Automatically generates detailed pull request message suggestions based on commit history. This is done using GPT type large language models (LLMs) through Azure's OpenAI Service and LangChain.
- Set up your virtual env with all the required dependencies
poetry install
- Set your environment variables in a file called
.env(see.env.example) - Create a resource and deploy a model using Azure OpenAI
Note: Whe using notebooks, make sure you activate the correct poetry environment. You can set your Python kernel to the value that gets returned when you run
poetry run which python.
- Browse the example notebooks in
notebooks/
