I have a Generable type with many elements. I am using a stream() to incrementally process the output (Generable.PartiallyGenerated?) content.
At the end, I want to pass the final version (not partially generated) to another function.
I cannot seem to find a good way to convert from a MyGenerable.PartiallyGenerated to a MyGenerable.
Am I missing some functionality in the APIs?
Foundation Models
RSS for tagDiscuss the Foundation Models framework which provides access to Apple’s on-device large language model that powers Apple Intelligence to help you perform intelligent tasks specific to your app.
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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,
Would be great to have an equivalent of toolCallId for both toolCall and toolResult in the transcript. Otherwise, it is hard to connect tool calls with their respective responses, when there were multiple parallel calls to the same tool.
Thanks!
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Here's the result:
Very weird.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I've been successfully integrating the Foundation Models framework into my healthcare app using structured generation with @Generable schemas. While my initial testing (20-30 iterations) shows promising results, I need to validate consistency and reliability at scale before production deployment.
Question
Is there a recommended approach for automated, large-scale testing of Foundation Models responses?
Specifically, I'm looking to:
Automate 1000+ test iterations with consistent prompts and structured schemas
Measure response consistency across identical inputs
Validate structured output reliability (proper schema adherence, no generation failures)
Collect performance metrics (TTFT, TPS) for optimization
Specific Questions
Framework Limitations: Are there any undocumented rate limits or thermal throttling considerations for rapid session creation/destruction?
Performance Tools: Can Xcode's Foundation Models Instrument be used programmatically, or only through Instruments UI?
Automation Integration: Any recommendations for integrating with testing frameworks?
Session Reuse: Is it better to reuse a single LanguageModelSession or create fresh sessions for each test iteration?
Use Case Context
My wellness app provides medically safe activity recommendations based on user health profiles. The Foundation Models framework processes health context and generates structured recommendations for exercises, nutrition, and lifestyle activities. Given the safety implications of providing health-related guidance, I need rigorous validation to ensure the model consistently produces appropriate, well-formed recommendations across diverse user scenarios and health conditions.
Has anyone in the community built similar large-scale testing infrastructure for Foundation Models? Any insights on best practices or potential pitfalls would be greatly appreciated.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
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
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'm working on a to-do list app that uses SpeechTranscriber and Foundation Models framework to transcribe a user's voice into text and create to-do items based off of it.
After about 30 minutes looking at my code, I couldn't figure out why I was failing to generate a to-do for "I need to go to Six Flags Great America tomorrow at 3pm." It turns out, I was consistently firing the Foundation Models's safety filter violation for unsafe content ("May contain unsafe content").
Lesson learned: consider comprehensively logging Foundation Models error states to quickly identify when safety filters are unexpectedly triggered.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
When I use the FoundationModel framework to generate long text, it will always hit an error.
"Passing along Client rate limit exceeded, try again later in response to ExecuteRequest"
And stop generating.
eg. for the prompt "Write a long story", it will almost certainly hit that error after 17 seconds of generation.
do{
let session = LanguageModelSession()
let prompt: String = "Write a long story"
let response = try await session.respond(to: prompt)
}catch{}
If possible, I want to know how to prevent that error or at least how to handle it.
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.
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
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.
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?
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?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Does the Foundation Model provide Objective-C compatible APIs?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
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
I have been using "apple" to test foundation models.
I thought this is local, but today the answer changed - half way through explanation, suddenly guardrailViolation error was activated! And yesterday, all reference to "Apple II", "Apple III" now refers me to consult apple.com!
Does foundation models connect to Internet for answer? Using beta 3.
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
Apologies if this is obvious to everyone but me... I'm using the Tahoe AI foundation models. When I get an error, I'm trying to handle it properly.
I see the errors described here: https://developer.apple.com/documentation/foundationmodels/languagemodelsession/generationerror/context, as well as in the headers. But all I can figure out how to see is error.localizedDescription which doesn't give me much to go on.
For example, an error's description is:
The operation couldn’t be completed. (FoundationModels.LanguageModelSession.GenerationError error 2.
That doesn't give me much to go on. How do I get the actual error number/enum value out of this, short of parsing that text to look for the int at the end?
This one is:
case guardrailViolation(LanguageModelSession.GenerationError.Context)
So I'd like to know how to get from the catch for session.respond to something I can act on. I feel like it's there, but I'm missing it.
Thanks!
In the play ground I'm trying to bias my LanguageModel to use a tool I registered, but I don't see it actually calling the tool. I'm following the developer video on landmarks itinerary generation tutorial almost verbatim. Is this a prompt engineering thing I'm missing? Or is it possible that I'm injecting my tool wrong?