Can access to SoundAnalysis (sound classifier built into next version of MacOS, iOS, WatchOS) be provided to my app running in the background on iPhone or Apple Watch? I want to monitor local sounds from Apple Watch and iPhones and take remote action for out of band data (ie. send alert to caregiver if coughing rate is too high, or if someone is knocking on the door for more than a minute, etc.)

Did something change on face detection / Vision Framework on iOS 15? Using VNDetectFaceLandmarksRequest and reading the VNFaceLandmarkRegion2D to detect eyes is not working on iOS 15 as it did before. I am running the exact same code on an iOS 14 and iOS 15 device and the coordinates are different as seen on the screenshot? Any Ideas?

in iOS 15, on stopSpeaking of AVSpeechSynthesizer, didFinish delegate method getting called instead of didCancel which is working fine in iOS 14 and below version.

I am working on the neural network classifier provided on the coremltools.readme.io in the updatable->neural network section(https://coremltools.readme.io/docs/updatable-neural-network-classifier-on-mnist-dataset). I am using the same code but I get an error saying that the coremltools.converters.keras.convert does not exist. But this I know can be coreml version issue. Right know I am using coremltools version 6.2. I converted this model to mlmodel with .convert only. It got converted successfully. But I face an error in the make_updatable function saying the loss layer must be softmax output. Even the coremlt package API reference there I found its because the layer name is softmaxND but it should be softmax. Now the problem is when I convert the model from Keras sequential model to coreml model. the layer name and type change. And the softmax changes to softmaxND. Does anyone faced this issue? if I execute this builder.inspect_layers(last=4) I get this output [Id: 32], Name: sequential/dense_1/Softmax (Type: softmaxND) Updatable: False Input blobs: ['sequential/dense_1/MatMul'] Output blobs: ['Identity'] [Id: 31], Name: sequential/dense_1/MatMul (Type: batchedMatmul) Updatable: False Input blobs: ['sequential/dense/Relu'] Output blobs: ['sequential/dense_1/MatMul'] [Id: 30], Name: sequential/dense/Relu (Type: activation) Updatable: False Input blobs: ['sequential/dense/MatMul'] Output blobs: ['sequential/dense/Relu'] In the make_updatable function when I execute builder.set_categorical_cross_entropy_loss(name='lossLayer', input='Identity') I get this error ValueError: Categorical Cross Entropy loss layer input (Identity) must be a softmax layer output.

Hi everyone, I might need some help with on-device recognition. It seems that the speech recognition task will discard whatever it has transcribed after a new sentence starts (or it believes it becomes a new sentence) during a single audio session, with requiresOnDeviceRecognition is set to true. This doesn't happen with requiresOnDeviceRecognition set to false. System environment: macOS 14 with Xcode 15, deploying to iOS 17 Thank you all!

Hello, I posted an issue on the coremltools GitHub about my Core ML models not performing as well on iOS 17 vs iOS 16 but I'm posting it here just in case. TL;DR The same model on the same device/chip performs far slower (doesn't use the Neural Engine) on iOS 17 compared to iOS 16. Longer description The following screenshots show the performance of the same model (a PyTorch computer vision model) on an iPhone SE 3rd gen and iPhone 13 Pro (both use the A15 Bionic). iOS 16 - iPhone SE 3rd Gen (A15 Bioinc) iOS 16 uses the ANE and results in fast prediction, load and compilation times. iOS 17 - iPhone 13 Pro (A15 Bionic) iOS 17 doesn't seem to use the ANE, thus the prediction, load and compilation times are all slower. Code To Reproduce The following is my code I'm using to export my PyTorch vision model (using coremltools). I've used the same code for the past few months with sensational results on iOS 16. # Convert to Core ML using the Unified Conversion API coreml_model = ct.convert( model=traced_model, inputs=[image_input], outputs=[ct.TensorType(name="output")], classifier_config=ct.ClassifierConfig(class_names), convert_to="neuralnetwork", # compute_precision=ct.precision.FLOAT16, compute_units=ct.ComputeUnit.ALL ) System environment: Xcode version: 15.0 coremltools version: 7.0.0 OS (e.g. MacOS version or Linux type): Linux Ubuntu 20.04 (for exporting), macOS 13.6 (for testing on Xcode) Any other relevant version information (e.g. PyTorch or TensorFlow version): PyTorch 2.0 Additional context This happens across "neuralnetwork" and "mlprogram" type models, neither use the ANE on iOS 17 but both use the ANE on iOS 16 If anyone has a similar experience, I'd love to hear more. Otherwise, if I'm doing something wrong for the exporting of models for iOS 17+, please let me know. Thank you!

