reranker

What it is

Use Jev, TypeSafe's System One decision model, as a reranker. One call carries the query and up to 30 candidate documents; the model answers one question per document, in parallel: is this document relevant to the query? The answer is a calibrated probability, so the score is both a sort key (rerank) and an absolute…

What the README says it does

• State: {"query": ..., "documents": {"D00": {...}, "D01": {...}, ...}}
• Questions: one Noul per document id, from prompt.yaml.
• Score: the Noul probability. Calibration on the SciFact run: documents scored ≥ 0.9

From the project’s README.

Getting started

From the README:

pip install hev-rerank        # or: uv add hev-rerank
export TYPESAFE_API_KEY=...   # https://console.typesafe.ai/settings/keys

Where the decision sits

reranker calls the hosted decision API rather than running its own weights. That keeps the project small and means its behaviour moves whenever the vendor ships a new model version. It also means an API key and a network round trip sit in the path of every decision.

Models it references: Jev.

How active it is

Created 2026-09-17, last pushed 2026-09-17, 18 stars and 0 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.