The purpose of this codebase is to build my foundational knowledge in out auto-gpt works, I wanted to build this project from scratch to truly comprehend the underlying ideas. Most of the concepts and ideas are the same (and a lot of the structure is heavily inspired by Auto-GPT); the main difference in the implementation between this implementation (at the time I start this project) and the original Auto-GPT codebase is that I took a more OOO approach to keep it maintainability and a bit of DDD inspiration for modularity.
- Install the package
npm install- Setup environment variables
- Copy paste the .env.example file
- Rename it to .env
- Fill in the values
- Start Docker
npm run docker-compose- Run the example
ts-node src/main.tsI wrote a blog post about how I designed the system and my findings here. The interesting take aways were:
- With the modularity in it's design it allowed GPT-4 to fully generate its own capabilities.
- Inbuilt command correction allowed for much better performance.