When I add AppEnity to my model, I receive this error that is still repeated for each attribute in the model. The models are already marked for Widget Extension in Target Membership. I have already cleaned and restarted, nothing works. Will anyone know what I'm doing wrong? Unable to find matching source file for path "@_swiftmacro_21HabitWidgetsExtension0A05ModelfMm.swift" import SwiftData import AppIntents enum FrecuenciaCumplimiento: String, Codable { case diario case semanal case mensual } @Model final class Habit: AppEntity { @Attribute(.unique) var id: UUID var nombre: String var descripcion: String var icono: String var color: String var esHabitoPositivo: Bool var valorObjetivo: Double var unidadObjetivo: String var frecuenciaCumplimiento: FrecuenciaCumplimiento static var typeDisplayRepresentation: TypeDisplayRepresentation = "Hábito" static var defaultQuery = HabitQuery() var displayRepresentation: DisplayRepresentation { DisplayRepresentation(title: "\(nombre)") } static var allHabits: [Habit] = [ Habit(id: UUID(), nombre: "uno", descripcion: "", icono: "circle", color: "#BF0000", esHabitoPositivo: true, valorObjetivo: 1.0, unidadObjetivo: "", frecuenciaCumplimiento: .mensual), Habit(id: UUID(), nombre: "dos", descripcion: "", icono: "circle", color: "#BF0000", esHabitoPositivo: true, valorObjetivo: 1.0, unidadObjetivo: "", frecuenciaCumplimiento: .mensual) ] /* static func loadAllHabits() async throws { do { let modelContainer = try ModelContainer(for: Habit.self) let descriptor = FetchDescriptor<Habit>() allHabits = try await modelContainer.mainContext.fetch(descriptor) } catch { // Manejo de errores si es necesario print("Error al cargar hábitos: \(error)") throw error } } */ init(id: UUID = UUID(), nombre: String, descripcion: String, icono: String, color: String, esHabitoPositivo: Bool, valorObjetivo: Double, unidadObjetivo: String, frecuenciaCumplimiento: FrecuenciaCumplimiento) { self.id = id self.nombre = nombre self.descripcion = descripcion self.icono = icono self.color = color self.esHabitoPositivo = esHabitoPositivo self.valorObjetivo = valorObjetivo self.unidadObjetivo = unidadObjetivo self.frecuenciaCumplimiento = frecuenciaCumplimiento } @Relationship(deleteRule: .cascade) var habitRecords: [HabitRecord] = [] } struct HabitQuery: EntityQuery { func entities(for identifiers: [Habit.ID]) async throws -> [Habit] { //try await Habit.loadAllHabits() return Habit.allHabits.filter { identifiers.contains($0.id) } } func suggestedEntities() async throws -> [Habit] { //try await Habit.loadAllHabits() return Habit.allHabits// .filter { $0.isAvailable } } func defaultResult() async -> Habit? { try? await suggestedEntities().first } }

Hello! I've noticed that adding localizations for AppShortcuts triggers the following warnings in Xcode 15.3: warning: missing the definition of zh-Hans # variables.1.definitions warning: missing the definition of zh-Hans # variables.2.definitions This occurs with both legacy strings files and String Catalogs. Example project: https://github.com/gongzhang/AppShortcutsLocalizationWarningExample

i'm trying to create an NLModel within a MessageFilterExtension handler. The code works fine in the main app, but when I try to use it in the extension it fails to initialize. Just this doesn't even work and gets the error below. Single line that fails. SMS_Classifier is the class xcode generated for my model. This line works fine in the main app. let mlModel = try SMS_Classifier(configuration: MLModelConfiguration()).model Error Unable to locate Asset for contextual word embedding model for local en. MLModelAsset: load failed with error Error Domain=com.apple.CoreML Code=0 "initialization of text classifier model with model data failed" UserInfo={NSLocalizedDescription=initialization of text classifier model with model data failed} Any ideas?

