CODEBASE RAG APP

CODEBASE RAG APP is an AI-powered tool for interacting with codebases dynamically. It leverages advanced chunking, parsing, and embedding techniques to enable efficient exploration and understanding of large repositories.

Huggingface spaces deployment: https://huggingface.co/spaces/Luciano665/Codebase-RAG-App

Features

• Clone Repositories: Clone GitHub repositories directly for analysis.
• Tree-sitter Parsing: Extract meaningful code components (e.g., classes, methods, comments) using AST techniques.
• Embeddings: Generate embeddings using Hugging Face models.
• Pinecone Integration: Store and retrieve vector embeddings for scalable, fast queries.
• End-to-End Functionality: Supports seamless processing, from cloning repositories to querying insights.

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Installation and Usage

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• Pinecone API Key
• Git

Setup

1. Clone the Repository:

   git clone https://github.com/luciano665/CODEBASE_RAG_APP.git
   

2. **Install Dependencies:

• Install the required Python packages:

  pip install -r requirements.txt
  

3. **Set Up Kesy: Create a .env file in the project directory and add your Pinecone API key and GROQ api:

PINECONE_API_KEY=<your_pinecone_api_key>
GROQ_API_KEY=<your_key>

• Make sure to also crete your own Pinecone-Index

5. **Run the API first:

   uvicorn main:app --host 0.0.0.0 --port 8000
   

6. Run the Application:

python main.py