Self-Querying & Citations
Push RAG further with self-querying retrievers that turn natural language into metadata filters, and answers that cite their sources so users can trust and verify them.
When Questions Carry Filters
Users ask things like give me 2023 reports about pricing. That sentence contains a filter (year 2023) and a semantic query (pricing).
A self-querying retriever automatically separates the two.
How Self-Querying Works
An LLM reads the question and emits a structured query: the semantic search string plus a metadata filter. The retriever then applies both to the vector store.