Built a Hybrid RAG API with FastAPI & Ollama – Sparse + Dense retrieval in action.

Source: Dev.to

YouTube Video Tutorial

Overview

In this tutorial we dive deep into building a professional Retrieval‑Augmented Generation (RAG) system using FastAPI and Ollama. The guide goes beyond basic vector search by implementing Hybrid Search (BM25 + FAISS) and a Cross‑Encoder Reranker to ensure the language model receives the most relevant context for every query.

Key Features Covered

• FastAPI Integration – Build a real‑time API for document ingestion and query handling.
• Hybrid Search – Combine BM25 (sparse keyword search) with FAISS (dense vector search) for robust retrieval.
• Reranking – Apply cross‑encoders to re‑score retrieved candidates, boosting precision.
• Local LLM – Run the Phi‑3 model via Ollama for private, on‑device generation.