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CoreML: Model loading utilities
Hello, We find that models sometimes load very fast (<< 1 second) and sometimes encounter very long load times (>> 120 seconds). During such slow load times, the model is being compiled. We would greatly appreciate the ability to check cache validity via CoreML and determine that we are about to encounter long load times so that we can mitigate and provide a good user experience. A secondary issue: sometimes the cache is corrupted (typically .mpsgraphpackage yielding Metal cold asserts). This yields load failures and OS errors that persist between launches, and we have to manually nuke the cache (~/Library/..../my-app/...) for the CoreML assets. A CoreML API for clearing caches and hardening from asserts across the load paths would be appreciated
1
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174
Jun ’25
SwiftUI App Intent throws error when using requestDisambiguation with @Parameter property wrapper
I'm implementing an App Intent for my iOS app that helps users plan trip activities. It only works when run as a shortcut but not using voice through Siri. There are 2 issues: The ShortcutsTripEntity will only accept a voice input for a specific trip but not others. I'm stuck with a throwing error when trying to use requestDisambiguation() on the activity day @Parameter property. How do I rectify these issues. This is blocking me from completing a critical feature that lets users quickly plan activities through Siri and Shortcuts. Expected behavior for trip input: The intent should make Siri accept the spoken trip input from any of the options. Actual behavior for trip input: Siri only accepts the same trip when spoken but accepts any when selected by click/touch. Expected behavior for day input: Siri should accept the spoken selected option. Actual behavior for day input: Siri only accepts an input by click/touch but yet throws an error at runtime I'm happy to provide more code. But here's the relevant code: struct PlanActivityTestIntent: AppIntent { @Parameter(title: "Activity Day") var activityDay: ShortcutsItineraryDayEntity @Parameter( title: "Trip", description: "The trip to plan an activity for", default: ShortcutsTripEntity(id: UUID().uuidString, title: "Untitled trip"), requestValueDialog: "Which trip would you like to add an activity to?" ) var tripEntity: ShortcutsTripEntity @Parameter(title: "Activity Title", description: "The title of the activity", requestValueDialog: "What do you want to do or see?") var title: String @Parameter(title: "Activity Day", description: "Activity Day", default: ShortcutsItineraryDayEntity(itineraryDay: .init(itineraryId: UUID(), date: .now), timeZoneIdentifier: "UTC")) var activityDay: ShortcutsItineraryDayEntity func perform() async throws -> some ProvidesDialog { // ...other code... let tripsStore = TripsStore() // load trips and map them to entities try? await tripsStore.getTrips() let tripsAsEntities = tripsStore.trips.map { trip in let id = trip.id ?? UUID() let title = trip.title return ShortcutsTripEntity(id: id.uuidString, title: title, trip: trip) } // Ask user to select a trip. This line would doesn't accept a voice // answer. Why? let selectedTrip = try await $tripEntity.requestDisambiguation( among: tripsAsEntities, dialog: .init( full: "Which of the \(tripsAsEntities.count) trip would you like to add an activity to?", supporting: "Select a trip", systemImageName: "safari.fill" ) ) // This line throws an error let selectedDay = try await $activityDay.requestDisambiguation( among: daysAsEntities, dialog:"Which day would you like to plan an activity for?" ) } } Here are some related images that might help:
0
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311
Jul ’25
Regression in EnumeratedShaped support in recent MacOS release
Hi, unfortunately I am not able to verify this but I remember some time ago I was able to create CoreML models that had one (or more) inputs with an enumerated shape size, and one (or more) inputs with a static shape. This was some months ago. Since then I updated my MacOS to Sequoia 15.5, and when I try to execute MLModels with this setup I get the following error libc++abi: terminating due to uncaught exception of type CoreML::MLNeuralNetworkUtilities::AsymmetricalEnumeratedShapesException: A model doesn't allow input features with enumerated flexibility to have unequal number of enumerated shapes, but input feature global_write_indices has 1 enumerated shapes and input feature input_hidden_states has 3 enumerated shapes. It may make sense (but not really though) to verify that for inputs with a flexible enumerated shape they all have the same number of possible shapes is the same, but this should not impede the possibility of also having static shape inputs with a single shape defined alongside the flexible shape inputs.
