Use Laya from Node.js
You can run Laya inside a Node.js process with ONNX Runtime, or keep the model in a separate server and call it over HTTP. Both routes use the same state-plus-typed-questions request shape as the Python package and the Jev API.
378 projects
decision-lite
cckyros
Provides a Jev-compatible MCP decision server with pluggable local and hosted model backends
@tanstack/ai-ollaya
GitHub Actions
Connects TanStack AI to local Ollaya or Laya servers for typed decision evaluation
@fllstck/mlayax
kay-is
Runs the Laya typed-decision model in Node and Bun on Apple Silicon using MLX
@reasoning-router/classifiers
robertn702
Provides reasoning-effort classifiers for Jev, Clef, and Laya through HTTP
laya-compaction
bussolabs
A Claude Code plugin that uses Laya decisions to compact context by dropping or truncating tool history
laya-router
bussolabs
A Claude Code and Codex plugin that routes each turn to a model tier using Laya decisions
22-minds
Satya141
Runs a football simulation where each player uses Laya to choose actions during play
outfit-decider
bo-830
Ranks outfit photos with quick structured scores and optional multimodal analysis
laya
junaidariie
Classifies and routes support tickets with Laya before generating responses
playwright-laya-healer
sahil9256
Uses a local Laya/Jev decision model to repair and verify broken Playwright locators
Jev-Laya
SilverRuler
Runs Laya locally behind a Jev-compatible API and browser playground
LLMAutoRouter_Laya
nitesw
Routes Claude Code prompts to model tiers using a fine-tuned Laya decision model
laya
jetmiyoung
Provides a multilingual typed-decision engine with Python and integrations for serving and agent frameworks
jev-pipeline-analysis
bogdancstrike
Enrich text locally with configurable GLiNER and Laya analysis engines
system-one-harness
mev0lent
Compares Laya and other decision models as gates for HTTP response triage
triage-cascade
teddywinglee
Routes support tickets through a Laya classifier and escalates uncertain cases to a local LLM
dsh-system1
GitHub Actions
Provides typed System One decisions for DeepSeek Harness plugins with Jev, Laya and Clef providers
jev-creator-decoder
sujalkanere
Labels YouTube Shorts and evaluates hooks using local Laya or the optional Jev model
decision-model-arena
dante01yoon
Compares four decision models, including local Laya, across games and image-based decisions
laya-heart
r5x8ksva-del
A local desktop copilot uses Laya to interpret couple chats and Gemma to draft reply suggestions
Laya
areeb26
Provides a multilingual typed-decision model with Python, server, MCP, and framework integrations
ducktape-laya
adrian729
Embeds local Laya GGUF inference through C++, Rust, Node.js and experimental browser bindings
@marg-adk/verdict
GitHub Actions
Provides typed decision cascades with Laya support, calibration, an MCP server, and an HTTP server
laya-mcp
Hypokoto
Runs the Laya ONNX decision model locally and exposes policy and code-analysis tools through MCP
In-process: @receptron/laya
@receptron/laya runs the model with ONNX Runtime, so neither Python nor PyTorch is needed at runtime. It requires Node.js 20 or newer.
npm install @receptron/laya
import { Laya } from "@receptron/laya";
const laya = await Laya.load();
const result = await laya.systemOne(
{ subject: "Refund not received", body: "I cancelled two weeks ago and still have no refund..." },
{
department: {
type: "choice",
instructions: "Which team should handle this ticket?",
criteria: { billing: "payments, refunds, invoices", support: "product help and bugs", sales: "new purchases" },
},
churn_risk: { type: "noul", instructions: "Is the customer likely to cancel or dispute?" },
},
);
result.answers.department.choice; // "billing"
await laya.close();
Per its README, the fp32 ONNX weights are about 1.7 GB and download on first use. Budget roughly 2 GB of RAM. A three-question call takes about 140 ms on an Apple Silicon CPU once warm, and the output matches the Python implementation to four decimal places. The package is MIT-licensed; the weights are Apache 2.0.
Over HTTP: laya-studio
laya-studio is a zero-dependency TypeScript client for a running Laya server (Node.js 18.17+):
npm install laya-studio
pip install "laya[serve]"
laya-serve # binds 0.0.0.0:8000
Other JavaScript projects
- @r4ai/laya-web: ONNX Runtime Web runtime for browsers and Node.js.
- kevala: a Rust engine compiled to WebAssembly with WebGPU kernels, installable from npm.
- gg-friggin-ez: a profanity and toxicity screener that defaults to Jev and can point at a local Laya endpoint.
Caveats
The English checkpoint's options must fit a 192-token budget and the state is cut at 512 tokens. The receptron README recommends fewer than about 20 options per choice question.
More ways to use Laya