Hi everyone ! I'm getting random crashes when I'm using the Speech Recognizer functionality in my app. This is an old bug (for 8 years on Apple Forums) and I will really appreciate if anyone from Apple will be able to find a fix for this crashes. Can anyone also help me please to understand what could I do to keep the Speech Recognizer functionality still available in my app, but to avoid this crashes (if there is any other native library available or a CocoaPod library). Here is my code and also the crash log for it. Code: func startRecording() { startStopRecordBtn.setImage(UIImage(#imageLiteral(resourceName: "microphone_off")), for: .normal) if UserDefaults.standard.bool(forKey: Constants.darkTheme) { commentTextView.textColor = .white } else { commentTextView.textColor = .black } commentTextView.isUserInteractionEnabled = false recordingLabel.text = Constants.recording if recognitionTask != nil { recognitionTask?.cancel() recognitionTask = nil } let audioSession = AVAudioSession.sharedInstance() do { try audioSession.setCategory(AVAudioSession.Category.record) try audioSession.setMode(AVAudioSession.Mode.measurement) try audioSession.setActive(true, options: .notifyOthersOnDeactivation) } catch { showAlertWithTitle(message: Constants.error) } recognitionRequest = SFSpeechAudioBufferRecognitionRequest() let inputNode = audioEngine.inputNode guard let recognitionRequest = recognitionRequest else { fatalError(Constants.error) } recognitionRequest.shouldReportPartialResults = true recognitionTask = speechRecognizer?.recognitionTask(with: recognitionRequest, resultHandler: { (result, error) in var isFinal = false if result != nil { self.commentTextView.text = result?.bestTranscription.formattedString isFinal = (result?.isFinal)! } if error != nil || isFinal { self.audioEngine.stop() inputNode.removeTap(onBus: 0) self.recognitionRequest = nil self.recognitionTask = nil self.startStopRecordBtn.isEnabled = true } }) let recordingFormat = inputNode.outputFormat(forBus: 0) inputNode.installTap(onBus: 0, bufferSize: 1024, format: recordingFormat) {[weak self] (buffer: AVAudioPCMBuffer, when: AVAudioTime) in // CRASH HERE self?.recognitionRequest?.append(buffer) } audioEngine.prepare() do { try audioEngine.start() } catch { showAlertWithTitle(message: Constants.error) } } Here is the crash log: Thanks for very much for reading this !

Does the new Image Playground API allow programmatically generating images? Can the app generate and use them without the API's UI or would that require using another generative image model?

The Translation API introduced at Session 10117 is impressive, but limiting it to SwiftUI is restrictive. This API works great in the demo, but for more complex apps, it lacks flexibility because it is bound to SwiftUI Views. Please consider making it available in non-SwiftUI environments.

I am very new to App Intents and I am trying to add them to my On Device LLM ChatBot app so my users can get answers to any questions anywhere in iOS. I have the following code and it is working wonderfully in the Shortcuts app. import AppIntents struct AskAi: AppIntent { static var openAppWhenRun: Bool = false static let title: LocalizedStringResource = "Ask Ai About" static let description = "Gets an answer from Ai for your question." @Parameter(title: "Question") var question: String static var parameterSummary: some ParameterSummary { Summary("Ask Ai About \(\.$question)") } @MainActor func perform() async throws -> some IntentResult & ReturnsValue<String> { let bot: Bot = Bot() await bot.respond(to: self.question) return .result( value: bot.output ) } } class AppShortcuts: AppShortcutsProvider { static var appShortcuts: [AppShortcut] { AppShortcut( intent: AskAi(), phrases: [ "Ask \(.applicationName) \(\.$question)", "Get \(.applicationName) answer for \(\.$question)", "Open \(\.$question) using \(.applicationName) ", "Using \(.applicationName) get help with \(\.$question)" ], shortTitle: "Ask Ai", systemImageName: "sparkles" ) } } I can create a shortcut for this AppIntent and that allows me say speak the response. I can call my shortcut via iOS 18 Beta 1 by the Shortcut name I set in the Shortcuts app and that allows it to work. It does not work at all by just Asking Siri any of the phrases I have defined. The info.plist has an app name alias defined just to be sure. I even added the Siri capability in Xcode-beta. I also tried using the ProvidesDialog return type too. Whatever I do the AppIntent is invisible to Siri. Siri tries to search the web, looking for my app name in the contacts or have an error Apple Cash which has nothing to do with what I was talking about. Is there anything else I am missing for setting up iOS AppIntents to work with Siri?

