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Let Jev judge. Let your code decide. Python issue-routing sandbox with labeled replay, an offline demo, and Kev support.
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Jevidence
Python sandbox and tutorial companion that turns Jev Choice and Noul judgments about issue category and reproduction into code-applied queue proposals, with confidence gates, a review fallback, synthetic offline fixtures and labeled replay. Live mode is opt-in.
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- Python
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- MIT
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- Oct 2026
About this project
Let Jev judge. Let your code decide. A Python sandbox for turning TypeSafe Jev judgments into testable issue-routing proposals. Inspect the evidence, change a threshold, and replay labeled records without another model call. A companion to Jev for developers by Peak Evergreen. Substantially built with Codex; independent of TypeSafe.
Quoted from the project's README. Read the full README.
Used inJev for Software & DevTools
Highlights
- Offline demo and evaluate commands need no packages, API key or network after cloning, on Python 3.10+.
- One Choice (investigation area), one Noul (explicit reproduction steps) and one Score (observation specificity, 0-2) drive the teaching policy.
- Replay never contacts a model: it reports wrong specialist routes, review volume, coverage and per-threshold disagreements from labeled JSONL.
- Live mode pins the TypeSafe endpoint to https://api.typesafe.ai with SDK 0.7.1 and default model jev-1.13.0; recording a response is opt-in.
- The README states bundled judgments are synthetic, so fixture agreement measures code behavior, not model accuracy or calibration.
Watch out
MIT licensed, but the bundled judgments are synthetic fixtures rather than a real evaluation, and the package is not published on PyPI. It is advisory only and never assigns issues, changes records or executes actions.
Questions about this entry
Short answers drawn from the linked project or page.
It shows how Jev judgments can feed a small, testable policy: a category Choice selects a specialist after an allowlist and confidence gate, a Noul routes runtime reports lacking reproduction steps to review, and a Score only emits a needs_more_detail hint.
No. The demo, evaluate and replay commands run offline on synthetic fixtures. Live calls are opt-in via make setup-live with TYPESAFE_API_KEY, and replay reuses stored judgments without contacting any model.
It reports wrong specialist routes, review volume, unavailable judgments, coverage and individual disagreements for each threshold, from one JSON object per line with an issue_id, provenance, stored evidence and an independent expected_queue label. The demo video shows the same synthetic judgment falling back at 0.8 and proposing runtime investigation at 0.7, followed by policy tests.
The TypeSafe endpoint is pinned to https://api.typesafe.ai and a TYPESAFE_BASE_URL override cannot redirect this backend, the SDK is pinned to 0.7.1, the default model to jev-1.13.0, and SDK retries are disabled. The output names the actual endpoint, and --record-response can save a dated real raw response and its input, which is opt-in and refuses an existing filename.
It is advisory only: output carries applied: false, an omitted current queue is null meaning unknown, and a failure keeps the existing queue. It never assigns issues, changes records or executes actions. The README states the bundled judgments are synthetic, so fixture agreement measures code behavior rather than model accuracy or calibration, and the package is not on PyPI.
Very little, by design. The Score hint is an illustrative review signal from an averaged rubric, not proof that a report lacks detail. Reproduction gates runtime reports only in this teaching policy, since a sequence of user actions is useful for reproducing application behavior while build and documentation reports can begin investigation from error output or a specific document reference.
Python 3.10 or newer, and after cloning the offline commands need no packages, no API key and no network. python3 -m jevidence demo runs the teaching scenario, demo --route-floor 0.7 moves the routing gate, and evaluate runs the policy tests; make demo, make evaluate and make test wrap the same three. The replay command takes a labeled JSONL file and --compare-route-floor values to sweep.
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