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JevOps

Python kernel of Jev Choice/Score/Noul gates, caches and loops used to admit or reject Lean proof candidates in research pipelines.

LibraryresearchAGPL-3.0

Overview

JevOps is a TypeSafe/Jev kernel split out of the Lean Refactor Arena and related papers. It treats Jev as a gate, not a generator or a proof authority: optional refactoring and autoencoder modules propose Lean candidates, Jev ranks and filters them, and only the consuming Lean/Lake verifier can admit them. The verifier is injected by the caller.

The package contains many modules: Choice, Score and Noul projectors with a fixture client, a Jev beam and ranking picker, an outer action loop with stall and stop handling, an oracle for ordering candidates, layered caches with context budgets, success and failure memory, a goal/subgoal board and a guarded legal adapter. A roadmap describes a proposed workflow for formalising parts of the U.S. Code with source locks, and the README is explicit that this is a plan, not a claim of formalisation. It is a research codebase for people building verifier-backed search loops, licensed AGPL-3.0.

What the decision model decides

TypeQuestionAnswers
ChoiceWhich candidate (e.g. Lean edit) should be tried next? (Jev beam)(inferred)—
Yes / noShould this candidate step be admitted for verification?(inferred)—
ScoreHow promising is this candidate?(inferred)—

How it works

  1. Generator modules propose Lean candidates
  2. Jev projectors rank and filter candidates in a beam
  3. Outer loop routes the next action and detects stalls
  4. Caller-supplied Lean/Lake verifier admits or rejects
  5. Memory records successes, failures and blacklists

Strengths

  • Clear separation: model gates, verifier decides
  • Injectable verifier and fixture client for offline tests
  • Caching and context budgeting built in

Caveats

  • Research code with many experimental modules
  • Legal formalisation work is a proposed plan, not a result
  • Native backend qualification still pending per the README

At a glance

Type
Library
Status
research
Language
Python
Runtime
library
Has code
yes
Has tests
yes
License
AGPL-3.0

Use cases and integrations

How curated lists describe it

  • Jev is a \*\*gate\*\*, not a generator. This package does \*\*not\*\* write Lean. Lake (or another oracle) lives in the implementation that \*uses\* the kernel.

    logicrw/awesome-jev-projects

Frequently asked questions

Does JevOps write proofs?

No. It gates and ranks candidates; generation is done by other modules and admission by a Lean/Lake verifier.

What is the legal roadmap?

A proposed plan to apply the kernel to source-grounded U.S. law formalisation, explicitly not a completed result.

Can I test without the API?

Yes, a FixtureClient replays Jev answers for offline tests.

Related projects

  • Explainable day-trip planner where an LLM drafts the itinerary and Jev screens places, compares transport and reviews each step.

    AppprototypeTypeScript
  • Research implementation of Jev-style typed decisions over clinical evidence: supported, contradicted or unresolved.

    ProjectresearchPython
  • Inference-time loop where a System One judge like Jev scores a model's thought paths and picks which reasoning branch to keep.

    ProjectresearchPython
  • Python harness stress-testing Jev's confidence, its accuracy as a RAGTruth hallucination judge, and its use as a RAG reranker.

    DemoresearchPython
  • Local decision engine on zero-shot ModernBERT and SigLIP2 answering Choice, Noul, Score and Relation over text, documents and images.

    ServicebetaPython
  • Open-weight 0.6B decision model on a Qwen3 backbone: state and typed questions in, a probability for every option out, nothing decoded.

    ModelresearchPython