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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How do I test the new RecognizeDocumentRequest API. Reference: https://www.youtube.com/watch?v=H-GCNsXdKzM
I am running Xcode Beta, however I only have one primary device that I cannot install beta software on.
Please provide a strategy for testing. Will simulator work?
The new capability is critical to my application, just what I need for structuring document scans and extraction.
Thank you.
According to the Tool documentation, the arguments to the tool are specified as a static struct type T, which is given to tool.call(argument: T) However, if the arguments are not known until runtime, is it possible to still create a Tool object with the proper parameters? Let's say a JSON-style dictionary is passed into the Tool init function to specify T, is this achievable?
This is my code:
witch SystemLanguageModel.default.availability {
case .available:
ContentView()
.popover(isPresented: $showSettings) {
SettingsView().presentationCompactAdaptation(.popover)
}
case .unavailable(.modelNotReady):
ContentUnavailableView("Apple Intelligence is unavailable",
systemImage: "apple.intelligence.badge.xmark",
description: Text("Please come back later."))
case .unavailable(.appleIntelligenceNotEnabled):
ContentUnavailableView("Apple Intelligence is unavailable",
systemImage: "apple.intelligence.badge.xmark",
description: Text("Please turn on Apple Intelligence."))
case .unavailable(.deviceNotEligible):
ContentUnavailableView("Apple Intelligence is unavailable",
systemImage: "apple.intelligence.badge.xmark",
description: Text("This device is not eligible for Apple Intelligence."))
case .unavailable:
ContentUnavailableView("Apple Intelligence is unavailable",
systemImage: "apple.intelligence.badge.xmark")
}
When I switch off Apple Intelligence, I expected "Please turn on Apple Intelligence.", but instead I get "Please come back later."
This seems to be wrong error?
Topic:
Machine Learning & AI
SubTopic:
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?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Testing Foundation Models framework with a health-focused recipe generation app. The on-device approach is appealing but performance is rough. Taking 20+ seconds just to get recipe name and description. Same content from Claude API: 4 seconds.
I know it's beta and on-device has different tradeoffs, but this is approaching unusable territory for real-time user experience. The streaming helps psychologically but doesn't mask the underlying latency.The privacy/cost benefits are compelling but not if users abandon the feature before it completes.
Anyone else seeing similar performance? Is this expected for beta, or are there optimization techniques I'm missing?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I’m working on generating images using Image Playground. The code works fine for other styles but fails when using an external provider. I don’t see any other requirements mentioned in the documentation. Has anyone else encountered a similar issue?
Here’s the relevant code snippet:
https://developer.apple.com/documentation/imageplayground/imageplaygroundstyle/externalprovider?changes=_2
The error message is also not very helpful. It simply states that the creation failed.
Note: I have enabled ChatGPT Plus, and the image generation using ChatGPT styles works fine when using the Playground app.
do {
let creator = try await ImageCreator()
let concept = ImagePlaygroundConcept.text("Love")
let images = creator.images(for: [concept], style: .externalProvider, limit: 1)
for try await image in images {
// Handle image
break
}
} catch {
// Handle error
}
I’m using the iOS 26 RC, and when I print creator.availableStyles, it doesn’t display the external Provider.
[ImagePlayground.ImagePlaygroundStyle(id: "animation", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "emoji", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "illustration", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "sketch", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "messages-background", _representationInfo: nil)]
Topic:
Machine Learning & AI
SubTopic:
Apple Intelligence
Hi,
I have an app that uses Core Data to store user information and display it in various views. I want to know if it's possible to easily integrate this setup with FoundationModels to make it easier for the user to query and manipulate the information, and if so, how would I go about it? Can the model be pointed to the database schema file and the SQLite file sitting in the user's app group container to parse out the information needed? And/or should the NSManagedObjects be made @Generable for better output? Any guidance about this would be useful.
Access to VisionPro cameras is required for a research project. The project is on mixed reality software development for healthcare applications in dentistry.
I have rewatched WWDC22 a few times , but still not getting full understanding how to get .mlmodel model file type from components .
Example with banana ripeness is cool , but what need to be added to actually have output of .mlmodel , is somewhere full sample code for this type of modular project ?
