Docs
CommunityJev Tools & CLIs
Jev on Workers AI
Cloudflare Workers AI's model page for typesafe/jev: run the structured evaluation model through an env.AI.run binding or the REST /ai/run endpoint, with typed Noul, Choice, and Score questions and worked examples.
- Format
- Docs
- Reading time
- 3 min
- Published by
- Community
- Last verified
- Sep 2026
Highlights
- Runs as model typesafe/jev with a 32,000-token context window; the model page is marked third-party.
- One env.AI.run call takes a state plus Noul, Choice, and Score questions and evaluates them together.
- Worked examples cover a duplicate-charge refund review, support department routing, and account risk scoring with escalation.
- Responses carry the resolved model ID (jev-1.13.0), per-option probabilities, a separate confidence, and token usage.
- Input and output JSON schemas are downloadable, and pricing is shown only in the Cloudflare dashboard.
Quickstart
ts
const response = await env.AI.run('typesafe/jev', {
state: 'Help! My payouts have been failing for 3 days.',
questions: {
is_urgent: { type: 'noul', instructions: 'Does this convey urgency?' },
department: {
type: 'choice',
instructions: 'Which team should handle this?',
criteria: { billing: 'Payments', technical: 'Bugs', sales: 'Pricing' },
},
},
})Watch out
A platform model card rather than an evaluation: it publishes no accuracy or calibration numbers, and pricing is a dashboard link rather than a listed rate.
Questions about this entry
Short answers drawn from the linked project or page.
No TypeSafe key appears anywhere in the examples. You authenticate to the platform instead, with env.AI.run('typesafe/jev', ...) inside a Worker or POST to /ai/run on the REST side using your Cloudflare account ID and an AI API token as a Bearer credential. The model is flagged third-party, and the card lists zero data retention.
The card states a 32,000-token context window and nothing more about quality inside it. There are no accuracy figures, no calibration numbers and no latency benchmarks, because this is a platform model listing rather than an evaluation. The worked examples are small, around 426 input tokens for a support message with three questions, so nothing on the page tells you how the model behaves near the limit.
Both. The structured refund example passes a nested JSON object as state, with a ticket holding subject and message, an order holding an array of charge records, and a refund_policy string, then asks whether the policy supports the refund given those charges. One call evaluates all three question types together, so a question can reference fields of the state rather than a flattened prompt.
Answers keyed by question id, plus the resolved model id such as jev-1.13.0 and input and output token counts. A noul gives a single probability, a choice gives the picked option, per-option probabilities and a separate confidence, and a score gives a fractional value, its rubric legend and probabilities, which is why the sample returns 1.04 on a three-level scale. Choosing thresholds stays your code's job, and confidence is not the same quantity as a noul probability.
The model page lists $0.042 per million input tokens and $0.00 for output and cached input, and marks the model third-party with zero data retention. It publishes no accuracy or calibration numbers, because this is a platform model listing rather than an evaluation.
Inside a Worker, env.AI.run('typesafe/jev', { state, questions }); from anywhere else, POST to the account-scoped /ai/run endpoint with a Bearer token and a body of { model: 'typesafe/jev', input: { state, questions } }.
A duplicate-charge refund review that passes a nested state with an order and a refund policy, a support request routed to the right department, and account risk scoring with escalation. The refund example returns noul 0.99 for refund_requested and 0.98 for policy_supports_refund.
Reactions & coverage
Posts, threads, and videos about this entry from around the web.
X: Search and tagging on keep.md
Reddit: Jev is on Workers AI as typesafe/jev
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.