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openlayer-ai / jevals

Agent evals and guardrails as Jev decisions: one request per trace, a fraction of a cent, fast enough for the agent loop. Runs locally with Kev or Laya.

Why this job: says: evals; topics: evals, llm-evaluation

What it does

Evals and guardrails for agents, using Jev-style decision models instead of an LLM judge. All the evals for a trace go out as one request that costs a few thousandths of a cent and comes back in a few hundred milliseconds, so you can run them on every trace and inside the agent loop.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 2 days ago
Stars
117
+6 this week
Licence
MIT
Allows business use
Downloads for
None listed
No release files
Latest version
None yet
No releases
Built with
Python
100% of the code

Is it looked after?

Contributors
9
Last 90 days
Issues
25% closed
3 still open
Pull requests
12 merged
1 waiting
Releases
None
Never published

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More: languages, topics and project record

Languages

  • Python 100%

Topics

  • agents
  • evals
  • guardrails
  • jev
  • llm
  • llm-evaluation
  • ragas
  • typesafe

Project record

  • JobEvals and observability
  • StatusListed
  • Commits27
  • Forks13
  • Watching0
  • Stars in 28 days+13
  • CreatedSep 20, 2026
  • First seen by usNov 7, 2026
  • CheckedNov 9, 2026

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