Code is from [https://developer.apple.com/videos/play/wwdc2022/10019)
import CoreImage
import CreateMLComponents
struct ImageRegressor {
static let trainingDataURL = URL(fileURLWithPath: "~/Desktop/bananas")
static let parametersURL = URL(fileURLWithPath: "~/Desktop/parameters")
static func train() async throws -> some Transformer<CIImage, Float> {
let estimator = ImageFeaturePrint()
.appending(LinearRegressor())
// File name example: banana-5.jpg
let data = try AnnotatedFiles(labeledByNamesAt: trainingDataURL, separator: "-", index: 1, type: .image)
.mapFeatures(ImageReader.read)
.mapAnnotations({ Float($0)! })
let (training, validation) = data.randomSplit(by: 0.8)
let transformer = try await estimator.fitted(to: training, validateOn: validation)
try estimator.write(transformer, to: parametersURL)
return transformer
}
}
I have tried to run it in Mac OS command line type app, Swift-UI but most what I had as output was .pkg with
"pipeline.json,
parameters,
optimizer.json,
optimizer"
Hi all,
I'm capturing a photo using AVCapturePhotoOutput, and I've set:
let photoSettings = AVCapturePhotoSettings()
photoSettings.isDepthDataDeliveryEnabled = true
Then I create the handler like this:
let data = photo.fileDataRepresentation()
let handler = try ImageRequestHandler(data: data, orientation: .right)
Now I’m wondering:
If depth data delivery is enabled, is it actually included and used when I pass the Data to ImageRequestHandler?
Or do I need to explicitly pass the depth data using the other initializer?
let handler = try ImageRequestHandler(
cvPixelBuffer: photo.pixelBuffer!,
depthData: photo.depthData,
orientation: .right
)
In short:
Does ImageRequestHandler(data:) make use of embedded depth info from AVCapturePhoto.fileDataRepresentation() — or is the pixel buffer + explicit depth data required?
Thanks for any clarification!
Are there any guidelines for using Foundation Models To generate text for users in response to some canned queries? Should we use a special icon or text to let the user know that Apple Intelligence is generating the text? Should there be a disclaimer like, Apple Intelligence can make mistakes, please check for accuracy, etc?
Topic:
Machine Learning & AI
SubTopic:
Apple Intelligence
I have a mac (M4, MacBook Pro) running Tahoe 26.0 beta. I am running Xcode beta.
I can run code that uses the LLM in a #Preview { }.
But when I try to run the same code in the simulator, I get the 'device not ready' error and I see the following in the Settings app.
Is there anything I can do to get the simulator to past this point and allowing me to test on it with Apple's LLM?
I have reinstalled everything including command line tools but the CreateML frameworks fail to install, I need the framework so that I can train my auto-categorzation model which predicts category based on descriptions. I need that framework because I want to use reviision 4.
please suggest advice on how do I proceed
I get the following dyld error on an iPad Pro with Xcode 26 beta 4:
Symbol not found: _$s16FoundationModels20LanguageModelSessionC7prewarm12promptPrefixyAA6PromptVSg_tF
Any advice?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
When the @Generable is applied toward a Swift struct declared within another struct, and when said nested struct is defined as the type of one of the properties of another @Generable type, which is in turn defined as the output format of Foundation Model session, Foundation Model can stuck in a loop trying to create a infinitely nested response, until the context window limit exceeded error is triggered.
I have filed feedback FB19987191 with a demo project. Is this expected behavior?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Has Apple made any commitment to versioning the Foundation Models on device? What if you build a feature that works great on 26.0 but they change the model or guardrails in 26.1 and it breaks your feature, is your only recourse filing Feedback or pulling the feature from the app? Will there be a way to specify a model version like in all of the server based LLM provider APIs? If not, sounds risky to build on.
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!
Topic:
Machine Learning & AI
SubTopic:
Apple Intelligence
Tags:
Shortcuts
App Intents
Apple Intelligence
I am trying to create a slightly different version of the content tagging code in the documentation:
https://developer.apple.com/documentation/foundationmodels/systemlanguagemodel/usecase/contenttagging
In the playground I am getting an "Inference Provider crashed with 2:5" error.
I have no idea what that means or how to address the error. Any assistance would be appreciated.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hey,
I receive GenerableContent as follows:
let response = try await session.respond(to: "", schema: generationSchema)
And it wraps GeneratedJSON which seems to be private.
What is the best way to get a string / raw value out of it? I noticed it could theoretically be accessed via transcriptEntries but it's not ideal.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models