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295
May ’25
FoundationModels guardrailViolation on Beta 3
Hello everybody! I’m encountering an unexpected guardrailViolation error when using Foundation Models on macOS Beta 3 (Tahoe) with an Apple M2 Pro chip. This issue didn’t occur on Beta 1 or Beta 2 using the same codebase. Reproduction Context I’m developing an app that leverages Foundation Models for structured generation, paired with a local database tool. After upgrading to macOS Beta 3, I started receiving this error consistently, despite no changes in the generation logic. To isolate the issue, I opened the official WWDC sample project from the Adding intelligent app features with generative models and the same guardrailViolation error appeared without any modifications. Simplified Working Example I attempted to narrow down the issue by starting with a minimal prompt structure. This basic case works fine: import Foundation import Playgrounds import FoundationModels @Generable struct GeneableLandmark { @Guide(description: "Name of the landmark to visit") var name: String } final class LandmarkSuggestionGenerator { var landmarkSuggestion: GeneableLandmark.PartiallyGenerated? private var session: LanguageModelSession init(){ self.session = LanguageModelSession( instructions: Instructions { """ generate a list of landmarks to visit """ } ) } func createLandmarkSuggestion(location: String) async throws { let stream = session.streamResponse( generating: GeneableLandmark.self, options: GenerationOptions(sampling: .greedy), includeSchemaInPrompt: false ) { """ Generate a list of landmarks to viist in \(location) """ } for try await partialResponse in stream { landmarkSuggestion = partialResponse } } } #Playground { let generator = LandmarkSuggestionGenerator() Task { do { try await generator.createLandmarkSuggestion(location: "New york") if let suggestion = generator.landmarkSuggestion { print("Suggested landmark: \(suggestion)") } else { print("No suggestion generated.") } } catch { print("Error generating landmark suggestion: \(error)") } } } But as soon as I use the Sample ItineraryPlanner: #Playground { // Example landmark for demonstration let exampleLandmark = Landmark( id: 1, name: "San Francisco", continent: "North America", description: "A vibrant city by the bay known for the Golden Gate Bridge.", shortDescription: "Iconic Californian city.", latitude: 37.7749, longitude: -122.4194, span: 0.2, placeID: nil ) let planner = ItineraryPlanner(landmark: exampleLandmark) Task { do { try await planner.suggestItinerary(dayCount: 3) if let itinerary = planner.itinerary { print("Suggested itinerary: \(itinerary)") } else { print("No itinerary generated.") } } catch { print("Error generating itinerary: \(error)") } } } The error pops up: Multiline Error generating itinerary: guardrailViolation(FoundationModels.LanguageModelSession. >GenerationError.Context(debug Description: "May contain sensitive or unsafe content", >underlyingErrors: [FoundationModels. LanguageModelSession. Gene >rationError.guardrailViolation(FoundationMo dels. >LanguageModelSession.GenerationError.C ontext (debugDescription: >"May contain unsafe content", underlyingErrors: []))])) Based on my tests: The error may not be tied to structure complexity (since more nested structures work) The issue may stem from the tools or prompt content used inside the ItineraryPlanner The guardrail sensitivity may have increased or changed in Beta 3, affecting models that worked in earlier betas Thank you in advance for your help. Let me know if more details or reproducible code samples are needed - I’m happy to provide them. Best, Sasha Morozov
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421
Jul ’25
FoundationModels Content Sanitizer Blocking Legitimate Text Processing
I'm developing a macOS application using the FoundationModels framework (LanguageModelSession) and encountering issues with the content sanitizer blocking legitimate text input. ** Issue Description:** The content sanitizer is flagging text strings that contain certain substrings, even when they represent legitimate technical content. For example: F_SEEL_SEX1S.wav (sE Electronics SEX1S microphone model) Technical product identifiers Serial numbers and version codes ** Broader Concern:** The content sanitizer appears to be applying restrictions that seem inappropriate for user-owned content. Even if a filename were something like "human sex.wav", users should have the right to process their own legitimate files on their own devices without content filtering interference. ** Error Messages:** SensitiveContentSettings: Sanitizer model found unsafe content in value FoundationModels.LanguageModelSession.GenerationError error 2 ** Questions:** Is there a way to disable content sanitization for processing user-owned content? 2. What's the recommended approach for applications that need to handle arbitrary user text? 3. Are there APIs to process personal content without filtering restrictions? ** Environment:** macOS 26.0 FoundationModels framework LanguageModelSession Any guidance would be appreciated.
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420
Jun ’25
Selecting an output language with Foundation Models
When using Foundation Models, is it possible to ask the model to produce output in a specific language, apart from giving an instruction like "Provide answers in ." ? (I tried that and it kind of worked, but it seems fragile.) I haven't noticed an API to do so and have a use-case where the output should be in a user-selectable language that is not the current system language.
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584
Jul ’25
Can I give additional context to Foundation Models?
