Intelligent Document Assistant (RAG)

🧠 Contextual Intelligence

This project leverages the power of LLMs through a RAG (Retrieval-Augmented Generation) architecture to enable precise interactions with large knowledge bases.

• •Hybrid Search: Combining semantic search (vectors) and keyword search (BM25) for maximum accuracy.
• •LangChain Orchestration: Complex management of processing chains, from document chunking to result re-ranking.
• •Anti-Hallucination: Grounding verification system to ensure responses come exclusively from provided documents.

🛠️ Tech Stack

• •AI Layer: OpenAI GPT models, LangChain.
• •Vector DB: Pinecone / ChromaDB for embedding storage.
• •API: High-performance backend with FastAPI.