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.
696 projects
code-oracle
wahyuzero
Verifies code changes with AST checks and Laya-based residual-drift evaluation
seems-laya
ericmjl
Runs natural-language judgments in the Seems programming language using the local Laya decision model
laya-mlx-zh
ZLHAOOO
Provides Chinese fine-tuned Laya weights, training data, and evaluations for Apple Silicon MLX
opencode-jev-compaction
jlegends
Two OpenCode plugins prune stale tool calls and optionally refine decisions with local Laya
@gobing-ai/ts-laya-mlx
GitHub Actions
A TypeScript package connects applications to a local Laya decision backend through MLX
laya-doom
shantanugoel
A Doom game experiment uses a frozen Laya encoder and a trained decision head
laya-rs
codesoda
A planned Rust runtime for local Laya decisions with Metal acceleration and a Jev-compatible HTTP API
laya-playground
marcosnovaesq
Runs Laya locally behind a TypeSafe-compatible API and provides a web UI for testing requests
laya-jev-ultrafast
leisc
A browser agent that uses Laya for typed action and element selection, with Jev as an optional backend
openjev
gillmoreno
Demonstrates local Laya email-triage and simulated trading-tick decisions
anima3
hulryung-uo
Uses a System One decision brain with Qwen log-probabilities and Laya triage for a game client
laya
robit-man
Provides a FastAPI service and web interface for testing Laya decisions and latency
XERON
PIXELZX0
Fine-tunes Laya decision models for multilingual classification, scoring, routing, and browser actions
Laya-vs-Jev
abcdmku
A side-by-side test bench compares the local Laya model with the hosted Jev API
layad
a1re1
A local HTTP daemon that keeps a Python Laya decision model resident for repeated inference
Nekomimi-Waifu-Seeker
CooLguNxDD
Uses Laya to guess anime and other fictional characters through typed decisions
laya-router
MiguelCarrascoB
A FastAPI router uses Laya typed decisions to route prompts by complexity
laya-blackjack
adambloebaum
Trains and evaluates a Laya-based blackjack policy with a simulator and probability dashboard
laya-mcp
EbiPenMan
Serves a persistent local Laya model through an MCP Streamable HTTP server
laya-server
phaser
A Jev-compatible HTTP server serves local Laya typed decisions on Apple silicon
local-laya
binbandit
Runs Laya-MLX locally with an HTTP API and a TypeScript client
laya-deploy
Pidbid
Deploys Laya as a local judgment backend for omp with an HTTP bridge, MCP tools, and installation scripts
laya-test
byteling
CLI and Flask demos show typed decisions from the Laya model
laya-server
SUSTYuxiao
A local inference wrapper and HTTP server for Laya with native and Jev-compatible prediction endpoints
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