I'm interested in using Foundation Models to act as an AI support agent for our extensive in-app documentation. We have many pages of in-app documents, which the user can currently search, but it would be great to use Foundation Models to let the user get answers to arbitrary questions. Is this possible with the current version of Foundation Models? It seems like the way to add new context to the model is with the instructions parameter on LanguageModelSession. As I understand it, the combined instructions and prompt need to consume less than 4096 tokens. That definitely wouldn't be enough for the amount of documentation I want the agent to be able to refer to. Is there another way of doing this, maybe as a series of recursive queries? If there is a solution based on multiple queries, should I expect this to be fast enough for interactive use?
4
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377
Jul ’25
FoundationModels not supported on Mac Catalyst?
I'd love to add a feature based on FoundationModels to the Mac Catalyst version of my iOS app. Unfortunately I get an error when importing FoundationModels: No such module 'FoundationModels'. Documentation says Mac Catalyst is supported: https://developer.apple.com/documentation/foundationmodels I can create iOS builds using the FoundationModels framework without issues. Hope this will be fixed soon! Config: Xcode 26.0 beta (17A5241e) macOS 26.0 Beta (25A5279m) 15-inch, M4, 2025 MacBook Air
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330
Jun ’25
get error with xcode beta3 :decodingFailure(FoundationModels.LanguageModelSession.GenerationError.Context
@Generable enum Breakfast { case waffles case pancakes case bagels case eggs } do { let session = LanguageModelSession() let userInput = "I want something sweet." let prompt = "Pick the ideal breakfast for request: (userInput)" let response = try await session.respond(to: prompt,generating: Breakfast.self) print(response.content) } catch let error { print(error) } i want to test the @Generable demo but get error with below:decodingFailure(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Failed to convert text into into GeneratedContent\nText: waffles", underlyingErrors: [Swift.DecodingError.dataCorrupted(Swift.DecodingError.Context(codingPath: [], debugDescription: "The given data was not valid JSON.", underlyingError: Optional(Error Domain=NSCocoaErrorDomain Code=3840 "Unexpected character 'w' around line 1, column 1." UserInfo={NSJSONSerializationErrorIndex=0, NSDebugDescription=Unexpected character 'w' around line 1, column 1.})))]))
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138
Jul ’25
Swipe-to-Type Broken in iOS 26 Beta 1 & 2 Siri Typing Mode
I’ve been testing silent Siri engagement via typing on iOS 18 and also on iOS 26 beta 1 and beta 2. While normal typing works perfectly in type-to-Siri mode, I’ve noticed that swipe-to-type gestures don’t work within Siri’s input field. Interestingly, you still feel the usual haptic feedback associated with swipe typing, but no text appears in the Siri text box. Swipe-to-type continues to work flawlessly in other apps like Messages and Notes, so this seems to be an issue specific to Siri’s typing input handler in these betas. Hopefully, it will be fixed in the next release because swipe typing is essential to my silent Siri workflow.
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243
Jun ’25
Foundation Models Adapter Training Toolkit v0.2.0 LoRA Adapter Incompatible with macOS 26 Beta 4 Base Model
Context I trained a LoRA adapter for Apple’s on-device language model using the Foundation Models Adapter Training Toolkit v0.2.0 on macOS 26 beta 4. Although training completes successfully, loading the resulting .fmadapter package fails with: Adapter is not compatible with the current system base model. What I’ve Observed, Hard-coded Signature: In export/constants.py, the toolkit sets, BASE_SIGNATURE = "9799725ff8e851184037110b422d891ad3b92ec1" Metadata Injection: The export_fmadapter.py script writes this value into the adapter’s metadata: self_dict[MetadataKeys.BASE_SIGNATURE] = BASE_SIGNATURE Compatibility Check: At runtime, the Foundation Models framework compares the adapter’s baseModelSignature against the OS’s system model signature, and reports compatibleAdapterNotFound if they don’t match—without revealing the expected signature. Questions Signature Generation - What exactly does the toolkit hash to derive BASE_SIGNATURE? Is it a straight SHA-1 of base-model.pt, or is there an additional transformation? Recomputing for Beta 4 - Is there a way to locally compute the correct signature for the macOS 26 beta 4 system model? Toolkit Updates - Will Apple release Adapter Training Toolkit v0.3.0 with an updated BASE_SIGNATURE for beta 4, or is there an alternative workaround to generate it myself? Any guidance on how the Foundation Models framework derives and verifies the base model signature—or how to regenerate it for beta 4—would be greatly appreciated.
