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Sentinel RAG: Source-Aware Assistant

A RAG pipeline that ingests documents, generates embeddings, retrieves relevant context and returns citation-backed answers.

This project has no public repository or demo. The description leaves out any result that can't be checked.

Overview

A retrieval-augmented generation (RAG) pipeline: it ingests documents, generates embeddings, retrieves the relevant context and returns citation-backed answers.

It is built in Python with FastAPI, ChromaDB as the vector store and local models through Ollama.

Stack

  • Python
  • FastAPI
  • ChromaDB
  • Ollama
  • Embeddings
  • RAG

Interested in this kind of work?

I'm looking for remote work as a Full Stack Engineer. If you'd like to talk about this project or your team, get in touch.

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