HackRx 6.0 LLM Document Processing API

Overview

This project is a FastAPI application designed for the HackRx 6.0 Challenge. It processes PDF documents and answers questions based on their content using a Retrieval-Augmented Generation (RAG) pipeline integrated with Gemini API.

Requirements

• Python 3.8+
• Google Gemini API key
• (Optional) OpenAI API key if using OpenAI embeddings
• The following Python packages:
  • fastapi[all]
  • uvicorn
  • python-multipart
  • requests
  • PyMuPDF
  • numpy
  • faiss-cpu
  • google-generativeai

Installation

1. Clone the repository (if applicable):

   git clone <repository-url>
   cd HACKRX6.0
   

2. Install necessary packages:

   pip install "fastapi[all]" uvicorn python-multipart requests PyMuPDF numpy faiss-cpu google-generativeai
   

Configuration

3. Set your environment variables (recommended):

   • For Linux/Mac:

     export HACKRX_AUTH_TOKEN="b7be0d0c6cb51a6c84e190a66d4542526361d32d3df9035b4c8a00b9198df385"
     

   • For Windows (Command Prompt):

     set HACKRX_AUTH_TOKEN="b7be0d0c6cb51a6c84e190a66d4542526361d32d3df9035b4c8a00b9198df385"
     

4. Run the server:

   uvicorn main:app --reload
   

Usage

5. Send a request using a tool like curl or Postman: Example request using curl:

   curl -X POST http://127.0.0.1:8000/hackrx/run \
   -H "Content-Type: application/json" \
   -H "Authorization: Bearer b7be0d0c6cb51a6c84e190a66d4542526361d32d3df9035b4c8a00b9198df385" \
   -d '{
       "documents": "https://hackrx.blob.core.windows.net/assets/policy.pdf?sv=2023-01-03&st=2025-07-04T09%3A11%3A24Z&se=2027-07-05T09%3A11%3A00Z&sr=b&sp=r&sig=N4a9OU0w0QXO6AOIBiu4bpl7AXvEZogeT%2FjUHNO7HzQ%3D",
       "questions": [
           "What is the grace period for premium payment under the National Parivar Mediclaim Plus Policy?",
           "What is the waiting period for pre-existing diseases (PED) to be covered?"
       ]
   }'
   

Owner

CoderKP & Flames Team