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Aug ’25
A specific mlmodelc model runs on iPhone 15, but not on iPhone 16
As we described on the title, the model that I have built completely works on iPhone 15 / A16 Bionic, on the other hand it does not run on iPhone 16 / A18 chip with the following error message. E5RT encountered an STL exception. msg = MILCompilerForANE error: failed to compile ANE model using ANEF. Error=_ANECompiler : ANECCompile() FAILED. E5RT: MILCompilerForANE error: failed to compile ANE model using ANEF. Error=_ANECompiler : ANECCompile() FAILED (11) It consumes 1.5 ~ 1.6 GB RAM on the loading the model, then the consumption is decreased to less than 100MB on the both of iPhone 15 and 16. After that, only on iPhone 16, the above error is shown on the Xcode log, the memory consumption is surged to 5 to 6GB, and the system kills the app. It works well only on iPhone 15. This model is built with the Core ML tools. Until now, I have tried the target iOS 16 to 18 and the compute units of CPU_AND_NE and ALL. But any ways have not solved this issue. Eventually, what kindof fix should I do? minimum_deployment_target = ct.target.iOS18 compute_units = ct.ComputeUnit.ALL compute_precision = ct.precision.FLOAT16
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May ’25
Apple's Illusion of Thinking paper and Path to Real AI Reasoning
Hey everyone I'm Manish Mehta, field CTO at Centific. I recently read Apple's white paper, The Illusion of Thinking and it got me thinking about the current state of AI reasoning. Who here has read it? The paper highlights how LLMs often rely on pattern recognition rather than genuine understanding. When faced with complex tasks, their performance can degrade significantly. I was just thinking that to move beyond this problem, we need to explore approaches that combines Deeper Reasoning Architectures for true cognitive capability with Deep Human Partnership to guide AI toward better judgment and understanding. The first part means fundamentally rewiring AI to reason. This involves advancing deeper architectures like World Models, which can build internal simulations to understand real-world scenarios , and Neurosymbolic systems, which combines neural networks with symbolic reasoning for deeper self-verification. Additionally, we need to look at deep human partnership and scalable oversight. An AI cannot learn certain things from data alone, it lacks the real-world judgment an AI will never have. Among other things, deep domain expert human partners are needed to instill this wisdom , validate the AI's entire reasoning process , build its ethical guardrails , and act as skilled adversaries to find hidden flaws before they can cause harm. What do you all think? Is this focus on a deeper partnership between advanced AI reasoning and deep human judgment the right path forward? Agree? Disagree? Thanks
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300
Jul ’25
App Shortcuts Limit (10 per app) — Can This Be Increased?
Hi Apple team, When using AppShortcutsProvider, I hit the hard limit: Each app may have at most 10 App Shortcuts. This feels limiting for apps that offer multiple workflows and would benefit from deeper Siri integration. Could this cap be raised — ideally to 30 — to support broader use of AppIntents, enhance Siri automation, and unlock more system-level capabilities? AppShortcuts are a fantastic tool. Increasing the limit would make them even more powerful. Thanks!
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221
Jun ’25
Embedding model missing once transferred to Xcode
I've created a "Transfer Learning BERT Embeddings" model with the default "Latin" language family and "Automatic" Language setting. This model performs exceptionally well against the test data set and functions as expected when I preview it in Create ML. However, when I add it to the Xcode project of the application to which I am deploying it, I am getting runtime errors that suggest it can't find the embedding resources: Failed to locate assets for 'mul_Latn' - '5C45D94E-BAB4-4927-94B6-8B5745C46289' embedding model Note, I am adding the model to the app project the same way that I added an earlier "Maximum Entropy" model. That model had no runtime issues. So it seems there is an issue getting hold of the embeddings at runtime. For now, "runtime" means in the Simulator. I intend to deploy my application to iOS devices once GM 26 is released (the app also uses AFM). I'm developing on Tahoe 26 beta, running on iOS 26 beta, using Xcode 26 beta. Is this a known/expected issue? Are the embeddings expected to be a resource in the model? Is there a workaround? I did try opening the model in Xcode and saving it as an mlpackage, then adding that to my app project, but that also didn't resolve the issue.
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547
Sep ’25
Guardrail configuration options?
Is anything configurable for LanguageModelSession.Guardrails besides the default? I'm prototyping a camping app, and it's constantly slamming into guardrail errors when I use the new foundation model interface. Any subjects relating to fishing, survival, etc. won't generate. For example the prompt "How can I kill deer ticks using a clothing treatment?" returns a generation error. The results that I get are great when it works, but so far the local model sessions are extremely unreliable.
