This tutorial demonstrates integrating Jev as a System 1 decision engine in an agentic RAG pipeline. It showcases practical implementations for query routing, citation verification, and steerable cross-encoder reranking.
Original by The AI AutomatorsRetrievalIntermediate16 min 6 secPublished
Jev can replace generative LLMs for micro-decisions like routing queries between models and verifying chunk citation support.
Formulating questions using Boolean (Noul), choice, or score types constrains Jev's output schema, preventing formatting hallucinations but not incorrect judgements.
Steerable reranking with Jev combines candidate retrieval chunks with dynamic natural language instructions to prioritize results based on distinct context rules.
Worth knowing
Schema-guaranteed JSON outputs prevent formatting hallucinations and syntax errors, but Jev can still make incorrect classification decisions or wrong factual assessments.