Self-Reflective RAG with LangGraph: Iterative Relevance Validation Loop Replaces Single-Pass Retrieval

LangChain Blog·medium signal

Self-Reflective RAG adds a post-retrieval validation node to the LangGraph pipeline: retrieved chunks are scored for query relevance, and if below threshold, the query is reformulated and re-issued before generation. This eliminates the single-pass retrieval failure mode where the first query formulation misses the right chunks. Implementation uses a conditional edge in LangGraph: retrieve → grade → (pass to generate | rewrite query → retrieve again). The pattern also applies a generation hallucination grader as a second loop, routing unsupported answers back to retrieval.