2
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267
Jul ’25
CoreML: Model loading utilities
Hello, We find that models sometimes load very fast (<< 1 second) and sometimes encounter very long load times (>> 120 seconds). During such slow load times, the model is being compiled. We would greatly appreciate the ability to check cache validity via CoreML and determine that we are about to encounter long load times so that we can mitigate and provide a good user experience. A secondary issue: sometimes the cache is corrupted (typically .mpsgraphpackage yielding Metal cold asserts). This yields load failures and OS errors that persist between launches, and we have to manually nuke the cache (~/Library/..../my-app/...) for the CoreML assets. A CoreML API for clearing caches and hardening from asserts across the load paths would be appreciated
Replies
1
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0
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174
Activity
Jun ’25
SwiftUI App Intent throws error when using requestDisambiguation with @Parameter property wrapper
I'm implementing an App Intent for my iOS app that helps users plan trip activities. It only works when run as a shortcut but not using voice through Siri. There are 2 issues: The ShortcutsTripEntity will only accept a voice input for a specific trip but not others. I'm stuck with a throwing error when trying to use requestDisambiguation() on the activity day @Parameter property. How do I rectify these issues. This is blocking me from completing a critical feature that lets users quickly plan activities through Siri and Shortcuts. Expected behavior for trip input: The intent should make Siri accept the spoken trip input from any of the options. Actual behavior for trip input: Siri only accepts the same trip when spoken but accepts any when selected by click/touch. Expected behavior for day input: Siri should accept the spoken selected option. Actual behavior for day input: Siri only accepts an input by click/touch but yet throws an error at runtime I'm happy to provide more code. But here's the relevant code: struct PlanActivityTestIntent: AppIntent { @Parameter(title: "Activity Day") var activityDay: ShortcutsItineraryDayEntity @Parameter( title: "Trip", description: "The trip to plan an activity for", default: ShortcutsTripEntity(id: UUID().uuidString, title: "Untitled trip"), requestValueDialog: "Which trip would you like to add an activity to?" ) var tripEntity: ShortcutsTripEntity @Parameter(title: "Activity Title", description: "The title of the activity", requestValueDialog: "What do you want to do or see?") var title: String @Parameter(title: "Activity Day", description: "Activity Day", default: ShortcutsItineraryDayEntity(itineraryDay: .init(itineraryId: UUID(), date: .now), timeZoneIdentifier: "UTC")) var activityDay: ShortcutsItineraryDayEntity func perform() async throws -> some ProvidesDialog { // ...other code... let tripsStore = TripsStore() // load trips and map them to entities try? await tripsStore.getTrips() let tripsAsEntities = tripsStore.trips.map { trip in let id = trip.id ?? UUID() let title = trip.title return ShortcutsTripEntity(id: id.uuidString, title: title, trip: trip) } // Ask user to select a trip. This line would doesn't accept a voice // answer. Why? let selectedTrip = try await $tripEntity.requestDisambiguation( among: tripsAsEntities, dialog: .init( full: "Which of the \(tripsAsEntities.count) trip would you like to add an activity to?", supporting: "Select a trip", systemImageName: "safari.fill" ) ) // This line throws an error let selectedDay = try await $activityDay.requestDisambiguation( among: daysAsEntities, dialog:"Which day would you like to plan an activity for?" ) } } Here are some related images that might help:
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0
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311
Activity
Jul ’25
Regression in EnumeratedShaped support in recent MacOS release
Hi, unfortunately I am not able to verify this but I remember some time ago I was able to create CoreML models that had one (or more) inputs with an enumerated shape size, and one (or more) inputs with a static shape. This was some months ago. Since then I updated my MacOS to Sequoia 15.5, and when I try to execute MLModels with this setup I get the following error libc++abi: terminating due to uncaught exception of type CoreML::MLNeuralNetworkUtilities::AsymmetricalEnumeratedShapesException: A model doesn't allow input features with enumerated flexibility to have unequal number of enumerated shapes, but input feature global_write_indices has 1 enumerated shapes and input feature input_hidden_states has 3 enumerated shapes. It may make sense (but not really though) to verify that for inputs with a flexible enumerated shape they all have the same number of possible shapes is the same, but this should not impede the possibility of also having static shape inputs with a single shape defined alongside the flexible shape inputs.
