Production RAG Pipeline (Dvara ML)

Domain experts need accurate, grounded answers from large private document corpora — not hallucinated generalities from a base model.

A full document ingestion → chunking → embedding → vector retrieval → LLM response pipeline exposed through FastAPI, with a React frontend for real-time interaction.

Documents are chunked and embedded into a vector store. At query time, the most relevant chunks are retrieved and orchestrated into an LLM prompt through LangChain. FastAPI handles query processing, retrieval, and LLM orchestration; the whole stack is containerized with Docker.