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).
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.
Selecting any option will automatically load the page
Post
Replies
Boosts
Views
Activity
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
Hey everyone,
Is it possible to generate XML using the “Generable” macro of the Foundation Model Framework?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hello
I’m experimenting with Apple’s on‑device language model via the FoundationModels framework in Xcode (using LanguageModelSession in my code). I’d like to confirm a few points:
• Is the language model provided by FoundationModels designed and trained by Apple? Or is it based on an open‑source model?
• Is this on‑device model available on iOS (and iPadOS), or is it limited to macOS?
• When I write code in Xcode, is code completion powered by this same local model? If so, why isn’t the same model available in the left‑hand chat sidebar in Xcode (so that I can use it there instead of relying on ChatGPT)?
• Can I grant this local model access to my personal data (photos, contacts, SMS, emails) so it can answer questions based on that information? If yes, what APIs, permission prompts, and privacy constraints apply?
Thanks
I would like to write a macOS application that uses on-device AI (FoundationModels).
I don’t understand how to, practically, give it access to my documents, photos, or contacts and be able to ask it a question like: “Find the document that talks about this topic.”
Do I need to manually retrieve the data and provide it in the form of a prompt? Or is FoundationModels capable of accessing it on its own?
Thanks
Pretty much as per the title and I suspect I know the answer. Given that Foundation Models run on device, is it possible to use Foundation Models framework inside of a DeviceActivityReport? I've been tinkering with it, and all I get is errors and "Sandbox restrictions". Am I missing something? Seems like a missed trick to utilise on device AI/ML with other frameworks.
I've downloaded the Xcode-beta and run the sample project "FoundationModelsTripPlanner" but I got this error when trying generate the response.
InferenceError::inferenceFailed::Error Domain=com.apple.UnifiedAssetFramework Code=5000 "There are no underlying assets (neither atomic instance nor asset roots) for consistency token for asset set com.apple.modelcatalog" UserInfo={NSLocalizedFailureReason=There are no underlying assets (neither atomic instance nor asset roots) for consistency token for asset set com.apple.modelcatalog}
Device: M1 Pro
Question:
Is it because M1 not supporting this feature?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Trying the Foundation Model framework and when I try to run several sessions in a loop, I'm getting a thrown error that I'm hitting a rate limit.
Are these rate limits documented? What's the best practice here?
I'm trying to run the models against new content downloaded from a web service where I might get ~200 items in a given download. They're relatively small but there can be that many that want to be processed in a loop.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I downloaded Xcode Beta 1 on my mac (did not upgrade the OS). The target OS level of iOS26 and the device simulator for iOS26 is downloaded and selected as the target.
When I try a simple Playground in Xcode ( #Playground ) I get a session error.
#Playground {
let avail = SystemLanguageModel.default.availability
if avail != .available {
print("SystemLanguageModel not available")
return
}
let session = LanguageModelSession()
do {
let response = try await session.respond(to: "Create a recipe for apple pie")
} catch {
print(error)
}
}
The error I get is:
Asset com.apple.gm.safety_deny_input.foundation_models.framework.api not found in Model Catalog
Is there a way to test drive the FoundationModel code without upgrading to macos26?
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
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I have a MacBook Pro M3 Pro with 18GB of RAM and was following the instructions to fine tune the foundational model given here: https://developer.apple.com/apple-intelligence/foundation-models-adapter/
However, while following the code sample in the example Jupyter notebook, my Mac hangs on the second code cell. Specifically:
from examples.generate import generate_content, GenerationConfiguration
from examples.data import Message
output = generate_content(
[[
Message.from_system("A conversation between a user and a helpful assistant. Taking the role as a play writer assistant for a kids' play."),
Message.from_user("Write a script about penguins.")
]],
GenerationConfiguration(temperature=0.0, max_new_tokens=128)
)
output[0].response
After some debugging, I was getting the following error:
RuntimeError: MPS backend out of memory (MPS allocated: 22.64 GB, other allocations: 5.78 MB, max allowed: 22.64 GB). Tried to allocate 52.00 MB on private pool. Use PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0 to disable upper limit for memory allocations (may cause system failure).
So is my machine not capable enough to adapter train Apple's Foundation Model? And if so, what's the recommended spec and could this be specified somewhere? Thanks!
I am calling into an app extension from a Safari Web Extension (sendNativeMessage, which in turn results in a call to NSExtensionRequestHandling’s beginRequest). My Safari extension aims to make use of the new foundation models for some of the features it provides.
In my testing, I hit the rate limit by sending 4 requests, waiting 30 seconds between each. This makes the FoundationModels framework (which would otherwise serve my use case perfectly well) unusable in this context, because the model is called in response to user input, and this rate of user input is perfectly plausible in a real world scenario.
The error thrown as a result of the rate limit is “Safety guardrail was triggered after consecutive failures during streaming.", but looking at the system logs in Console.app shows the rate limit as the real culprit.
My suggestions:
Please introduce sensible rate limits for app extensions, through an entitlement if need be. If it is rate limited to 1 request per every couple of seconds, that would already fix the issue for me.
Please document the rate limit.
Please make the thrown error reflect that it is the result of a rate limit and not a generic guardrail violation. IMPORTANT: please indicate in the thrown error when it is safe to try again.
Filed a feedback here: FB18332004
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I am using Foundation Models for the first time and no response is being provided to me.
Code
import Playgrounds
import FoundationModels
#Playground {
let session = LanguageModelSession()
let result = try await session.respond(to: "List all the states in the USA")
print(result.content)
}
Canvas Output
What I did
New file
Code
Canvas refreshes but nothing happens
Am I missing a step or setup here? Please help. Something so basic is not working I do not know what to do.
Running 40GPU, 16CPU MacBook Pro.. IOS26/Xcodebeta2/Tahoe allocated 8CPU, 48GB memory in Parallels VM.
Settings for Playgrounds in Xcode
Thank you for your help in advance.
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.
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
Does the Foundation Model provide Objective-C compatible APIs?
Topic:
Machine Learning & AI
SubTopic:
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.
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.
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
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?