Hi everyone, I’m currently exploring the use of Foundation models on Apple platforms to build a chatbot-style assistant within an app. While the integration part is straightforward using the new FoundationModel APIs, I’m trying to figure out how to control the assistant’s responses more tightly — particularly: Ensuring the assistant adheres to a specific tone, context, or domain (e.g. hospitality, healthcare, etc.) Preventing hallucinations or unrelated outputs Constraining responses based on app-specific rules, structured data, or recent interactions I’ve experimented with prompt, systemMessage, and few-shot examples to steer outputs, but even with carefully generated prompts, the model occasionally produces incorrect or out-of-scope responses. Additionally, when using multiple tools, I'm unsure how best to structure the setup so the model can select the correct pathway/tool and respond appropriately. Is there a recommended approach to guiding the model's decision-making when several tools or structured contexts are involved? Looking forward to hearing your thoughts or being pointed toward related WWDC sessions, Apple docs, or sample projects.

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.

I am writing a custom package wrapping Foundation Models which provides a chain-of-thought with intermittent self-evaluation among other things. At first I was designing this package with the command line in mind, but after seeing how well it augments the models and makes them more intelligent I wanted to try and build a SwiftUI wrapper around the package. When I started I was using synchronous generation rather than streaming, but to give the best user experience (as I've seen in the WWDC sessions) it is necessary to provide constant feedback to the user that something is happening. I have created a super simplified example of my setup so it's easier to understand. First, there is the Reasoning conversation item, which can be converted to an XML representation which is then fed back into the model (I've found XML works best for structured input) public typealias ConversationContext = XMLDocument extension ConversationContext { public func toPlainText() -> String { return xmlString(options: [.nodePrettyPrint]) } } /// Represents a reasoning item in a conversation, which includes a title and reasoning content. /// Reasoning items are used to provide detailed explanations or justifications for certain decisions or responses within a conversation. @Generable(description: "A reasoning item in a conversation, containing content and a title.") struct ConversationReasoningItem: ConversationItem { @Guide(description: "The content of the reasoning item, which is your thinking process or explanation") public var reasoningContent: String @Guide(description: "A short summary of the reasoning content, digestible in an interface.") public var title: String @Guide(description: "Indicates whether reasoning is complete") public var done: Bool } extension ConversationReasoningItem: ConversationContextProvider { public func toContext() -> ConversationContext { // <ReasoningItem title="${title}"> // ${reasoningContent} // </ReasoningItem> let root = XMLElement(name: "ReasoningItem") root.addAttribute(XMLNode.attribute(withName: "title", stringValue: title) as! XMLNode) root.stringValue = reasoningContent return ConversationContext(rootElement: root) } } Then there is the generator, which creates a reasoning item from a user query and previously generated items: struct ReasoningItemGenerator { var instructions: String { """ <omitted for brevity> """ } func generate(from input: (String, [ConversationReasoningItem])) async throws -> sending LanguageModelSession.ResponseStream<ConversationReasoningItem> { let session = LanguageModelSession(instructions: instructions) // build the context for the reasoning item out of the user's query and the previous reasoning items let userQuery = "User's query: \(input.0)" let reasoningItemsText = input.1.map { $0.toContext().toPlainText() }.joined(separator: "\n") let context = userQuery + "\n" + reasoningItemsText let reasoningItemResponse = try await session.streamResponse( to: context, generating: ConversationReasoningItem.self) return reasoningItemResponse } } I'm not sure if returning LanguageModelSession.ResponseStream<ConversationReasoningItem> is the right move, I am just trying to imitate what session.streamResponse returns. Then there is the orchestrator, which I can't figure out. It receives the streamed ConversationReasoningItems from the Generator and is responsible for streaming those to SwiftUI later and also for evaluating each reasoning item after it is complete to see if it needs to be regenerated (to keep the model on-track). I want the users of the orchestrator to receive partially generated reasoning items as they are being generated by the generator. Later, when they finish, if the evaluation passes, the item is kept, but if it fails, the reasoning item should be removed from the stream before a new one is generated. So in-flight reasoning items should be outputted aggresively. I really am having trouble figuring this out so if someone with more knowledge about asynchronous stuff in Swift, or- even better- someone who has worked on the Foundation Models framework could point me in the right direction, that would be awesome!

What are the steps in order to safely partition a drive to run MacOS26 for testing on my main machine without corrupting the main machine, please advise? My machine is a Mac Pro M3 Max Apple Intelligence/Foundation Models DO NOT WORK on Parallels VM. I cannot afford to buy new machines. My current one is maxed out on GPU/CPU and memory. TIME SENSITIVE

What is the policy for data sharing when using Coding Intelligence in Xcode 26? In many environments, sending out source code or even meta data that may be stored in external systems is not allowed. Is there any kind of policy on data persistency / sharing when using the default provider? Is there a way to limit data sharing apart from running models locally?

error I get when I try and install predictive code completion model

how do we add google models, deepseek, or mistral into xcode 26 intelligence model providers ?

