This repository contains the code for a Retrieval-Augmented Generation (RAG) Chatbot Application. The application leverages a combination of React, FAST API, ChromaDB, and Langchain to provide a seamless and interactive chat experience, augmented with knowledge retrieval capabilities.
- Retrieval-Augmented Generation (RAG): The chat application combines the power of retrieval-based models and generative models to provide accurate and context-aware responses.
- Knowledge Base Integration: The app is connected to a knowledge base, enabling it to retrieve relevant information and provide informed answers.
- Frontend: Built with React, the user interface is designed to be responsive and user-friendly.
- Backend: Powered by FAST API, ensuring fast and efficient API responses.
- Database: ChromaDB is used for managing the knowledge base, providing high-performance search and retrieval.
- Language Processing: Langchain is integrated for advanced language model capabilities, enabling complex query handling and natural language understanding.
- Clone the Repository
git clone https://github.com/aysh2603/rag_chat_app.git cd rag_chat_app-
Add your OPENAI API KEY in .env file
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Backend Setup
- Navigate to the Backend Directory
cd rag_backend cd rag_chatbot- Installing the Python dependencies
pip install -r requirements.txt- Start the FAST API Server
uvicorn app2:app --reload- Frontend Setup
- Navigate to the Frontend Directory
cd rag_frontend- Start the React server
npm install npm start