AI Document Intelligence System (RAG + Semantic Search)

A production-style AI system for uploading documents, extracting text, and performing semantic search and question answering using Retrieval-Augmented Generation (RAG).

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🚀 Features

• 📄 Multi-format document support (PDF, DOCX, TXT, Images)
• 🔍 Text extraction (OCR + parser-based)
• 🧠 Semantic search using FAISS + Sentence Transformers
• 💬 Question answering over documents (RAG-based)
• 🧩 Chunking + embedding pipeline
• 🧠 AI fallback summarization (works without API key)
• ⚡ FastAPI backend (production-ready structure)

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It supports:

📄 Multi-format document ingestion (PDF, DOCX, TXT, images via OCR) 🧠 RAG-based semantic search using vector embeddings 💬 Chat-with-document interface (Ask questions directly on uploaded files) 🔍 Intelligent text chunking and retrieval system 📊 Automatic document insights (keywords, summaries, complexity analysis) ⚡ Hybrid AI pipeline (OpenAI + fallback local logic) 🧱 Modular architecture designed for scalability and production deployment

The system is designed as a foundation for enterprise-level document AI systems, combining information retrieval and generative AI.

🏗️ Architecture

Upload File ↓ Text Extraction ↓ Chunking ↓ Embedding (SentenceTransformer) ↓ Vector Store (FAISS) ↓ Semantic Search ↓ Answer Generation (RAG)