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How to block agent replies that fail checks before they reach the user with Jevals

Run evals inside an async agent loop with aevaluate() or a gate's acheck().

Who it is forA developer shipping an agent whose replies must pass scope and relevance checks before they go out.

The problemOffline evals catch problems after users see them, and slow judges are too expensive to run on every reply.

The outcomeA gate in the request path that checks each reply and can stop or retry it, using the same eval definitions you used offline.

What you need first

  • Python 3.10 or newer
  • An API key for one backend: AI_GATEWAY_API_KEY (Jev through Vercel AI Gateway), TYPESAFE_API_KEY, or OPENROUTER_API_KEY
  • A trace to evaluate: a messages list in the OpenAI chat format plus the tools you gave the model

Steps

  1. pip install jevals
  2. export AI_GATEWAY_API_KEY=...
  3. Define your checks with StayedInScope() and AnswerRelevancy() from jevals.agent and jevals.quality
  4. Inside your async agent loop, await aevaluate() on the current messages and tools, or call a gate's acheck()
  5. Branch on the result: return the reply if it passes, otherwise regenerate or fall back

Prompt for your agent

Wire jevals into the async agent loop in <agent_file>. Use aevaluate() with StayedInScope() and AnswerRelevancy() on each reply before it is returned. Report the latency added per reply. Verify that a reply that fails either check is not sent to the user.

Caveat. Calibrated probabilities depend on the backend, so run Jevals calibrate again if you switch backends before relying on a gate threshold.

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