Skip to content

Jev directory

LLM Output Evaluation with Clef

Pytest-based framework that judges mocked LLM outputs with Cloudflare clef-flash, a 9B decision model served locally by Ollama. Metrics turn typed probabilities into values between 0 and 1 and PASS/FAIL against a threshold.
Stars
0
Reading time
2 min
Published by
Community
Added
Nov 2026

Highlights

  • Runs clef-flash (~9.7 GB) locally in Ollama through Docker, with no hosted judge API required.
  • Metric kinds noul, score and choice convert typed answers into value in [0, 1] and PASS/FAIL.
  • Ships rubrics for RAG correctness, safety, style, classification, routing, tool choice and A/B.
  • Judge answers are cached per model digest: about 20 minutes on the first CPU run, seconds after.
  • Requires Python 3.11+, uv, Docker with compose, and roughly 10 GB of disk for the model.

Questions about this entry

Short answers drawn from the linked project or page.

From the Jev guides

Original write-ups on what this entry is for.

From the Jev AI model community

Posts from builders shipping with Jev right now.

Follow @typesafeai