Laya for Python
The reference implementation of Laya is the `laya` package on PyPI, maintained by Convai Innovations under Apache 2.0. It ships three checkpoints, a Router that picks one per request by script and language, a CLI, an HTTP server and an optional MCP server.
1713 projects
laya-invaders
inhabitants
Uses Laya to choose targets in a Space Invaders game and compares it with a rule baseline
jev-laya-benchmark
EnesDemir143
Benchmarks TypeSafe Jev and Laya-MLX on structured issue classification
laya-learning-demo
Daryl9441
A runnable tutorial teaches Laya decision primitives, routing, fine-tuning, and comparison with Jev
laya-omni-agent
yashrastogi069-dev
An autonomous agent combines local Laya or Jev routing with cloud reasoning and browser, OS, and data tools
tetris_for_laya
fchange
Provides a terminal Tetris environment where a local Laya model chooses each action
laya-mcp-mimo-desktop
miniongk
Bridges Laya typed decisions into MiMo Desktop through a local stdio MCP server
laya-mlx-per-turn-classifier
M37Labs
Demonstrates per-turn customer message classification with Laya on Apple Silicon
decision-infra
hufaei
Routes typed-decision requests to hosted Jev or local Reflex, SemIf, and Laya models
macos-use
ArdaOzd
Controls native macOS apps and Chrome using spoken or typed commands with local Laya or hosted Jev decisions
system-one-playground
minkhant1996
Provides a local web playground for Laya and other System One decision models
second-thought
KNambiarDJsc
Measures decision calibration, prioritizes human review, and builds fine-tuning datasets
hd5-antigravity-jev
alpaslan-exe
A workshop teaching developers to build projects with Antigravity and locally run Laya decisions
laya-cuda
adamjen
Benchmarks Laya typed-decision checkpoints with a CUDA backend on NVIDIA GPUs
laya-exp
changtimwu
Experiments comparing an MLX Laya port with Jev and a TypeSafe-compatible Laya client
laya-main
bill9924
Maps patent texts to OpenAlex concepts using TF-IDF retrieval and a Laya decision model
laya-lab
Alevsk
Runs Laya locally with reproducible scenarios that explore its capabilities on Apple Silicon
laya-rn-executorch
ksanjiv05
Exports and runs Laya decision models offline in a React Native app using ExecuTorch
laya-computer-use
koushikvarma37-jpg
Runs a local Windows voice assistant that uses Laya to choose intents and actions
laya-inference-engine
aaditagrawal
Provides a GPU inference engine and performance modes for Laya on NVIDIA Blackwell
laya-adk-toolkit
Ashfaqbs
Google ADK tools expose Laya's typed-decision engine for classification, scoring, and detection
decision-making
tzt-company
A local demo runs Laya for multilingual text decisions and Git commit risk checks
laya-ko-decision-onnx
2nugu
Fine-tunes Laya for Korean decisions and provides PyTorch training and ONNX export scripts
Tern
AmRitJain0442
A model router uses local Laya-MLX inference to select between configurable provider tiers
agent-decision-firewall
chinna250801
Gates AI agent actions with a local Laya decision model and fail-closed rules
Install
Python 3.10 or newer, per the core README:
python -m pip install laya
Optional extras: laya[serve] (HTTP server), laya[mcp] (MCP server), laya[langchain], laya[onnx] (ONNX Runtime) and laya[fast] (TileLang GPU fast path).
First decision
from laya import Router
router = Router() # downloads a checkpoint on first use
state = "Hi, we were billed twice for March. Please refund the duplicate today or we will cancel our plan."
questions = {
"department": {"type": "choice", "instructions": "Which department should handle this?",
"criteria": {"billing": "invoices, payments, refunds",
"technical": "bugs, outages, system errors",
"other": "everything else"}},
"urgency": {"type": "score", "instructions": "How urgent is this?",
"criteria": ["not urgent", "soon", "blocking"]},
"churn_risk": {"type": "noul", "instructions": "Does the user threaten to cancel or leave?"},
}
result = router.predict(state, questions)
print(result["answers"]["department"]["choice"]) # billing
print(result["routing"]["model"]) # english
The package also installs a laya command, for example laya "My payment failed twice" --preset triage.
Checkpoints
| checkpoint | encoder | params | context |
|---|---|---|---|
laya |
ModernBERT-large | 421M | 512 |
laya-multilingual |
mmBERT-base | 322M | 1024 (up to 8,192) |
laya-typed-decisions |
ModernBERT-large | 421M | 1024 |
The README reports 32.8 ms for one question with laya-multilingual on a Tesla T4, and 193 to 464 ms per request on CPU with checkpoints preloaded.
Other Python projects
laya-mlx and laya-coreml for Apple Silicon, laya-openvino for Intel CPUs, edgejev for INT8 ONNX on CPU, and laya-mcp for agent tools.
Caveats
The README is direct about limits: the base checkpoints score near chance on its typed-decisions benchmark (0.362 and 0.352), and the 0.766 figure comes from the fine-tuned checkpoint. Temperatures should be refit on your own data before you trust the probabilities. The English checkpoint collapses on non-Latin scripts, which is why the Router exists.
More ways to use Laya