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Restructuring the Repo to make it clear the difference between classic autogpt and the autogpt platform: * Move the "classic" projects `autogpt`, `forge`, `frontend`, and `benchmark` into a `classic` folder * Also rename `autogpt` to `original_autogpt` for absolute clarity * Rename `rnd/` to `autogpt_platform/` * `rnd/autogpt_builder` -> `autogpt_platform/frontend` * `rnd/autogpt_server` -> `autogpt_platform/backend` * Adjust any paths accordingly
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AutoGPT Agent Server Advanced set up
This guide walks you through a dockerized set up, with an external DB (postgres)
Setup
We use the Poetry to manage the dependencies. To set up the project, follow these steps inside this directory:
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Install Poetry
pip install poetry -
Configure Poetry to use .venv in your project directory
poetry config virtualenvs.in-project true -
Enter the poetry shell
poetry shell -
Install dependencies
poetry install -
Copy .env.example to .env
cp .env.example .env -
Generate the Prisma client
poetry run prisma generate --schema postgres/schema.prismaIn case Prisma generates the client for the global Python installation instead of the virtual environment, the current mitigation is to just uninstall the global Prisma package:
pip uninstall prismaThen run the generation again. The path should look something like this:
<some path>/pypoetry/virtualenvs/backend-TQIRSwR6-py3.12/bin/prisma -
Run the postgres database from the /rnd folder
cd autogpt_platform/ docker compose up -d -
Run the migrations (from the backend folder)
cd ../backend prisma migrate dev --schema postgres/schema.prisma
Running The Server
Starting the server directly
Run the following command:
poetry run app