Agentic RAG

Problem

Naive retrieval-augmented generation runs one retrieval per question and feeds the top chunks straight into the generator. It cannot decide whether retrieval is even needed for a given question, cannot choose between several available sources, cannot tell when it has gathered enough evidence to stop, and has no path to recover when the retrieval comes back with poor or irrelevant chunks. Easy questions get pointless retrieval calls, multi-hop questions get partial answers, and bad retrievals quietly corrupt the output.

Solution

Treat retrieval as a tool. The agent decides whether to retrieve, formulates and reformulates the query, picks among multiple retrievers (vector, graph, keyword, web), evaluates retrieved evidence, and re-queries on insufficient results. Composes naturally with reflection, planning, and tool-use patterns.

When to use

• A single retrieve-then-generate pass is insufficient for the task's information needs.
• Multiple retrievers (vector, graph, keyword, web) exist and the right one varies per query.
• The agent benefits from reflecting on retrieved evidence and re-querying when results are poor.