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What the loop does
A voice follow-up loop separates understanding from speaking. A speech layer turns the user’s utterance into text; Foundation Models evaluates that text and returns a constrained choice; then the app decides what to say or do. This keeps the model’s role narrow and makes the interaction easier to validate.
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- Capture the user’s utterance and obtain a transcription through an appropriate speech layer.
- Send the text and relevant, compact context to a Foundation Models session.
- Receive a structured decision, such as
clarify,continue, orhandoff. - Let app logic select the follow-up wording, continue the workflow, or route the request.
Foundation Models does not define this app’s capture or speech pipeline. Apple’s framework sources establish language-model capabilities, not which Speech APIs or audio interaction behavior a particular app should use.
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Apple presents Foundation Models for language tasks including guided generation and tool calling. Its WWDC25 introduction describes the on-device model as suited to tasks such as summarization, extraction, and classification, while cautioning that it is not suitable for world knowledge or advanced reasoning. That makes a small routing decision a better fit than open-ended response writing for this pattern. See Apple’s WWDC25 Foundation Models session.
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With structured output, the app can validate the model’s choice before it affects the conversation. Free-form text is harder to treat as a reliable control signal: a sentence may be fluent without corresponding to a valid app state. Apple supports guided generation using Swift data structures; the particular decision schema below is an app design choice, not an Apple-prescribed format. See Apple’s Foundation Models documentation.
Define a small, typed decision
Model only the information the app needs to choose its next step. A useful conceptual result might contain a decision and, only when clarification is required, the missing field:
clarify: ask for a specific missing or ambiguous detail.continue: the available information is sufficient for the next app-defined step.handoff: route to a human, another workflow, or a deterministic fallback when the request is outside the supported path.
Keep the result narrow. For example, the model can identify that a destination is missing; the app—not the model—can choose the wording of “Where would you like to go?” and render it through the product’s normal voice interface. Validate that a clarification names a field the app recognizes, and reject combinations that do not make sense for the selected decision.
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Foundation Models supports app-defined tools that the model can invoke. Treat a tool as a constrained interface to an app-owned operation, with explicit inputs and effects—not as permission for generated text to trigger arbitrary behavior. Check the model’s proposed inputs, current app state, and any consequential action before proceeding. Tool calling is a framework capability; the validation and confirmation policy is implementation guidance.
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For a voice loop, the model can select a permitted route or request a clarification, while the app decides whether that route is currently available and what the user hears. This division makes it possible to keep network access, account changes, purchases, or other sensitive effects outside an unchecked model decision.
Sequence requests and manage context
Foundation Models sessions are asynchronous, and a LanguageModelSession handles one request at a time. Await each request before sending another through the same session, or deliberately manage separate sessions if the product needs concurrent work. Do not assume that overlapping requests on one session will be processed independently. Apple documents these session constraints in its LanguageModelSession reference.
The documented system-model context window is up to 4,096 tokens. Instructions, prompts, conversation turns, and generated output all count toward that limit. Keep the decision prompt and retained history compact; include only details needed for the next choice. If the interaction grows, the app can start a fresh session or provide a concise summary, depending on its product requirements. Plan for context overflow rather than assuming the full conversation can be retained indefinitely. See Apple’s generation documentation.
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The model should not be the only path through a voice interaction. Decide what the app will do if the on-device model is unavailable, a request fails, the output cannot be validated, or context cannot be handled. A safe fallback might ask the user to repeat or clarify, offer a fixed set of choices, or route to a supported non-model flow. The appropriate behavior depends on the task; Apple does not prescribe a fallback for this pattern.
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Also check whether the device supports Apple Intelligence before depending on access to Apple’s on-device models. The framework’s availability requirement is documented by Apple; the app should handle unsupported devices or unavailable model access as an expected product state, not as an unhandled exception. See Foundation Models documentation.
Keep the model’s remit bounded
Apple’s 2025 technical report describes an approximately 3-billion-parameter on-device model. That is a figure from the 2025 report, not a promise about every later system model or device configuration. More importantly for this design, Apple’s WWDC25 presentation frames the model around focused language tasks such as classification and extraction—not general world knowledge or advanced reasoning. Use the model to interpret the utterance within the app’s supported domain; use app rules or an appropriate external source for facts and decisions that require broader knowledge.
The result is a clear division of responsibility: speech infrastructure captures and transcribes; the model classifies the next conversational need; and application code validates, speaks, and acts. That boundary is the central design choice—not a claim that Foundation Models itself supplies a complete voice assistant.
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