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 trying to create an App Intent that lets a user select a day in the itinerary of a trip. The trip has to be chosen before the days available can be displayed. When the PlanActivityIntentDemo intent is ran from the shortcuts app, the trip selected is not injected into the appropriate TripItineraryDayQueryDemo Entity Query. Is there a way to get the selected trip to be injected at run time from shortcuts app. Here's some code for illustration: // Entity Definition: import AppIntents struct ShortcutsItineraryDayEntityDemo: Identifiable, Hashable, AppEntity { typealias DefaultQuery = TripItineraryDayQueryDemo static var typeDisplayRepresentation: TypeDisplayRepresentation = "Trip Itinerary Day" var displayRepresentation: DisplayRepresentation { "Trip Day" } var id: String static var defaultQuery: DefaultQuery { TripItineraryDayQueryDemo() } init() { self.id = UUID().uuidString } } struct TripItineraryDayQueryDemo: EntityQuery { // This only works in shortcut editor but not at runtime. Why? How can I fix this issue? @IntentParameterDependency<PlanActivityIntentDemo>(\.$tripEntity) var tripEntity @IntentParameterDependency<PlanActivityIntentDemo>(\.$title) var intentTitle func entities(for identifiers: [ShortcutsItineraryDayEntityDemo.ID]) async throws -> [ShortcutsItineraryDayEntityDemo] { print("entities being called with identifiers: \(identifiers)") // This method is called when the app needs to fetch entities based on identifiers. let tripsStore = TripsStore() guard let trip = tripEntity?.tripEntity.trip, let itineraryId = trip.firstItineraryId else { print("No trip or itinerary ID can be found for the selected trip.") return [] } return [] // return empty for this demo } func suggestedEntities() async throws -> [ShortcutsItineraryDayEntityDemo] { print("suggested itinerary days being called") let tripsStore = TripsStore() guard let trip = tripEntity?.tripEntity.trip, let itineraryId = trip.firstItineraryId else { print("No trip or itinerary ID found for the selected trip.") return [] } return [] } } struct PlanActivityIntentDemo: AppIntent { static var title: LocalizedStringResource { "Plan New Activity" } // The selected trip fails to get injected when intent is run from shortcut app @Parameter(title: "Trip", description: "The trip to plan an activity for", requestValueDialog: "Which trip would you like to plan an activity for?") var tripEntity: ShortcutsTripEntity @Parameter(title: "Activity Title", description: "The title of the activity", requestValueDialog: "What do you want to do or see?") var title: String @Parameter(title: "Activity Day", description: "Activity Day") var activityDay: ShortcutsItineraryDayEntity func perform() async throws -> some ProvidesDialog { // This is a demo intent, so we won't actually perform any actions. .result(dialog: "Activity '\(title)' planned") } }

Are there any details available on how Xcode 26 connects to third party model providers? For example, can Xcode only use OpenAI compatible API endpoints?

Hi everyone, I am using Xcode 16.4 in MacOS Sequoia 15.5 with Apple Intelligence turned on. The following code gives the error message in the title: import NaturalLanguage @available(iOS 18.0, *) func testSystemModel() { let model = SystemLanguageModel.default print(model) } What am I missing?

I'm experimenting with downloading an audio file of spoken content, using the Speech framework to transcribe it, then using FoundationModels to clean up the formatting to add paragraph breaks and such. I have this code to do that cleanup: private func cleanupText(_ text: String) async throws -> String? { print("Cleaning up text of length \(text.count)...") let session = LanguageModelSession(instructions: "The content you read is a transcription of a speech. Separate it into paragraphs by adding newlines. Do not modify the content - only add newlines.") let response = try await session.respond(to: .init(text), generating: String.self) return response.content } The content length is about 29,000 characters. And I get this error: InferenceError::inferenceFailed::Failed to run inference: Context length of 4096 was exceeded during singleExtend.. Is 4096 a reference to a max input length? Or is this a bug? This is running on an M1 iPad Air, with iPadOS 26 Seed 1.

Posting a follow up question after the WWDC 2025 Machine Learning AI & Frameworks Group Lab on June 12. In regards to the on-device API of any of the AI frameworks (foundation model, vision framework, ect.), is there a response condition or path where the API outsources it's input to ChatGPT if the user has allowed this like Siri does? Ignore this if it's a no: is this handled behind the scenes or by the developer?

While test driving Xcode on macOS 26, Intelligence is showing unavailable in region error. I am in the US, and I would love to try it out.

Can I use the “apple.intelligence” SF symbol to refer to the functionality of Foundation Models frameworks within my app, or does it specifically refer to Apple Intelligence and not a feature of my own creation that is built upon Apple Intelligence?

Currently there's only an option to link your OpenAI account to use ChatGPT within Xcode on MacOS 26 Beta. Apparently with other services like Claude you can specify which model you'd like to use, but there's no such option for ChatGPT. Is this coming, or is this working as designed?

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!

Greetings! I was trying to get a response from the LanguageModelSession but I just keep getting the following: Error getting response: Model Catalog error: 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.MobileAsset.UAF.FM.Overrides" UserInfo={NSLocalizedFailureReason=There are no underlying assets (neither atomic instance nor asset roots) for consistency token for asset set com.apple.MobileAsset.UAF.FM.Overrides} This occurs both in macOS 15.5 running the new Xcode beta with an iOS 26 simulator, and also on a macOS 26 with Xcode beta. The simulators are both Pro iPhone 16s. I was wondering if anyone had any advice?

Can the Xcode 26 code assist feature be used in a macOS 26 virtual machine? I am not seeing a way to enable it... Also asking on https://github.com/insidegui/VirtualBuddy/discussions/524

I'm attempting to run a basic Foundation Model prototype in Xcode 26, but I'm getting the error below, using the iPhone 16 simulator with iOS 26. Should these models be working yet? Do I need to be running macOS 26 for these to work? (I hope that's not it) Error: Passing along Model Catalog error: 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.MobileAsset.UAF.FM.Overrides" UserInfo={NSLocalizedFailureReason=There are no underlying assets (neither atomic instance nor asset roots) for consistency token for asset set com.apple.MobileAsset.UAF.FM.Overrides} in response to ExecuteRequest Playground to reproduce: #Playground { let session = LanguageModelSession() do { let response = try await session.respond(to: "What's happening?") } catch { let error = error } }