Cover image for "Videogame Assist RAG"

Videogame Assist RAG


๐Ÿ”— GitHub Repository

A Retrieval-Augmented Generation (RAG) system built with Azure OpenAI and Azure Cognitive Search, featuring both console and web interfaces for document-based question answering about video game manuals and guides.

๐Ÿš€ Features

  • ๐Ÿ“„ PDF Document Processing: Automatically extracts and processes PDF documents using Azure Document Intelligence
  • ๐Ÿ” Vector Search: Uses Azure Cognitive Search with semantic search capabilities and text embeddings
  • ๐Ÿ’ฌ AI-Powered Chat: Leverages Azure OpenAI GPT-4o-mini for intelligent responses
  • ๐ŸŒ Web Interface: Interactive Streamlit chat interface with conversation history
  • ๐Ÿ–ฅ๏ธ Console Interface: Command-line interface for quick interactions
  • ๐Ÿ“Š Analytics: Chat statistics and export functionality
  • ๐Ÿ”’ Secure: Environment-based configuration with no hardcoded secrets
  • โšก Smart Processing: MD5 hash checking to avoid reprocessing unchanged documents

๐Ÿ—๏ธ Architecture

This RAG system combines several Azure services:

  • Azure OpenAI: For text generation and embeddings
  • Azure Cognitive Search: For vector search and document indexing
  • Azure Document Intelligence: For PDF text extraction
  • Azure Blob Storage: For document storage

Architecture Diagram