Building a Robust RAG Pipeline Architecture for Production

Short summary

A practical guide to building a production-grade RAG pipeline covering ingestion, chunking, embedding, vector storage, retrieval, and LLM generation. The author shares a modular FastAPI + LangChain architecture with externalized config, real code examples, and lessons from debugging SQLAlchemy session leaks under load. Key trade-offs around chunk size, hybrid search, and component swappability are discussed.

• •Modular RAG architecture with seven layers: ingestion, chunking, embedding, vector store, retrieval, LLM generation, and orchestration
• •Externalized YAML config allows swapping components (loaders, vector stores) without code changes
• •Production lessons include SQLAlchemy session leak debugging and chunk-size tuning trade-offs

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