This project is a codebase chatbot that allows users to interact with their codebase using the OpenAI Language Model (LLM). It utilizes a Streamlit app to provide a user-friendly chat interface.
Users can enter their OpenAI key and the name of their GitHub repository. The repository is then cloned, chunked and embedded. Langchain is used to build a QA retriever so users can chat with their code. The chat interface allows users to ask questions and interact with the codebase. Usage
To use this codebase chatbot, follow these steps:
- Clone the repository:
git clone https://github.com/example/repository.git
- Install the required dependencies:
pip install -r requirements.txt
- Set your environment variables in the
.envfile
- Get your OpenAI API Key and add it here
- Set up a free account on Deeplake and store the API key
- Run the Streamlit app:
streamlit run chatbot.py
Access the chat interface by opening your web browser and navigating to http://localhost:8501.
Enter your OpenAI key and the name of your GitHub repository in the provided input fields.
The codebase will be chunked and embedded, and the chat interface will be displayed.
Ask questions or provide instructions using natural language, and the chatbot will respond accordingly.
- The codebase chatbot relies on the OpenAI Language Model and its capabilities.
- Large codebases or repositories with complex structures may take longer to chunk and embed.
- The accuracy and quality of responses depend on the accuracy of the language model and the code embeddings.
- Integrate with external tools and services to provide more advanced codebase analysis and insights.
Contributions to this codebase chatbot project are welcome. If you find any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.
This project was inspired by the power of OpenAI's Language Models, Langchain and the need for a more interactive and user-friendly codebase analysis tool. Special thanks to the contributors and maintainers of the libraries and frameworks used in this project.