Show HN: Autoretrieval – Autoresearch for RAG Pipelines
Hi, inspired by Andrej Karpathy's autoresearch, I built autoretrieval, a small framework that lets an AI agent improve a RAG pipeline by running experiments against an evaluation dataset. The agent edits the retrieval pipeline, runs an eval, checks whether the F-beta score improved, keeps or discards the change, and repeats. It can try different chunking strategies, chunk sizes, the number of retrieved chunks, embedding models, keyword retrieval, and more, while keeping a log of every experiment
Story Overview
Hi, inspired by Andrej Karpathy's autoresearch, I built autoretrieval, a small framework that lets an AI agent improve a RAG pipeline by running experiments against an evaluation dataset. The agent edits the retrieval pipeline, runs an eval, checks whether the F-beta score improved, keeps or discards the change, and repeats. It can try different chunking strategies, chunk sizes, the number of retrieved chunks, embedding models, keyword retrieval, and more, while keeping a log of every experiment