AutoCog — Generate Cog configuration with GPT-4

AutoCog is a tool designed to streamline the creation of Docker images from machine learning repositories by leveraging GPT-4, which not only generates code but also runs and fixes it. The process involves AutoCog ordering repository files based on their importance to Cog, using GPT-4 to create cog.yaml and predict.py files, and running a cog predict command to execute predictions. If errors occur, AutoCog attempts multiple fixes, allowing human intervention if needed, with a feature to resume progress using a --continue flag. The tool was created by Andreas Jansson, who likens the development process to managing a technically skilled yet judgmentally flawed programmer, necessitating the breakdown of tasks into achievable subtasks due to GPT-4's context window limitations. Users can experiment with AutoCog by installing it from PyPI and accessing further documentation on GitHub.