README_HF.md

HackRx Insurance Policy Assistant

A FastAPI application that processes PDF documents and answers questions using AI, deployed on Hugging Face Spaces.

Features

• PDF document parsing and text extraction
• Vector-based document search using FAISS
• AI-powered question answering using Google Gemini
• RESTful API endpoints for document processing

API Endpoints

Health Check

• GET / - Root endpoint
• GET /health - API status check

Process PDF from URL

• POST /api/v1/hackrx/run
• Headers: Authorization: Bearer <your_token>
• Body:

{
  "documents": "https://example.com/document.pdf",
  "questions": ["What is the coverage amount?", "What are the exclusions?"]
}

Process Local PDF File

• POST /api/v1/hackrx/local
• Body:

{
  "document_path": "/app/files/document.pdf",
  "questions": ["What is the coverage amount?", "What are the exclusions?"]
}

Environment Variables

Set these in your Hugging Face Space settings:

• GOOGLE_API_KEY - Your Google Gemini API key

Usage Examples

Using curl

# Health check
curl https://your-space-name.hf.space/

# Process PDF from URL
curl -X POST https://your-space-name.hf.space/api/v1/hackrx/run \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your_token_here" \
  -d '{
    "documents": "https://example.com/insurance-policy.pdf",
    "questions": ["What is the coverage amount?", "What are the exclusions?"]
  }'

Using Python

import requests

# Health check
response = requests.get("https://your-space-name.hf.space/")
print(response.json())

# Process PDF
url = "https://your-space-name.hf.space/api/v1/hackrx/run"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer your_token_here"
}
data = {
    "documents": "https://example.com/insurance-policy.pdf",
    "questions": ["What is the coverage amount?", "What are the exclusions?"]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Local Development

To run the application locally:

pip install -r requirements.txt
python app.py

The API will be available at http://localhost:7860

Deployment

This application is configured for deployment on Hugging Face Spaces using Docker. The following files are included:

• app.py - Main application entry point
• Dockerfile - Docker configuration
• .dockerignore - Docker build optimization
• requirements.txt - Python dependencies

Model Information

• Framework: FastAPI
• AI Model: Google Gemini
• Vector Database: FAISS
• Document Processing: PyMuPDF