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Title: AI Document Search RAG Chatbot
Description:
Built a RAG chatbot for PDF Q&A using FAISS vector search, FastAPI backend, and React frontend. Users upload documents and get accurate AI answers from their own files.
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Connect with clients, get discovered, and run your business 100% commission-free
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Developed a production-ready Retrieval-Augmented Generation (RAG) AI Chatbot using Python, FastAPI, LangChain, and ChromaDB. The application allows users to upload documents (PDF, DOCX, TXT, CSV, XLSX) or scrape website content, automatically indexes the data into a vector database, and answers questions using semantic search and LLMs. It supports conversational memory, multi-format document ingestion, REST APIs, and a responsive web interface for accurate, context-aware AI-powered question answering.
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