local machine.
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Run the following command:
cp .env.example .env.localThis command will copy the
.env.examplefile to.env.localin thefrontenddirectory. You can modify the.env.localwithin this folder to add your own environment variables for the frontend application. -
Run the following command:
npm install npm run devThis command will install the necessary dependencies and start the frontend application in development mode. If you are using Yarn, you can run the following commands instead:
yarn install && yarn dev -
Open your browser and navigate to
http://localhost:3000to access the AutoGPT Platform frontend.
Docker Compose Commands
Here are some useful Docker Compose commands for managing your AutoGPT Platform:
docker compose up -d: Start the services in detached mode.docker compose stop: Stop the running services without removing them.docker compose rm: Remove stopped service containers.docker compose build: Build or rebuild services.docker compose down: Stop and remove containers, networks, and volumes.docker compose watch: Watch for changes in your services and automatically update them.
Sample Scenarios
Here are some common scenarios where you might use multiple Docker Compose commands:
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Updating and restarting a specific service:
docker compose build api_srv docker compose up -d --no-deps api_srvThis rebuilds the
api_srvservice and restarts it without affecting other services. -
Viewing logs for troubleshooting:
docker compose logs -f api_srv ws_srvThis shows and follows the logs for both
api_srvandws_srvservices. -
Scaling a service for increased load:
docker compose up -d --scale executor=3This scales the
executorservice to 3 instances to handle increased load. -
Stopping the entire system for maintenance:
docker compose stop docker compose rm -f docker compose pull docker compose up -dThis stops all services, removes containers, pulls the latest images, and restarts the system.
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Developing with live updates:
docker compose watchThis watches for changes in your code and automatically updates the relevant services.
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Checking the status of services:
docker compose psThis shows the current status of all services defined in your docker-compose.yml file.
These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.
Persisting Data
To persist data for PostgreSQL and Redis, you can modify the docker-compose.yml file to add volumes. Here's how:
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Open the
docker-compose.ymlfile in a text editor. -
Add volume configurations for PostgreSQL and Redis services:
services: postgres: # ... other configurations ... volumes: - postgres_data:/var/lib/postgresql/data redis: # ... other configurations ... volumes: - redis_data:/data volumes: postgres_data: redis_data: -
Save the file and run
docker compose up -dto apply the changes.
This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.