jev-cookbook (paramjeetn)
Community Jev cookbook with 10 runnable examples, composition patterns, theory notes and a list of 120+ use cases.
This repository is mostly documentation or write-up rather than runnable code.
Overview
This Jev Cookbook collects examples, composition patterns and background theory for building with Jev. It explains Jev as a calibrated zero-shot classifier that returns probability distributions rather than tokens, and positions it as a fast first layer: high-confidence answers go straight to application logic, low-confidence ones fall back to a slower LLM.
The repository includes a quick start through the TypeSafe console, a Python requests example, ten runnable examples, four composition patterns and a list of more than 120 use cases. The README makes performance claims such as about 100 ms responses and 400 times lower cost than traditional LLMs; these are the author's framing and not measured in the repo excerpt. It is mainly a learning resource rather than a tool.
What the decision model decides
| Type | Question | Answers |
|---|---|---|
| Choice | Why is the user canceling? | bug_frustration · price · competitor · unknown |
| Yes / no | Is this user at serious risk of permanently leaving? | — |
How it works
- Try a state and questions in the TypeSafe console
- Call the API from Python with state and questions in one body
- Act on high-confidence answers in code
- Fall back to an LLM when confidence is low
Strengths
- Broad catalogue of use cases and patterns
- Examples need no SDK
- Clear confidence-fallback architecture
Caveats
- Performance claims are not backed by measurements in the excerpt
- Mostly documentation; maturity of examples unclear
Getting started
Paste the sample state and questions into console.typesafe.ai, or run the Python requests example with TYPESAFE_API_KEY in a .env file.At a glance
- Type
- Project
- Language
- Python
- Has code
- yes
Use cases and integrations
How curated lists describe it
The complete cookbook for Jev by TypeSafe AI — 120+ use cases, 10 runnable…
wh000wh000/awesome-jev-liveThe complete cookbook for Jev by TypeSafe AI — 120+ use cases, 10 runnable examples, 4 composition patterns, and first-principles theory for the world's first System One AI model.
hellogumbo/awesome-jev
Frequently asked questions
What is in the cookbook?
Ten runnable examples, four composition patterns, theory notes and a list of 120+ use cases.
How does it handle uncertain answers?
It recommends falling back to a slower LLM when Jev's confidence is low.
Do I need an SDK?
No, the examples use plain HTTP via Python requests.
Related projects
Awesome list and guide to System One models (Jev, Laya and others) organized around a five-stage agent lifecycle, with comparison tables.
ProjectproductionOpinionated catalog of 84 Jev projects in 11 categories, each with a hand-written reason it is worth looking at.
ProjectproductionUnofficial collection of Jev state formats, question patterns, cookbook index and case studies, plus a ranked Top 30 of community builds.
ProjectproductionBilingual catalogue of 183 Jev applications in 11 categories, explaining how each works and what its demo actually proves.
ProjectproductionKorean course code for attaching Jev to Claude Code, Codex and OpenClaw: skills, hooks, routers and open-model comparisons.
ProjectproductionJavaScriptRepository behind jevhub.io: plain-English Jev guide, ready-to-run examples, cost data and a directory of community builds.
Projectproduction