Jev glossary
Ecosystem
Cookbook
An end-to-end recipe in the TypeSafe docs that shows a real problem, with its dataset, latencies, and measured numbers.
- Category
- Ecosystem
- Also known as
- None
- Reading time
- 1 min
- Related terms
- 3
- Directory entries
- 25
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The official cookbooks run from a few questions to full pipelines: parallel questions, re-ranking, line-by-line search, function calling, skill suggestion, entity alignment, date extraction, guardrails, and more. Each publishes the numbers behind its claims rather than only the code.
They are the best source of thresholds and patterns because the caveats come with them: tuned datasets, historical cost sweeps, and the failure cases each recipe leaves open.
Tagsdocslearning
Related terms
Definitions that connect to this one.
Parallel questionsBatching many questions into one request instead of many calls, which is dramatically cheaper and faster with identical answers.PatternsWorkflow evalsTypeSafe's published evaluations of four automation workflows, comparing Jev and frontier LLMs as structured workflows versus single prompts.Evaluation & TrainingSDE cascadeA two-stage extraction cascade: a mini model extracts, a Noul battery verifies, and a confidence gate escalates to a reasoning model.Patterns
From the Jev directory
Directory entries that go deeper on this term.
The canonical introduction: Jev is TypeSafe's flagship model and the first System One model. Send state and typed questions, get structured answers your code can use directly.
Jev Guides & ArticlesDocs#docs#official#primitives
Official
A 13-question regulatory briefing that shows batching every question into one call is 12.2x cheaper and 10x faster with no change in answers.
Jev CookbooksDocs#official#cookbook#batching
Official
A two-stage extraction cascade: a mini model extracts, a Noul battery verifies each field in one request, and a 0.7 gate escalates to a reasoning model, sitting on the cost/quality frontier.
Jev CookbooksDocs#official#cookbook#extraction
Official
A community curriculum of Jupyter notebook recipes that teach typed decisions with Jev, TypeSafe's System One model. Each recipe takes one bounded Choice, Noul or Score decision over text or image state, spanning first classification through closed-loop control.
Jev Cookbooks#community#github#python
A support-ticket cookbook that lets Jev decide which requests are worth remembering, then wraps each call so saved tickets ride along in the state. Six later messages route correctly with memory against two without.
Jev CookbooksDocs#official#cookbook#memory
Official
A live chat filter that asks three questions per message (category, toxicity, and spoilers), then turns the answers into show, highlight, dim, hide, or blur in plain code. The 29-message example hides seven, blurs two, and highlights six.
Jev CookbooksDocs#official#cookbook#moderation
Official
19 more matching entries in the full directory.
From the Jev AI model community
Posts from builders shipping with Jev right now.