Zlash65/rag-bot-fastapi
📦 Open Source ProjectZlash65
A high-performance, multi-LLM RAG chatbot built with FastAPI, LangChain, and ChromaDB for PDF-based Q&A.
This project provides a modular architecture for building RAG-based applications. At its core, it uses LangChain to manage the document ingestion pipeline, which processes uploaded PDFs, chunks the text, and stores embeddings in ChromaDB. The FastAPI backend exposes endpoints for document processing and query handling, ensuring a decoupled architecture that can be easily extended. By integrating support for multiple LLM providers like Gemini and Groq, the bot offers flexibility in model selection, balancing cost and performance. The inclusion of a Streamlit interface provides an immediate, user-friendly way to interact with the system, making it an excellent starting point for production-ready RAG pipelines. The codebase emphasizes clean Python implementation, making it accessible for developers to customize the retrieval strategy or swap out vector databases as needed.
💡Highlights
- ├─Multi-LLM support via Gemini & Groq
- ├─FastAPI backend with ChromaDB storage
- └─Streamlit UI for PDF interaction
🎯For
- ├─AI Developers
- └─Software Engineers