iOS 18 App Intents while supporting iOS 17 Hello, I have an existing app that supports iOS 17. I already have three App Intents but would like to add some of the new iOS 18 app intents like ShowInAppSearchResultsIntent. However, I am having a hard time using #available or @available to limit this ShowInAppSearchResultsIntent to iOS 18 only while still supporting iOS 17. Obviously, the ShowInAppSearchResultsIntent needs to use @AssistantIntent which is iOS 18 only, so I mark that struct as @available(iOS 18, *). That works as expected. It is when I need to add this "SearchSnippetIntent" intent to the AppShortcutsProvider, that I begin to have trouble doing. See code below: struct SnippetsShortcutsAppShortcutsProvider: AppShortcutsProvider { @AppShortcutsBuilder static var appShortcuts: [AppShortcut] { //iOS 17+ AppShortcut(intent: SnippetsNewSnippetShortcutsAppIntent(), phrases: [ "Create a New Snippet in \(.applicationName) Studio", ], shortTitle: "New Snippet", systemImageName: "rectangle.fill.on.rectangle.angled.fill") AppShortcut(intent: SnippetsNewLanguageShortcutsAppIntent(), phrases: [ "Create a New Language in \(.applicationName) Studio", ], shortTitle: "New Language", systemImageName: "curlybraces") AppShortcut(intent: SnippetsNewTagShortcutsAppIntent(), phrases: [ "Create a New Tag in \(.applicationName) Studio", ], shortTitle: "New Tag", systemImageName: "tag.fill") //iOS 18 Only AppShortcut(intent: SearchSnippetIntent(), phrases: [ "Search \(.applicationName) Studio", "Search \(.applicationName)" ], shortTitle: "Search", systemImageName: "magnifyingglass") } let shortcutTileColor: ShortcutTileColor = .blue } The iOS 18 Only AppShortcut shows the following error but none of the options seem to work. Maybe I am going about it the wrong way. 'SearchSnippetIntent' is only available in iOS 18 or newer Add 'if #available' version check Add @available attribute to enclosing static property Add @available attribute to enclosing struct Thanks in advance for your help.

The documentation for translationTask(source:target:action:) says it should translate when content appears, but this isn't happening. I’m only able to translate when I manually associate that task with a configuration, and instantiate the configuration. Here’s the complete source code: import SwiftUI import Translation struct ContentView: View { @State private var originalText = "The orange fox jumps over the lazy dog" @State private var translationTaskResult = "" @State private var translationTaskResult2 = "" @State private var configuration: TranslationSession.Configuration? var body: some View { List { // THIS DOES NOT WORK Section { Text(translationTaskResult) .translationTask { session in Task { @MainActor in do { let response = try await session.translate(originalText) translationTaskResult = response.targetText } catch { print(error) } } } } // THIS WORKS Section { Text(translationTaskResult2) .translationTask(configuration) { session in Task { @MainActor in do { let response = try await session.translate(originalText) translationTaskResult2 = response.targetText } catch { print(error) } } } Button(action: { if configuration == nil { configuration = TranslationSession.Configuration() return } configuration?.invalidate() }) { Text("Translate") } } } } } How can I automatically translate a given text when it appears using the new translationTask API?

I'm trying to use a custom system image for my App Shortcut: AppShortcut( intent: AppOpenIntent(), phrases: ["Open \(.applicationName)"], shortTitle: "Open App", systemImageName: "custom.image" ) I've added custom.image to Images.xcassets for my project, but the shortcuts icon is always blank in the Shortcuts app. Is it possible to use custom system images for app shortcuts?

I'm looking for a solution to take a picture or point the camera at a piece of clothing and match that image with an image the user has stored in my app. I'm storing the data in a Core Data database as a Binary Data object. Since the user also takes the pictures they store in the database I think I cannot use pre-trained Core ML models. I would like the matching to be done on device if possible instead of going to an external service. That will probably describe the item based on what the AI sees, but then I cannot match the item with the stored images in the app. Does anyone know if this is possible with frameworks as Vision or VisionKit?

Adding the openAppWhenRun property to an AppIntent for a ControlWidgetButton causes the following error when the control is tapped in Control Center: Unknown NSError The operation couldn’t be completed. (LNActionExecutorErrorDomain error 2018.) Here’s the full ControlWidget and AppIntent code that causes the errorerror: Should controls be able to open apps after the AppIntent runs, or is this a bug?

I want to implement AppIntent in my framework which is created and choose Objective-C as language, but when I new a swift file and implement AppIntent. then import to my project. the AppIntent didn't work. but I can use AppIntent directly in project.

I want to implement AppIntent in my Objective-C framework, because we need to design a fast pass to certain function. However, I create a struct inherited from AppIntent, and create a projectName-Bridging-Header.h in my framework just like I did in my project. It seems like framework don't work, I can't find it in shortcuts