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.
1712 projects
laya-pt-es-typed
telepatia-ai
Fine-tunes multilingual Laya for typed decisions in Portuguese and Spanish
laya-multilingual-typed-decisions
alfred361
Fine-tunes the Laya multilingual model on a typed-decisions dataset
laya-vision-modernvbert-250m
thaitea
Adds image inputs to Laya for calibrated typed decisions over images and optional text
laya-experts
goku-san
Provides Laya fine-tunes for PII detection and banking intent classification
laya-mcp
NVentimiglia
An MCP server exposes Laya decision capabilities as tools for agent workflows
home-assistant-laya
allenporter
Runs Laya as a local conversation agent for Home Assistant Assist
jev-laya-benchmark
harrymunro
Benchmarks local MLX Laya against TypeSafe's hosted Jev on synthetic decision tasks
sysone-bench
instax-dutta
Compares Laya and Jev on identical inputs across multiple decision benchmarks
laya-mlx-voice-browser
aryanbhujade
Uses a local Laya-MLX model to turn spoken commands into browser actions on Mac
mjbrain
jinlio
Fine-tunes Laya into a real-time recommendation system for Japanese riichi mahjong
runtime-tutorials
Runtime-weekly
Provides runnable Python guides for Laya classification and a comparison of Laya with other systems
decision-systems-bakeoff
actuallyrizzn
Runs a reproducible benchmark comparing Flybrain, Jev, and Laya on four public tests
jev-as-quant
jiayylu
Combines Laya and Jev with Claude in a quantitative research stack and evaluates trading experiments
Laya
ljw98
Provides a local web console and HTTP API for running Laya typed-decision models
chinese-laya
yanqiangmiffy
Fine-tunes Laya multilingual for Chinese typed decisions and evaluates the resulting checkpoints
fast-laya-compaction
ShinyDataTech
Uses local Laya decisions to compact agent context and provides filters, caching, and an MCP server
flappy-laya-openvino-cpu
rupeshs
Runs Laya inference with OpenVINO to control a Flappy Bird game on CPU
laya-studio
Hantlowt
Specializes frozen Laya representations for new decision tasks and exports portable artifacts
fast-browser
hamza-sahin
Automates Brave browser workflows through MCP using Jev or optional local Laya inference
Bud-Decision-Engine
BudEcosystem
Desktop app and local server for Laya and other Jev-like decision models
vegaml
NandhaKishorM
Produces calibrated typed decisions from frozen language models with conformal sets and abstention
layapet
elisaterumi-ai
A Portuguese virtual pet uses Laya to classify player messages locally on the CPU
laya-ara-rag
Wouze
Fine-tunes Laya multilingual for Arabic information retrieval and document reranking
laya-ara
Wouze
Fine-tunes multilingual Laya for Arabic intent classification, inference, and ranking
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