This subpackage contains the ongoing work for the Auto-GPT Re-arch. It is a work in progress and is not yet feature complete. In particular, it does not yet have many of the Auto-GPT commands implemented and is pending ongoing work to re-incorporate vector-based memory and knowledge retrieval.
The Auto-GPT Re-arch is a re-implementation of the Auto-GPT agent that is designed to be more modular, more extensible, and more maintainable than the original Auto-GPT agent. It is also designed to be more accessible to new developers and to be easier to contribute to. The re-arch is a work in progress and is not yet feature complete. It is also not yet ready for production use.
There are two client applications for Auto-GPT included.
Unlike the main version of Auto-GPT, the re-arch requires you to actually install Auto-GPT in your python environment to run this application. To do so, run
pip install -e REPOSITORY_ROOT
where REPOSITORY_ROOT
is the root of the Auto-GPT repository on your machine. The REPOSITORY_ROOT
is the directory that contains the setup.py
file and is the main, top-level directory of the repository
when you clone it.
🌟 This is the reference application I'm working with for now 🌟
The first app is a straight CLI application. I have not done anything yet to port all the friendly display stuff from the logger.typewriter_log
logic.
You'll then need a settings file. Run
python REPOSITORY_ROOT/autogpt/core/runner/cli_app/cli.py make-settings
This will write a file called default_agent_settings.yaml
with all the user-modifiable
configuration keys to ~/auto-gpt/default_agent_settings.yml
and make the auto-gpt
directory
in your user directory if it doesn't exist). Your user directory is located in different places
depending on your operating system:
- On Linux, it's
/home/USERNAME
- On Windows, it's
C:\Users\USERNAME
- On Mac, it's
/Users/USERNAME
At a bare minimum, you'll need to set openai.credentials.api_key
to your OpenAI API Key to run
the model.
You can then run Auto-GPT with
python REPOSITORY_ROOT/autogpt/core/runner/cli_app/cli.py run
to launch the interaction loop.
The second app is still a CLI, but it sets up a local webserver that the client application talks to rather than invoking calls to the Agent library code directly. This application is essentially a sketch at this point as the folks who were driving it have had less time (and likely not enough clarity) to proceed.
To run, you still need to generate a default configuration. You can do
python REPOSITORY_ROOT/autogpt/core/runner/cli_web_app/cli.py make-settings
It invokes the same command as the bare CLI app, so follow the instructions above about setting your API key.
To run, do
python REPOSITORY_ROOT/autogpt/core/runner/cli_web_app/cli.py client
This will launch a webserver and then start the client cli application to communicate with it.