Tutorials 15 min read· 27 Aug 2026· By Tutorials
Building a production RAG pipeline
Ingestion, chunking, embedding, retrieval, reranking, generation — the full stack.
A production RAG pipeline is six stages. Each has good defaults and a few gotchas.
1. Ingestion#
Parse PDFs, HTML, markdown into plain text. Preserve headings and lists — they help the chunker.
2. Chunking#
See chunking strategies.
3. Embedding#
See embeddings and semantic search.
4. Retrieval#
Cosine similarity, top-K = 50.
5. Reranking#
Cross-encoder to top 5 — see reranking for better RAG.
6. Generation#
Feed top 5 chunks to GPT-5.4 Mini or Gemini 3 Flash with a strict system prompt.
The whole pipeline is ~300 lines of Python. Start simple; measure before optimizing.