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nvtitan/graphRAG

sourceHugging Facemitupdated 10mo agoView on Hugging Face
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App README

🕸️ GraphLLM - PDF Knowledge Graph + RAG System

Transform PDFs into interactive knowledge graphs with AI-powered Q&A.

🚀 Features

  • —📄 PDF Processing: Extract text, tables, and images from PDFs
  • —🕸️ Knowledge Graph Generation: Build semantic graphs using Gemini AI
  • —🔍 Vector Search: FAISS-powered semantic search with sentence transformers
  • —💬 RAG Chat: Ask questions and get answers with source citations
  • —🎨 Interactive Visualization: Explore knowledge graphs in your browser

🛠️ Technology Stack

  • —LLM: Google Gemini (gemini-2.5-flash)
  • —Embeddings: sentence-transformers/all-MiniLM-L6-v2
  • —Vector Store: FAISS with HNSW index
  • —Graph: NetworkX (in-memory)
  • —Backend: FastAPI + Uvicorn
  • —Frontend: Vanilla JS with D3.js/Cytoscape

📋 Setup

Required: Gemini API Key

This app requires a Google Gemini API key:

  1. 1.Get your API key from Google AI Studio
  2. 2.Add it as a Secret in Hugging Face Spaces settings:
  3. 3.Name: GEMINI_API_KEY
  4. 4.Value: Your API key

Configuration (Optional)

You can set these environment variables in Space Settings:

bash
# LLM Settings
GEMINI_MODEL=gemini-2.5-flash     # Gemini model
LLM_TEMPERATURE=0.0               # Temperature for extraction

# Embedding Settings
EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2

# Environment
ENVIRONMENT=production
LOG_LEVEL=INFO

🎯 Usage

  1. 1.Upload PDF: Click "Upload PDF" and select your document
  2. 2.Wait for Processing: The system will:
  3. 3.Extract text chunks
  4. 4.Generate embeddings
  5. 5.Build knowledge graph with Gemini
  6. 6.Explore Graph: Click nodes to see details and related concepts
  7. 7.Ask Questions: Use the chat interface for Q&A with citations

📊 Graph Generation

  • —Per-Page Extraction: Max 2 concepts per page (quality over quantity)
  • —Parallel Processing: All pages processed concurrently via Gemini API
  • —Strict Filtering: Only technical/domain-specific concepts
  • —Co-occurrence Relationships: Concepts on same page are linked

🎨 Frontend

The frontend is a single-page application located in /frontend/:

  • —index.html - Main UI
  • —app.js - Graph visualization & API calls
  • —styles.css - Styling

Access it at: http://your-space-url.hf.space/frontend/

📦 Docker

This Space uses Docker for deployment:

  • —Base: python:3.12-slim
  • —Port: 7860 (HF Spaces default)
  • —Health check enabled
  • —Persistent data directory

🤝 Credits

  • —LLM: Google Gemini
  • —Embeddings: Hugging Face sentence-transformers