Intent-Aware Multi-Stage RAG Routing: Classify Queries as Factual/Procedural/Open-Ended to Auto-Route Between Fast Models and Powerful Models with 92%+ Accuracy

DEV Community·medium signal

Modern RAG systems now use intent classification as the first routing layer. A lightweight classifier distinguishes factual queries (route to fast, cheap model + vector retrieval), procedural queries (route to step-by-step reasoning model), and open-ended queries (route to powerful model with web search). LangGraph enables unified orchestration with global state tracking and fallback nodes when primary agents fail. The router agent selects optimal retrieval method (vectorstore, websearch, or composite) based on query analysis. This reduces costs by sending simple lookups to cheap models while reserving expensive inference for complex reasoning.