Retrieval-Augmented Generation (RAG) for Knowledge-Intensive NLP Tasks

PyTorch Hugging Face FAISS LangChain OpenAI FastAPI

A state-of-the-art Retrieval-Augmented Generation (RAG) pipeline for answering complex, knowledge-intensive questions. The system combines dense retrieval with generative language models to retrieve relevant documents and synthesize accurate, context-aware answers.

Features

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