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

A developer built a Simplified Chinese iPhone app, 他爱我吗, that runs a Core ML conversion of the laya-multilingual model entirely on-device to score candidate answers to relationship questions such as affection, no affection, and uncertainty. The app uses local SenseVoice transcription and template-based responses rather than a hosted chatbot, and keeps history on the device. The developer stresses that displayed scores are relative preferences among supplied options, not probabilities that a person is in love, and proposes reproducible evaluation directions instead of an accuracy claim.

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. 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. 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. There are useful questions to investigate before making stronger claims about this type of product: These are proposed evaluation directions, not completed experimental results. A reproducible set of cases would be more useful than an unsupported accuracy number. Laya's upstream project https://github.com/NandhaKishorM/laya 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 https://github.com/mizorewww/laya-coreml . The app itself is not being presented as an open-source project. The current interface is Simplified Chinese. The project website https://doesheloveme.tennote.site/en/ 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.