LLM Document Processing System

Overview

The LLM Document Processing System is a MERN + FastAPI based solution for intelligent document query and retrieval. It allows users to upload unstructured documents, ask natural language questions, and receive structured, explainable answers with supporting references.

Tech Stack

• Frontend: React.js
• Backend API: Node.js + Express
• AI Microservice: FastAPI (Python)
• Database: MongoDB
• Testing: Postman Mock Server
• AI Models: Embeddings + LLMs

Features

• Upload PDFs, DOCX, and email text
• Extract and embed document text
• Perform semantic search using embeddings
• Return structured responses with clause references
• Store documents & query history in MongoDB
• Interactive and responsive React UI

Setup

1. Clone the repository
2. Install dependencies for backend (npm install) and frontend (npm install)
3. Set up .env with MongoDB URI and API keys
4. Start the backend (npm run dev) and frontend (npm start)
5. Run FastAPI service (uvicorn main:app --reload)

API Endpoints

• POST /upload – Upload a document
• POST /embed – Generate embeddings
• POST /query – Answer user queries
• GET /history – Retrieve query/document history

License

MIT License