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wyat

wyat

Decisions, made locally.

wyat.io · wyat-1-800m · Documentation


wyat chooses between options your application defines. You provide a message and a set of candidates. A small local model returns the ID of one of them. The model was trained on French and English decisions. Nothing leaves your machine, and nothing runs until you act on the result.

The model is wyat-1 800M. It runs with PyTorch on CPU, CUDA or Apple MPS, or with MLX on Apple Silicon. Version 0.1.2 downloads its pinned release and verifies every file before loading.

Try it

No model required. The demo uses fixed scores to show the interface.

git clone https://github.com/teilomillet/wyat && cd wyat
uv run python examples/quickstart/main.py --demo
# Selected: cancel

Install

Python 3.12 or newer, with uv.

uv add wyat --extra inference   # PyTorch: CPU, CUDA or Apple MPS
uv add wyat --extra mlx         # MLX on Apple Silicon

Add --extra server to serve over HTTP. The core alone (uv add wyat) has no dependencies. Model weights are separate from the package. wyat.load() downloads and verifies wyat-1 800M on first use, then reuses the verified cache. Run uv run wyat download to fetch it ahead of time. Inference itself never uses the network.

On Apple Silicon, use the GPU: wyat.load(backend="mlx") with the mlx extra, or wyat.load(device="mps") with PyTorch. Both give the same scores as PyTorch CPU, which is several times slower there.

Use it

import wyat

model = wyat.load("teilomillet/wyat-1-800m")  # also the default for wyat.load()

decision = model.decide(wyat.Request(
    query="Choose the requested booking action.",
    context="Please cancel my booking.",
    candidates=[
        wyat.Candidate(id="create", text="Create a booking"),
        wyat.Candidate(id="cancel", text="Cancel the booking"),
    ],
))

decision.selected  # one of your IDs, such as "cancel"

Load once. Decide many times. The same request and result work in Python, JSONL, and HTTP:

uv run wyat decide teilomillet/wyat-1-800m < requests.jsonl > decisions.jsonl
uv run wyat serve  teilomillet/wyat-1-800m

Besides choosing an option, wyat rates on an ordered scale (Request.score) and answers yes or no with a probability (Request.noul).

Documentation

Quickstart Your first decision, step by step
Embedded demo A coding agent acting on wyat's choice
Python API Requests, results, batching, serving, evaluation
Workflows Routing, review, recovery
Explaining decisions Reading scores and owning policy
Use cases Choice, Score and Noul in short scripts
Expert use cases Triage, agents, RAG gates, calibration
Integrations LangChain, LangGraph, LlamaIndex, MCP, pandas
All documentation

Coding agents can start from llms.txt.

License

Code is licensed under Apache 2.0; see NOTICE. Model artifacts carry their own licenses. The 800M trained adapters and decision head are released for non-commercial use; its backbone and runtime use Apache 2.0. Contributions are welcome; see CONTRIBUTING.md.

Metadata

Release files for wyat 0.1.2

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Source distribution for wyat 0.1.2
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Table of built distributions (wheels) for wyat 0.1.2
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wyat-0.1.2-py3-none-any.whl Python 3 none any Details

Total release size: 669.1 kB

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