Replies
6
Boosts
1
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295
Activity
May ’25
FoundationModels guardrailViolation on Beta 3
Hello everybody! I’m encountering an unexpected guardrailViolation error when using Foundation Models on macOS Beta 3 (Tahoe) with an Apple M2 Pro chip. This issue didn’t occur on Beta 1 or Beta 2 using the same codebase. Reproduction Context I’m developing an app that leverages Foundation Models for structured generation, paired with a local database tool. After upgrading to macOS Beta 3, I started receiving this error consistently, despite no changes in the generation logic. To isolate the issue, I opened the official WWDC sample project from the Adding intelligent app features with generative models and the same guardrailViolation error appeared without any modifications. Simplified Working Example I attempted to narrow down the issue by starting with a minimal prompt structure. This basic case works fine: import Foundation import Playgrounds import FoundationModels @Generable struct GeneableLandmark { @Guide(description: "Name of the landmark to visit") var name: String } final class LandmarkSuggestionGenerator { var landmarkSuggestion: GeneableLandmark.PartiallyGenerated? private var session: LanguageModelSession init(){ self.session = LanguageModelSession( instructions: Instructions { """ generate a list of landmarks to visit """ } ) } func createLandmarkSuggestion(location: String) async throws { let stream = session.streamResponse( generating: GeneableLandmark.self, options: GenerationOptions(sampling: .greedy), includeSchemaInPrompt: false ) { """ Generate a list of landmarks to viist in \(location) """ } for try await partialResponse in stream { landmarkSuggestion = partialResponse } } } #Playground { let generator = LandmarkSuggestionGenerator() Task { do { try await generator.createLandmarkSuggestion(location: "New york") if let suggestion = generator.landmarkSuggestion { print("Suggested landmark: \(suggestion)") } else { print("No suggestion generated.") } } catch { print("Error generating landmark suggestion: \(error)") } } } But as soon as I use the Sample ItineraryPlanner: #Playground { // Example landmark for demonstration let exampleLandmark = Landmark( id: 1, name: "San Francisco", continent: "North America", description: "A vibrant city by the bay known for the Golden Gate Bridge.", shortDescription: "Iconic Californian city.", latitude: 37.7749, longitude: -122.4194, span: 0.2, placeID: nil ) let planner = ItineraryPlanner(landmark: exampleLandmark) Task { do { try await planner.suggestItinerary(dayCount: 3) if let itinerary = planner.itinerary { print("Suggested itinerary: \(itinerary)") } else { print("No itinerary generated.") } } catch { print("Error generating itinerary: \(error)") } } } The error pops up: Multiline Error generating itinerary: guardrailViolation(FoundationModels.LanguageModelSession. >GenerationError.Context(debug Description: "May contain sensitive or unsafe content", >underlyingErrors: [FoundationModels. LanguageModelSession. Gene >rationError.guardrailViolation(FoundationMo dels. >LanguageModelSession.GenerationError.C ontext (debugDescription: >"May contain unsafe content", underlyingErrors: []))])) Based on my tests: The error may not be tied to structure complexity (since more nested structures work) The issue may stem from the tools or prompt content used inside the ItineraryPlanner The guardrail sensitivity may have increased or changed in Beta 3, affecting models that worked in earlier betas Thank you in advance for your help. Let me know if more details or reproducible code samples are needed - I’m happy to provide them. Best, Sasha Morozov
Replies
2
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1
Views
421
Activity
Jul ’25
FoundationModels Content Sanitizer Blocking Legitimate Text Processing
I'm developing a macOS application using the FoundationModels framework (LanguageModelSession) and encountering issues with the content sanitizer blocking legitimate text input. ** Issue Description:** The content sanitizer is flagging text strings that contain certain substrings, even when they represent legitimate technical content. For example: F_SEEL_SEX1S.wav (sE Electronics SEX1S microphone model) Technical product identifiers Serial numbers and version codes ** Broader Concern:** The content sanitizer appears to be applying restrictions that seem inappropriate for user-owned content. Even if a filename were something like "human sex.wav", users should have the right to process their own legitimate files on their own devices without content filtering interference. ** Error Messages:** SensitiveContentSettings: Sanitizer model found unsafe content in value FoundationModels.LanguageModelSession.GenerationError error 2 ** Questions:** Is there a way to disable content sanitization for processing user-owned content? 2. What's the recommended approach for applications that need to handle arbitrary user text? 3. Are there APIs to process personal content without filtering restrictions? ** Environment:** macOS 26.0 FoundationModels framework LanguageModelSession Any guidance would be appreciated.
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1
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420
Activity
Jun ’25
Selecting an output language with Foundation Models
When using Foundation Models, is it possible to ask the model to produce output in a specific language, apart from giving an instruction like "Provide answers in ." ? (I tried that and it kind of worked, but it seems fragile.) I haven't noticed an API to do so and have a use-case where the output should be in a user-selectable language that is not the current system language.
Replies
3
Boosts
1
Views
584
Activity
Jul ’25
Can I give additional context to Foundation Models?
I'm interested in using Foundation Models to act as an AI support agent for our extensive in-app documentation. We have many pages of in-app documents, which the user can currently search, but it would be great to use Foundation Models to let the user get answers to arbitrary questions. Is this possible with the current version of Foundation Models? It seems like the way to add new context to the model is with the instructions parameter on LanguageModelSession. As I understand it, the combined instructions and prompt need to consume less than 4096 tokens. That definitely wouldn't be enough for the amount of documentation I want the agent to be able to refer to. Is there another way of doing this, maybe as a series of recursive queries? If there is a solution based on multiple queries, should I expect this to be fast enough for interactive use?
