pcastiglione99/RAGify-Search
RAGify is designed to enhance search capabilities using Retrieval-Augmented Generation (RAG). By combining traditional web search with AI-driven contextual understanding, RAGify retrieves relevant information from the web and generates concise, human-readable summaries.
Built on Streamlit with a modular architecture, RAGify implements document chunking and semantic embedding via vector similarity search, backed by local LLM inference through Ollama for privacy-preserving processing. The pipeline chains web scraping, prompt optimization, and context-aware generation—with automatic temporary file cleanup to manage storage. Targets users prioritizing data privacy while maintaining real-time information retrieval through integrated web search.
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Language
Python
License
MIT
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Last pushed
Mar 01, 2025
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