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rag

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A full-stack, multimodal Retrieval-Augmented Generation (RAG) application that allows users to upload PDF documents and engage in a real-time, conversational Q&A. The backend, built with FastAPI, handles PDF parsing, advanced semantic chunking, and a dual-strategy (semantic + keyword) retrieval from a ChromaDB vector store. The frontend is a modern

  • Updated Jun 23, 2025
  • TypeScript

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