RAG

Introduction Building a chat backend powered by LLMs seems straightforward at first. You create an API endpoint, invoke your LangGraph agent, and stream the response back to the client. It works beautifully in development. Then reality hits. Users lose connection mid-response. Load balancers time out long-running requests. Your server restarts, and all in-flight conversations are lost. Scaling horizontally becomes a nightmare because each request is tightly coupled to the process handling it. ...