Bringing Laya onto an iPhone: a local decision-model experiment

yang9527 — Sun, 27 Sep 2026 11:28:34 +0000

Disclosure: I am the maker of 他爱我吗. This article was prepared with AI assistance from the project's implementation notes.

A question such as ‘Does he like me?’ looks simple in an interface. It is much harder to decide what an answer should mean. A model cannot see the other person's thoughts, and an attractive percentage does not change that.

I built a Chinese-language iPhone app to explore a narrower interaction: describe a situation, compare candidate answers, and leave room for uncertainty. Here is the architecture and the product boundary behind that experiment.

A decision model instead of a cloud conversation

The app uses a Core ML conversion of laya-multilingual to compare supplied answer options for the question and context. For a relationship question, those options might be affection, no affection, and uncertainty. The wording needs to fit the actual question.

This is not an unrestricted chatbot generating long responses through a hosted language model. Short conclusions and suggestions use templates. Chinese speech transcription uses SenseVoice locally, and history remains on the device.

Chinese text or speech
        ↓
Local transcription, when needed
        ↓
Question + context + candidate answers
        ↓
Laya through Core ML
        ↓
Relative answer scores + template-based response

Keeping analysis on-device is useful when the input is personal. It also shifts responsibilities to the app: model packaging, storage, loading, and keeping the interface responsive become part of the mobile experience. I am not claiming a latency or battery benchmark here; those require measured device tests.

What the percentages do—and do not—mean

A displayed answer score is a relative preference among the options given to the model. It is not evidence that a person has a corresponding probability of being in love.

An uncertain result belongs in the interaction rather than being treated as an error. More context can help frame a question, but it still cannot establish another person's internal state. The interface should make that limit visible close to the result.

The image below is an actual Chinese-language result screen. It illustrates the interface, not a validated prediction about anyone.

Tests I would like to make more systematic

There are useful questions to investigate before making stronger claims about this type of product:

Does reversing candidate order change the preferred answer?
Does a neutral paraphrase of the same story change it substantially?
Do contradictory details lead to more uncertainty?
Do reassuring or negative words dominate otherwise equivalent context?
Does the UI remain responsive while models load and transcription runs?

These are proposed evaluation directions, not completed experimental results. A reproducible set of cases would be more useful than an unsupported accuracy number.

Where JEV and System One fit

Laya's upstream project describes a non-autoregressive System 1 decision engine and an optional Jev-compatible server interface at /v1/systemone. That is related technical context, not the architecture of this iOS app: the app uses local Laya inference and does not call the Jev API or run that server.

The conversion project is available at laya-coreml. The app itself is not being presented as an open-source project.

The current interface is Simplified Chinese. The project website shows the screens and limitations. If you are working on a local decision model, I would be interested in comparing evaluation approaches—especially how you prevent users from interpreting a relative score as certainty.

DEV Community: yang9527

Bringing Laya onto an iPhone: a local decision-model experiment

A decision model instead of a cloud conversation

What the percentages do—and do not—mean

Tests I would like to make more systematic

Where JEV and System One fit