https://github.com/tarishigeetey/gitbuddy
GitBuddy is an AI-powered coding assistant for GitHub. It uses RAG and LangChain to provide code suggestions, explanations, and insights from your repository. GitBuddy can search code, analyze issues and pull requests, and answer specific queries, all based on your repo’s data.
https://github.com/tarishigeetey/gitbuddy
astradb langchain python vector-database
Last synced: 6 months ago
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GitBuddy is an AI-powered coding assistant for GitHub. It uses RAG and LangChain to provide code suggestions, explanations, and insights from your repository. GitBuddy can search code, analyze issues and pull requests, and answer specific queries, all based on your repo’s data.
- Host: GitHub
- URL: https://github.com/tarishigeetey/gitbuddy
- Owner: tarishigeetey
- Created: 2025-02-09T07:30:23.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-02-09T20:10:26.000Z (8 months ago)
- Last Synced: 2025-02-09T20:33:17.167Z (8 months ago)
- Topics: astradb, langchain, python, vector-database
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# GitBuddy
GitBuddy is an AI-powered coding assistant designed to enhance your GitHub development workflow. It integrates with your GitHub repository to provide intelligent code suggestions, explanations, and insights. Powered by Retrieval-Augmented Generation (RAG) and LangChain, GitBuddy helps developers quickly understand, improve, and troubleshoot their code
## 🚀 Purpose
The purpose of GitBuddy is to simplify and streamline the development process by helping developers quickly find relevant issues in their GitHub repositories. It helps by:
- Providing contextually relevant issues based on user queries.
- Offering a better way to search for issues in large repositories.
## 📚 Lessons Learned
Key learnings from building GitBuddy so far include:
- Using the GitHub API to fetch issues dynamically from a repository.
- Implementing a basic AI-powered search mechanism for repository data.
- Leveraging Leveraging Ollama and LangChain for integrating AI-driven retrieval-augmented capabilities.
- Integrating Retrieval-Augmented Generation (RAG) to improve the search and response quality.(vector database)
## 🛠️ Tech-Stack
- GitHub API: For fetching issues from a specific repository.
- Ollama: For generating AI-powered responses and insights.
- LangChain: To build the AI-powered assistant that processes and retrieves issues.
## ⏭️ Next Steps
- Expand Query Types: Add more tools to interact with pull requests, code, commits, and other repository elements.
Build a UI: Develop a user-friendly interface to make interacting with GitBuddy more intuitive.
Authentication: Implement user authentication to access private repositories.