PRODUCTION RAG: WHAT I LEARNED FROM PROCESSING 5M+ DOCUMENTS

Summary from the TLDR Dev newsletter

After building Retrieval Augmented Generation (RAG) systems for two large datasets, this dev found that initial success with Langchain and Llamaindex was misleading, as real-world performance required much more refinement. The most impactful improvements came from query generation, reranking, custom chunking strategies, incorporating metadata, and query routing.