Replies
4
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0
Views
377
Activity
Jul ’25
FoundationModels not supported on Mac Catalyst?
I'd love to add a feature based on FoundationModels to the Mac Catalyst version of my iOS app. Unfortunately I get an error when importing FoundationModels: No such module 'FoundationModels'. Documentation says Mac Catalyst is supported: https://developer.apple.com/documentation/foundationmodels I can create iOS builds using the FoundationModels framework without issues. Hope this will be fixed soon! Config: Xcode 26.0 beta (17A5241e) macOS 26.0 Beta (25A5279m) 15-inch, M4, 2025 MacBook Air
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2
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330
Activity
Jun ’25
Asking about computers model always refer to apple.com?
Here's the result: Very weird.
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5
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190
Activity
Jul ’25
Does Apple's new foundation models include a Vision API for accessing on-device LLM capabilities?
I couldn't find information about this in the documentation. Could someone clarify if this API is available and how to access it?
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2
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233
Activity
Jun ’25
get error with xcode beta3 :decodingFailure(FoundationModels.LanguageModelSession.GenerationError.Context
@Generable enum Breakfast { case waffles case pancakes case bagels case eggs } do { let session = LanguageModelSession() let userInput = "I want something sweet." let prompt = "Pick the ideal breakfast for request: (userInput)" let response = try await session.respond(to: prompt,generating: Breakfast.self) print(response.content) } catch let error { print(error) } i want to test the @Generable demo but get error with below:decodingFailure(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Failed to convert text into into GeneratedContent\nText: waffles", underlyingErrors: [Swift.DecodingError.dataCorrupted(Swift.DecodingError.Context(codingPath: [], debugDescription: "The given data was not valid JSON.", underlyingError: Optional(Error Domain=NSCocoaErrorDomain Code=3840 "Unexpected character 'w' around line 1, column 1." UserInfo={NSJSONSerializationErrorIndex=0, NSDebugDescription=Unexpected character 'w' around line 1, column 1.})))]))
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1
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138
Activity
Jul ’25
Swipe-to-Type Broken in iOS 26 Beta 1 & 2 Siri Typing Mode
I’ve been testing silent Siri engagement via typing on iOS 18 and also on iOS 26 beta 1 and beta 2. While normal typing works perfectly in type-to-Siri mode, I’ve noticed that swipe-to-type gestures don’t work within Siri’s input field. Interestingly, you still feel the usual haptic feedback associated with swipe typing, but no text appears in the Siri text box. Swipe-to-type continues to work flawlessly in other apps like Messages and Notes, so this seems to be an issue specific to Siri’s typing input handler in these betas. Hopefully, it will be fixed in the next release because swipe typing is essential to my silent Siri workflow.
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243
Activity
Jun ’25
Foundation Models Adapter Training Toolkit v0.2.0 LoRA Adapter Incompatible with macOS 26 Beta 4 Base Model
Context I trained a LoRA adapter for Apple’s on-device language model using the Foundation Models Adapter Training Toolkit v0.2.0 on macOS 26 beta 4. Although training completes successfully, loading the resulting .fmadapter package fails with: Adapter is not compatible with the current system base model. What I’ve Observed, Hard-coded Signature: In export/constants.py, the toolkit sets, BASE_SIGNATURE = "9799725ff8e851184037110b422d891ad3b92ec1" Metadata Injection: The export_fmadapter.py script writes this value into the adapter’s metadata: self_dict[MetadataKeys.BASE_SIGNATURE] = BASE_SIGNATURE Compatibility Check: At runtime, the Foundation Models framework compares the adapter’s baseModelSignature against the OS’s system model signature, and reports compatibleAdapterNotFound if they don’t match—without revealing the expected signature. Questions Signature Generation - What exactly does the toolkit hash to derive BASE_SIGNATURE? Is it a straight SHA-1 of base-model.pt, or is there an additional transformation? Recomputing for Beta 4 - Is there a way to locally compute the correct signature for the macOS 26 beta 4 system model? Toolkit Updates - Will Apple release Adapter Training Toolkit v0.3.0 with an updated BASE_SIGNATURE for beta 4, or is there an alternative workaround to generate it myself? Any guidance on how the Foundation Models framework derives and verifies the base model signature—or how to regenerate it for beta 4—would be greatly appreciated.
