Project implements an advanced Retrieval-Augmented Generation (RAG) pipeline powered by MongoDB Vector Search and OpenAI embeddings. It demonstrates how to build a scalable, production-ready system that stores vectorized documents in MongoDB, retrieves the most relevant context using similarity search, and generates accurate responses using LLMs.
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Go7bi/Advanced-Retrieval-Augmented-Generation-RAG-with-MongoDB-Vector-Search
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