Run Laya in the browser
Laya is small enough to run in a browser tab with no server and no API key. The input never leaves the page. The trade-off is a download of several hundred megabytes on the first visit and much slower inference than a native runtime.
171 projects
Helpdesk-Laya-Router
stefanus-ai-tech
Classifies helpdesk tickets with Laya and produces Excel routing and evaluation reports
laya-post-flagger
MishraAnkit10
Classifies LinkedIn posts with a local Laya server and Chrome extension
laya-system-one
italoalmeida0
Provides a local JavaScript Laya decision engine with WebGPU and WASM acceleration
laya-sponsor-skip
Samuel-Ku
Skips YouTube sponsor reads using a local typed-decision model and a Chrome extension
jev-systemone-local
katya4oyu
Plans a local Jev-compatible System One server with MLX, Core ML, and ONNX Laya backends
laya-vs-dgpl-arena
vk-alto-none
Stages AI decision models in a game arena, including local Laya and hosted Jev
simplotel-guest-concierge
Itachi-1824
A hotel guest assistant combines retrieval, Laya classification, and validated availability
usejev
ali-master
Serves Laya through native ONNX inference on Bun with a TypeSafe-compatible API and bilingual playground
ai-second-brain-lab
dante01yoon
Combines an Obsidian knowledge workflow, coding-assistant hooks, local Laya classification, and a 3D Markdown viewer
decision-lab
Amine-LG
Provides a visual playground to build decisions and compare Jev, OpenJEV, and local Laya
fly-brain-agent
shenjie002
Drives a browser-based fruit-fly simulation with Laya decisions and spiking-neuron dynamics
laya
HydriaOne
Serves Laya routing predictions in Docker and includes an offline scenario inspector
layaAgent
vishalmysore
Runs a browser-based agent that uses Laya for routine decisions and WebLLM when needed
classifier-laya
josecruset
A local browser interface for testing Laya-MLX typed-decision models on Apple Silicon
try-laya
lin52025iq
Provides a Laya-first agent runtime with browser and Android control integrations
laya-scraper
qxZap
Uses Laya to find publication pages and extract publication details with a browser-capable crawler
LAYA_DEMO
davidL-zhan
Matches exam questions to knowledge points with local Laya yes-or-no predictions
laya-rex
luiz0ar
A browser dashboard uses Laya decisions to control the T-Rex Runner game
laya-browser
Benny93
Uses a local Laya model to resolve plain-English selectors in browser automation
zabbix-laya
j3udiel
A local web lab evaluates fictional Zabbix alerts with Laya and lets users download test results
jev-laya-tetris
HarryReidx
Benchmarks TypeSafe Jev against local Laya in a competitive Tetris duel
laya-mlx-voxel
yuxino
Builds voxel reliefs by using Laya-MLX to choose extrusion depths from image pixel statistics
laya-rlcd-expedition
HambaliMarcel
Runs local Laya decision inference in a web page for work and sales scenarios
dino-jump
ozbillwang
A browser runner game uses Laya scores to evaluate jump, duck, and run actions
Libraries
kevala is a zero-dependency Rust engine compiled to WebAssembly, with WebGPU kernels. It works from any page:
<script type="module">
import { Kevala } from "https://cdn.jsdelivr.net/npm/kevala@latest/js/src/index.js";
const kevala = await Kevala.load({ model: "laya", onProgress: console.log });
</script>
or pnpm add kevala. According to its README, the Laya int8 pack is 479 MB and is kept in browser storage after the first visit.
@r4ai/laya-web runs ONNX Runtime Web with WebGPU and a WebAssembly SIMD fallback, and is designed to run in a Web Worker:
npm install @r4ai/laya-web onnxruntime-web
Demos you can open
- layaForWeb: the English checkpoint as quantized ONNX (default build about 440 MB), with a live demo.
- open-jev-laya: multilingual Laya on Transformers.js (fp16 ONNX about 647 MB) with Gomoku, Big Two and a 3D maze.
- layaAsRagJudge: checks RAG claims against retrieved evidence entirely in the tab.
Speed and support
The layaForWeb README reports that a three-question call on the default WASM backend took about 2 to 5 seconds on a 2-core machine. In that project, WebGPU works only with the int4 build, because ONNX Runtime's WebGPU MatMulNBits kernel supports 2- and 4-bit weights. open-jev-laya tries WebGPU and falls back to WebAssembly.
Caveats
Quantized browser builds do not match PyTorch exactly. layaForWeb reports 97.9% top-answer agreement for all three of its quantized builds, with the largest probability gaps in int4. For a real-time loop, laya-pong keeps the model native. Its README gives the reason: the checkpoint wants about 2.4 GB resident in f32, and wasm32 has a 4 GB address space and no Metal.
More ways to use Laya