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12
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667
Activity
Aug ’25
A specific mlmodelc model runs on iPhone 15, but not on iPhone 16
As we described on the title, the model that I have built completely works on iPhone 15 / A16 Bionic, on the other hand it does not run on iPhone 16 / A18 chip with the following error message. E5RT encountered an STL exception. msg = MILCompilerForANE error: failed to compile ANE model using ANEF. Error=_ANECompiler : ANECCompile() FAILED. E5RT: MILCompilerForANE error: failed to compile ANE model using ANEF. Error=_ANECompiler : ANECCompile() FAILED (11) It consumes 1.5 ~ 1.6 GB RAM on the loading the model, then the consumption is decreased to less than 100MB on the both of iPhone 15 and 16. After that, only on iPhone 16, the above error is shown on the Xcode log, the memory consumption is surged to 5 to 6GB, and the system kills the app. It works well only on iPhone 15. This model is built with the Core ML tools. Until now, I have tried the target iOS 16 to 18 and the compute units of CPU_AND_NE and ALL. But any ways have not solved this issue. Eventually, what kindof fix should I do? minimum_deployment_target = ct.target.iOS18 compute_units = ct.ComputeUnit.ALL compute_precision = ct.precision.FLOAT16
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2
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233
Activity
May ’25
The answer that goes on forever
Encountered a few times when the answer get "stuck" (I am now at beta 6). This is an example.
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261
Activity
Aug ’25
Apple's Illusion of Thinking paper and Path to Real AI Reasoning
Hey everyone I'm Manish Mehta, field CTO at Centific. I recently read Apple's white paper, The Illusion of Thinking and it got me thinking about the current state of AI reasoning. Who here has read it? The paper highlights how LLMs often rely on pattern recognition rather than genuine understanding. When faced with complex tasks, their performance can degrade significantly. I was just thinking that to move beyond this problem, we need to explore approaches that combines Deeper Reasoning Architectures for true cognitive capability with Deep Human Partnership to guide AI toward better judgment and understanding. The first part means fundamentally rewiring AI to reason. This involves advancing deeper architectures like World Models, which can build internal simulations to understand real-world scenarios , and Neurosymbolic systems, which combines neural networks with symbolic reasoning for deeper self-verification. Additionally, we need to look at deep human partnership and scalable oversight. An AI cannot learn certain things from data alone, it lacks the real-world judgment an AI will never have. Among other things, deep domain expert human partners are needed to instill this wisdom , validate the AI's entire reasoning process , build its ethical guardrails , and act as skilled adversaries to find hidden flaws before they can cause harm. What do you all think? Is this focus on a deeper partnership between advanced AI reasoning and deep human judgment the right path forward? Agree? Disagree? Thanks
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300
Activity
Jul ’25
Documentation Deleted?
Was just wondering why the foundation model documentation is no longer available, thanks! https://developer.apple.com/documentation/FoundationModels
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273
Activity
Aug ’25
App Shortcuts Limit (10 per app) — Can This Be Increased?
Hi Apple team, When using AppShortcutsProvider, I hit the hard limit: Each app may have at most 10 App Shortcuts. This feels limiting for apps that offer multiple workflows and would benefit from deeper Siri integration. Could this cap be raised — ideally to 30 — to support broader use of AppIntents, enhance Siri automation, and unlock more system-level capabilities? AppShortcuts are a fantastic tool. Increasing the limit would make them even more powerful. Thanks!
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221
Activity
Jun ’25
Embedding model missing once transferred to Xcode
I've created a "Transfer Learning BERT Embeddings" model with the default "Latin" language family and "Automatic" Language setting. This model performs exceptionally well against the test data set and functions as expected when I preview it in Create ML. However, when I add it to the Xcode project of the application to which I am deploying it, I am getting runtime errors that suggest it can't find the embedding resources: Failed to locate assets for 'mul_Latn' - '5C45D94E-BAB4-4927-94B6-8B5745C46289' embedding model Note, I am adding the model to the app project the same way that I added an earlier "Maximum Entropy" model. That model had no runtime issues. So it seems there is an issue getting hold of the embeddings at runtime. For now, "runtime" means in the Simulator. I intend to deploy my application to iOS devices once GM 26 is released (the app also uses AFM). I'm developing on Tahoe 26 beta, running on iOS 26 beta, using Xcode 26 beta. Is this a known/expected issue? Are the embeddings expected to be a resource in the model? Is there a workaround? I did try opening the model in Xcode and saving it as an mlpackage, then adding that to my app project, but that also didn't resolve the issue.
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1
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547
Activity
Sep ’25
Guardrail configuration options?
Is anything configurable for LanguageModelSession.Guardrails besides the default? I'm prototyping a camping app, and it's constantly slamming into guardrail errors when I use the new foundation model interface. Any subjects relating to fishing, survival, etc. won't generate. For example the prompt "How can I kill deer ticks using a clothing treatment?" returns a generation error. The results that I get are great when it works, but so far the local model sessions are extremely unreliable.
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2
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267
Activity
Jul ’25