Topics / #typed-decisions

Typed-decisions projects on GitHub

As of October 18, 2026, the most-starred Typed-decisions projects on GitHub are laya (33.4K stars), laya-mlx (7K stars) and skills (2.7K stars). GitHub.Locker tracks 15 Typed-decisions repositories with 56.9K stars combined. The fastest-growing on October 17 was laya, with +100 stars in a day.

15Projects

56.9KStars in total

+216Stars in a day

Browse in the catalog →github.com/topics/typed-decisions ↗

Hot right now

Most stars gained in a day · Oct 17

+100

laya

NandhaKishorM/laya · ★ 33.4K

Laya is a non-autoregressive decision engine: instead of generating text, it answers typed questions — multiple choice, a numeric score, or yes/no — about any text in a single forward pass, across 100+ languages. A built-in router detects the language and picks the right checkpoint per request.

+86

The all-time top

15 projects · by stars

#1 · NandhaKishorM/laya
laya
Laya is a non-autoregressive decision engine: instead of generating text, it answers typed questions — multiple choice, a numeric score, or yes/no — about any text in a single forward pass, across 100+ languages. A built-in router detects the language and picks the right checkpoint per request.
33.4K
#2 · mizorewww/laya-mlx
laya-mlx
Laya-MLX is a native MLX runtime that runs the open-weight Laya typed decision models locally on Apple Silicon, returning structured answers like a choice, a rubric score, or a probability in milliseconds instead of generating text.
7K
#3 · typesafe-ai/skills
skills
A set of agent skills for building with TypeSafe: they let your coding agent get typed decisions and probabilities from System One models.
2.7K

4
awesome-jev
2.4Kyibie/awesome-jev · Python
A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions. It tracks who is actually building with it and which decision patterns transfer across industries.
5
nimble
2.2Kbespokelabsai/nimble · Python
Bespoke Nimble turns text plus a schema of questions into typed decisions: it picks one allowed answer per question and returns the probability of every option, in a single fast step. The repo shares the recipe and the trained Bespoke-Nimble-9B model.
6
deepopen
2Kdeepopen-com/deepopen · Python
DeepOpen is an open-source, non-autoregressive 'System 1' decision engine: instead of generating text token-by-token like an LLM, it makes typed decisions (choice, score, or boolean) over text, email, tickets or JSON in a single forward pass, across 100+ languages, in as little as 33ms.
7
laya-coreml
1.6Kmizorewww/laya-coreml · Python
It's an open-weight Python port of Laya that answers typed questions — pick an option, an ordinal score, or yes/no — locally on Apple Silicon through Core ML and the Neural Engine, generating zero text tokens.
8
jeff
1.5Kfirelex/jeff · Python
Jeff is a family of small (0.8B-2B parameter) open-weight models fine-tuned from Qwen3.5 and Gemma 4 that act as fast 'System 1' decision-makers: you describe a situation and a list of options in plain text, and Jeff returns a calibrated probability for each option from a single forward pass, with no generated text to parse.
9
decider
1.2KMapika/decider · Python
Decider is a family of language models fine-tuned from Qwen3.5 that don't generate text; instead they read a state plus a set of typed questions and return calibrated probability distributions for every question in one forward pass.
10
TypeLLM
960TypeLLM/TypeLLM · Python
TypeLLM adds type-safe, schema-guaranteed output generation to existing open autoregressive LLMs, without changing their weights or architecture, letting models still think freely while returning typed JSON Schema-constrained answers.
11
Intent-Router
763angel291592/Intent-Router · Python
Intent-Router is an 'intent compiler' skill for AI coding agents: it turns a vague request into a typed IntentSpec contract by looking up what it can, asking only what a human must decide, or halting when the request is contradictory, ambiguous, or underspecified.
12
StartLux-Decision
648StartLuxLabs/StartLux-Decision · Python
StartLux-Decision is a family of typed decision models (five dense sizes from 0.8B to 27B plus a 35B-A3B mixture-of-experts) that answer a question with a probability for each option instead of generating text.
13
awesome-jev
239Amal-David/awesome-jev · Python
A curated awesome-list of demos, projects, SDKs and skills built with Jev — 44 reviewed picks with source links, plus a curated gallery of demos from X and YouTube.
14
open-jev
134daseinlabs/open-jev · Python
An open implementation of Jev: a local Gemma 3 4B (via MLX) scores a list of pre-written options against a context in one batched forward pass on Apple silicon — no text generation, just log-probabilities per option.
15
Bud-Decision-Studio
110BudEcosystem/Bud-Decision-Studio · HTML
Bud Decision Studio is a cross-platform desktop app and local serving system for 'decision models' (Jev-like 'System One' models): you give it a situation and typed questions, and it returns a calibrated probability for every allowed answer instead of generated text.

Hot right now

laya

StartLux-Decision

awesome-jev

skills

The all-time top

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