mongodb/chatbot

Implements a RAG (retrieval-augmented generation) system combining MongoDB's document storage with Atlas Vector Search for semantic retrieval, enabling context-aware responses grounded in MongoDB documentation. The architecture ingests and vectorizes knowledge sources, then routes user queries through semantic search to retrieve relevant documents before passing them to a language model for generation. Built as a framework for knowledge-based AI assistants, it abstracts the pipeline for retrieval, ranking, and prompt engineering.

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