I have an image based app with albums, except in my app, albums are known as galleries. When I tried to conform my existing OpenGalleryIntent with @AssistantIntent(schema: .photos.openAlbum), I had to change my existing gallery parameter to be called target in order to fit the predefined shape of this domain. Previously, my intent was configured to display as “Open Gallery” with the description “Opens the selected Gallery” in the Shortcuts app. After conforming to the photos domain, it displays as “Open Album” with a description “Opens the Provided Album”. Shortcuts is ignoring my configured title and description now. My code builds, but with the following build warnings: Parameter argument title of a required Assistant schema intent parameter target should not be overridden Implementation of the property title of an AppIntent conforming to AssistantSchemaIntent should not be overridden Implementation of the property description of an AppIntent conforming to AssistantSchemaIntent should not be overridden Is my only option to change the concept of a Gallery inside of my app into an Album? I don't want to do this... Conceptually, my app aligns well with this domain does, but I didn't consider that conforming to the shape of an AI schema intent would also dictate exactly how it's presented to the user. FB16283840

Is it possible to train a model using CreateML to infer a relevance numeric score of a news article based on similar trained data, something like a sentiment score ? I created a Text Classifier that assigns a category label which works perfect but I would like a solution that calculates a numeric value, not a label.

I found what might be a bug with enabling Apple Intelligence when switching languages. When my iPhone's language is set to Catalan, the Apple Intelligence is disabled because it is not available for that language. Switching to Spanish doesn't activate it, and it still shows the same message of being unavailable, this time saying not available in Spanish (which is not true). However, it is enabled when the phone is rebooted. Once at this point, the bug becomes even weirder. Having the iPhone language set to Spanish and with Apple Intelligence on, I switch the language to Catalan, and the feature remains enabled. After I ask a query in Catalan, it surprisingly understands it and works, but then it gets disabled. Apart from that, as user feedback, I would love to activate Apple Intelligence in an available language other than my device's language. That's how I always used Siri (iPhone in Catalan, Siri in Spanish). Thanks!

Seeing this error from time to time: Context(debugDescription: "Content contains 4089 tokens, which exceeds the maximum allowed context size of 4096.", underlyingErrors: []) Of course, 4089 is less than 4096 so what is this telling me and how do I work around it? Is the limit actually lower than 4096?

We are building an app which can reads texts. It can read english and Japanese normal texts successfully. But in some cases, we need to read Japanese tategaki (vertically aligned texts). But in that times, the same code gives no output. So, is there any need to change any configuration to read Japanese tategaki? Or is it really possible to read Japanese tategaki using vision framework? lazy var detectTextRequest = VNRecognizeTextRequest { request, error in self.resStr="\n" self.words = [:] // Get OCR result guard let res = request.results as? [VNRecognizedTextObservation] else { return } // separate the words by space let text = res.compactMap({$0.topCandidates(1).first?.string}).joined(separator: " ") var n = 0 self.wordArr=[[]] self.xs = 1 self.ys = 1 var hs = 0.0 // To compare the heights of the words // To get the original axis (top most word's axis), only once for r in res { var word = r.topCandidates(1).first?.string self.words[word ?? ""] = [r.topLeft.x, r.topLeft.y] if(self.cartLabelType == 1){ if(word?.components(separatedBy: CharacterSet(charactersIn: "/／")).count ?? 0>2){ self.xs = r.topLeft.x self.ys = r.topLeft.y } } } } }

Hey everyone, Is it possible to generate XML using the “Generable” macro of the Foundation Model Framework?

Just tried to write a very simple test of using foundation models, but it gave me the error like this "ModelManager received unentitled request. Expected entitlement com.apple.modelmanager.inference establishment of session failed with Missing entitlement: com.apple.modelmanager.inference" The simple code is listed below: let session: LanguageModelSession = LanguageModelSession() let response = try? await session.respond(to: "What is the capital of France?") print("Response: (response)") So what's the problem of this one?

When context window size exceeded, this error is not called (instead another error has shown up) to handle new session. LanguageModelSession.GenerationError.exceededContextWindowSize Or am I doing things wrong?

Hi, I am a new IOS developer, trying to learn to integrate the Apple Foundation Model. my set up is: Mac M1 Pro MacOS 26 Beta Version 26.0 beta 3 Apple Intelligence & Siri --> On here is the code, func generate() { Task { isGenerating = true output = "⏳ Thinking..." do { let session = LanguageModelSession( instructions: """ Extract time from a message. Example Q: Golfing at 6PM A: 6PM """) let response = try await session.respond(to: "Go to gym at 7PM") output = response.content } catch { output = "❌ Error:, \(error)" print(output) } isGenerating = false } and I get these errors guardrailViolation(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Prompt may contain sensitive or unsafe content", underlyingErrors: [Asset com.apple.gm.safety_embedding_deny.all not found in Model Catalog])) Can you help me get through this?

Is there anywhere we can reference error codes? I'm getting this error: "The operation couldn’t be completed. (FoundationModels.LanguageModelSession.GenerationError error 4.)" and I have no idea of what it means or what to attempt to fix.

Almost everywhere else you see Apple Intelligence, you get to select whether it's on device, private cloud compute, or ChatGPT. Is there a way to do that via code in the Foundation Model? I searched through the docs and couldn't find anything, but maybe I missed it.

Hi, Are there rules around using Foundation Models: In a background task/session? Concurrently, i.e. a bunch simultaneously using Swift Concurrency? I couldn't find this in the docs (sorry if I missed it) so wondering what's supported and what the best practice is here. In case it matters, my primary platform is Vision Pro (so, M2).

