CommunityJev Guides & Articles
Documentation
TypeSafe's official docs: the System One introduction, the three question primitives, confidence, composable patterns, cookbooks, and the HTTP API and SDK references.
- Format
- Article
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- Community
- Last verified
- Oct 2026
Works forJev for Classification
Used inJev for Software & DevTools
Highlights
- The introduction frames Jev as the first System One model: state plus typed questions in, structured answers out, no parsing.
- Documents atomic-question design: one well-scoped judgment per question, combined with logic in code.
- Ships a machine-readable index at /llms.txt for discovering every page before exploring further.
Watch out
Vendor documentation, so the claims about Jev are TypeSafe's own; live pages can change. Copy reviewed against the linked page on 2026-10-04.
Questions about this entry
Short answers drawn from the linked project or page.
The introduction plus the AI Primer: they frame Jev as the first System One model and explain why TypeSafe trains decision models instead of text generators.
Read Primitives and Patterns: ask one atomic, well-scoped judgment per question and combine results with logic in code. The startup-pitch example shows the decomposition.
Yes. The /llms.txt file is a machine-readable index of every page, meant to be fetched before exploring further.
In Cookbooks: official runnable recipes with their own datasets, latencies, and numbers — with the HTTP API and SDK references alongside when you are ready to build.
Choice returns choice, probabilities and confidence. Score returns score, probabilities and confidence. Noul returns a single number from 0 to 1 and no confidence. All three are described as composable primitives.
Yes, all three can be mixed in a single API call. Every question is evaluated in parallel and in isolation against the same state, adding questions barely changes response time, and the docs say this avoids context-rot between questions.
Choice and Score both return confidence alongside their probabilities, so your code can decide whether and how to act on an answer. Noul returns only the 0 to 1 probability, with no separate confidence.
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