Embeddings

IndexFlatIP works for small corpora. For production with 100K+ vectors, you need smarter indexes. Here’s how to choose and implement them.

Picture this: You’re asking an AI about cancer treatments. It sounds super confident and gives you detailed answers. But here’s the problem — it just made up a medical study that doesn’t exist.

RAG is a design pattern, not a product. LangChain supports it out of the box. This guide shows a production-ready RAG setup in LangChain with architecture, retrieval choices, runnable code, evaluation metrics, and trade-offs from my client projects.