Do we know what a safe max token limit is? After some iterating, I have come to believe 4096 might be the limit on device. Could you help me out by answering any of these questions: Is 4096 the correct limit? Do all devices have the same limit? Will the limit change over time or by device? The errors I get when going over the limit do not seem to say, hey you are over, so it's just by trial and error that I figure these issues out. Thanks for the fun new toys. Regards, Rob

I’m developing an activity classifier that I’d like to input using the JSON format of CoreMotion data. I am getting the error: Unable to parse /Users/DewG/Downloads/Testing/Step1/Testing.json. It does not appear to be in JSON record format. A SequenceType of dictionaries is expected I've verified that the format I am using is JSON via various JSON validators, so I am expecting I'm just holding it wrong. Is there an example of a JSON file with CoreMotion data that I can model after?

I keep getting the error “An unsupported language or locale was used.” Is there any documentation that specifies the accepted languages or locales in Foundation model?

Hello, My app fully relies on the new Foundation Models. Since Foundation Models require Apple Intelligence, I want to ensure that only devices capable of running Apple Intelligence can install my app. When checking the UIRequiredDeviceCapabilities property for a suitable value, I found that iphone-performance-gaming-tier seems the closest match. Based on my research: On iPhone, this effectively limits installation to iPhone 15 Pro or later. On iPad, it ensures M1 or newer devices. This exactly matches the hardware requirements for Apple Intelligence. However, after setting iphone-performance-gaming-tier, I noticed that on iPad, Game Mode (Game Overlay) is automatically activated, and my app is treated as a game. My questions are: Is there a more appropriate UIRequiredDeviceCapabilities value that would enforce the same Apple Intelligence hardware requirements without triggering Game Mode? If not, is there another way to restrict installation to devices meeting Apple Intelligence requirements? Is there a way to prevent Game Mode from appearing for my app while still using this capability restriction? Thanks in advance for your help.

I've tried creating a Lora adapter using the example dataset, scripts as part of the adapter_training_toolkit_v26_0_0 (last available) on MacOs 26 Beta 6. import SwiftUI import FoundationModels import Playgrounds #Playground { // The absolute path to your adapter. let localURL = URL(filePath: "/Users/syl/Downloads/adapter_training_toolkit_v26_0_0/train/test-lora.fmadapter") // Initialize the adapter by using the local URL. let adapter = try SystemLanguageModel.Adapter(fileURL: localURL) // An instance of the the system language model using your adapter. let customAdapterModel = SystemLanguageModel(adapter: adapter) // Create a session and prompt the model. let session = LanguageModelSession(model: customAdapterModel) let response = try await session.respond(to: "hello") } I get Adapter assets are invalid error. I've added the entitlements Is adapter_training_toolkit_v26_0_0 up to date?

I have a fairly basic prompt I've created that parses a list of locations out of a string. I've then created a tool, which for these locations, finds their latitude/longitude on a map and populates that in the response. However, I cannot get the language model session to see/use my tool. I have code like this passing the tool to my prompt: class Parser { func populate(locations: String, latitude: Double, longitude: Double) async { let findLatLonTool = FindLatLonTool(latitude: latitude, longitude: longitude) let session = LanguageModelSession(tools: [findLatLonTool]) { """ A prompt that populates a model with a list of locations. """ """ Use the findLatLon tool to populate the latitude and longitude for the name of each location. """ } let stream = session.streamResponse(to: "Parse these locations: \(locations)", generating: ParsedLocations.self) let locationsModel = LocationsModels(); do { for try await partialParsedLocations in stream { locationsModel.parsedLocations = partialParsedLocations.content } } catch { print("Error parsing") } } } And then the tool that looks something like this: import Foundation import FoundationModels import MapKit struct FindLatLonTool: Tool { typealias Output = GeneratedContent let name = "findLatLon" let description = "Find the latitude / longitude of a location for a place name." let latitude: Double let longitude: Double @Generable struct Arguments { @Guide(description: "This is the location name to look up.") let locationName: String } func call(arguments: Arguments) async throws -> GeneratedContent { let request = MKLocalSearch.Request() request.naturalLanguageQuery = arguments.locationName request.region = MKCoordinateRegion( center: CLLocationCoordinate2D(latitude: latitude, longitude: longitude), latitudinalMeters: 1_000_000, longitudinalMeters: 1_000_000 ) let search = MKLocalSearch(request: request) let coordinate = try await search.start().mapItems.first?.location.coordinate if let coordinate = coordinate { return GeneratedContent( LatLonModel(latitude: coordinate.latitude, longitude: coordinate.longitude) ) } return GeneratedContent("Location was not found - no latitude / longitude is available.") } } But trying a bunch of different prompts has not triggered the tool - instead, what appear to be totally random locations are filled in my resulting model and at no point does a breakpoint hit my tool code. Has anybody successfully gotten a tool to be called?

Hi everyone😊, I want to implement facial recognition into my app. I was planning to use createML's image classification, but there seams to be a lot of hassle to implement (the JSON file etc.). Are there some other easy to implement options that don't involve advanced coding. Thanks, Oliver

I can no longer achieve 100% ANE usage since upgrading to MacOS26 Beta 5. I used to be able to get 100%. Has Apple activated throttling or power saving features in the new Betas? Is there any new rate limiting on the API? I can hardly get above 3w or 40%. I have a M4 Pro mini (64GB) with High Power energy setting. MacOS 26 Beta 5.