Building Production-Ready RAG Pipelines with LangChain

Why RAG Fails in Production

Retrieval-Augmented Generation (RAG) is easy to demo but hard to scale. The most common failure mode is poor retrieval relevance.

Hybrid Search is Key

Relying solely on dense vector embedding search often misses exact keyword matches (like part numbers or specific acronyms). The solution is Hybrid Search: combining vector search with BM25 keyword search.

Reranking

Always use a Cross-Encoder reranker on your top-k retrieved chunks. This computationally expensive step is only done on a small subset but drastically improves the context quality passed to the LLM.