I Built a Production-Style RAG Backend — Focused on What Happens When Things Break

Most RAG tutorials show you the happy path.

Ingest document → generate embeddings → store in vector DB → search → return results.

It works great in demos. But what happens when:

The worker crashes mid-processing?

Kafka replays messages and you get duplicates?

The database goes down during ingestion?

A malformed document gets stuck in an infinite retry loop? I built SmartSearch to answer those questions — a correctness-first ingestion and retrieval backend designed to handle failures deterministically.

The Problem With Most RAG Systems

Most RAG implementations are optimized for the happy path.…