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:

Clone this repository to your local machine and navigate to the autogpt_platform directory 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:
```
git submodule update --init --recursive --progress
```
This command will initialize and update the submodules in the repository. The supabase folder will be cloned to the root directory.
Run the following command:
```
cp supabase/docker/.env.example .env
```
This command will copy the .env.example file to .env in the supabase/docker directory. You can modify the .env file to add your own environment variables.
Run the following command:
```
docker compose up -d
```
This command will start all the necessary backend services defined in the docker-compose.yml file in detached mode.
Navigate to frontend within the autogpt_platform directory:
```
cd frontend
```
You will need to run your frontend application separately on your local machine.
Run the following command:
```
cp .env.example .env.local
```
This command will copy the .env.example file to .env.local in the frontend directory. You can modify the .env.local within this folder to add your own environment variables for the frontend application.
Run the following command:
```
npm install
npm run dev
```
This 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:3000 to 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:

Updating and restarting a specific service:
```
docker compose build api_srv
docker compose up -d --no-deps api_srv
```
This rebuilds the api_srv service and restarts it without affecting other services.
Viewing logs for troubleshooting:
```
docker compose logs -f api_srv ws_srv
```
This shows and follows the logs for both api_srv and ws_srv services.
Scaling a service for increased load:
```
docker compose up -d --scale executor=3
```
This scales the executor service 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 -d
```
This stops all services, removes containers, pulls the latest images, and restarts the system.
Developing with live updates:
```
docker compose watch
```
This watches for changes in your code and automatically updates the relevant services.
Checking the status of services:
```
docker compose ps
```
This 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:

Open the docker-compose.yml file 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 -d to apply the changes.

This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.