Hi everyone, I'm trying to use VNDetectTextRectanglesRequest to detect text rectangles in an image. Here's my current code: guard let cgImage = image.cgImage(forProposedRect: nil, context: nil, hints: nil) else { return } let textDetectionRequest = VNDetectTextRectanglesRequest { request, error in if let error = error { print("Text detection error: \(error)") return } guard let observations = request.results as? [VNTextObservation] else { print("No text rectangles detected.") return } print("Detected \(observations.count) text rectangles.") for observation in observations { print(observation.boundingBox) } } textDetectionRequest.revision = VNDetectTextRectanglesRequestRevision1 textDetectionRequest.reportCharacterBoxes = true let handler = VNImageRequestHandler(cgImage: cgImage, orientation: .up, options: [:]) do { try handler.perform([textDetectionRequest]) } catch { print("Vision request error: \(error)") } The request completes without error, but no text rectangles are detected — the observations array is empty (count = 0). Here's a sample image I'm testing with: I expected VNTextObservation results, but I'm not getting any. Is there something I'm missing in how this API works? Or could it be a limitation of this request or revision? Thanks for any help!

I couldn't find information about this in the documentation. Could someone clarify if this API is available and how to access it?

I'm the creator of an app that helps users learn Arabic. Inside of the app users can save words, engage in lessons specific to certain grammar concepts etc. I'm looking for a way for Siri to 'suggest' my app when the user asks to define any Arabic words. There are other questions that I would like for Siri to suggest my app for, but I figure that's a good start. What framework am I looking for here? I think AppItents? I remember I played with it for a bit last year but didn't get far. Any suggestions would be great. Would the new Foundations model be any help here?

I downloaded the new developer beta and then installed xcode. I did the downloads but I couldn't download the Predictive Code Completion Model. When I try to download it I get the error "The operation couldn’t be completed. (ModelCatalog.CatalogErrors.AssetErrors error 1.)". I am using the M3 Pro model.

Would there be a popup automatically shown to a user saying to enable Apple Intelligence if our user has the toggle turned off? Just curious about how that experience looks for both us as developers and users.

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

At WWDC25 we launched a new type of Lab event for the developer community - Group Labs. A Group Lab is a panel Q&A designed for a large audience of developers. Group Labs are a unique opportunity for the community to submit questions directly to a panel of Apple engineers and designers. Here are the highlights from the WWDC25 Group Lab for Apple Intelligence. Can I integrate writing tools in my own text editor? UITextView, NSTextView, and SwiftUI TextEditor automatically get Writing Tools on devices that support Apple Intelligence. For custom text editors, check out Enhancing your custom text engine with Writing Tools. Given that Foundation Models are on-device, how will Apple update the models over time? And how should we test our app against the model updates? Model updates are in sync with OS updates. As for testing with updated models, watch our WWDC session about prompt engineering and safety, and read the Human Interface Guidelines to understand best practices in prompting the on-device model. What is the context size of a session in Foundation Models Framework? How to handle the error if a session runs out of the context size? Currently the context size is about 4,000 tokens. If it’s exceeded, developers can catch the .exceededContextWindowSize error at runtime. As discussed in one of our WWDC25 sessions, when the context window is exceeded, one approach is to trim and summarize a transcript, and then start a new session. Can I do image generation using the Foundation Models Framework or is only text generation supported? Foundation Models do not generate images, but you can use the Foundation Models framework to generate prompts for ImageCreator in the Image Playground framework. Developers can also take advantage of Tools in Foundation Models framework, if appropriate for their app. My app currently uses a third party server-based LLM. Can I use the Foundation Models Framework as well in the same app? Any guidance here? The Foundation Models framework is optimized for a subset of tasks like summarization, extraction, classification, and tagging. It’s also on-device, private, and free. But at 3 billion parameters it isn’t designed for advanced reasoning or world knowledge, so for some tasks you may still want to use a larger server-based model. Should I use the AFM for my language translation features given it does text translation, or is the Translation API still the preferred approach? The Translation API is still preferred. Foundation Models is great for tasks like text summarization and data generation. It’s not recommended for general world knowledge or translation tasks. Will the TranslationSession class introduced in ios18 get any new improvments in performance or reliability with the new live translation abilities in ios/macos/ipados 26? Essentially, will we get access to live translation in a similar way and if so, how? There's new API in LiveCommunicationKit to take advantage of live translation in your communication apps. The Translate framework is using the same models as used by Live Communication and can be combined with the new SpeechAnalyzer API to translate your own audio. How do I set a default value for an App Intent parameter that is otherwise required? You can implement a default value as part of your parameter declaration by using the @Parameter(defaultValue:) form of the property wrapper. How long can an App Intent run? On macOS there is no limit to how long app intents can run. On iOS, there is a limit of 30 seconds. This time limit is paused when waiting for user interaction. How do I vary the options for a specific parameter of an App Intent, not just based on the type? Implement a DynamicOptionsProvider on that parameter. You can add suggestedEntities() to suggest options. What if there is not a schema available for what my app is doing? If an app intent schema matching your app’s functionality isn’t available, take a look to see if there’s a SiriKit domain that meets your needs, such as for media playback and messaging apps. If your app’s functionality doesn’t match any of the available schemas, you can define a custom app intent, and integrate it with Siri by making it an App Shortcut. Please file enhancement requests via Feedback Assistant for new App intent schemas that would benefit your app. Are you adding any new app intent domains this year? In addition to all the app intent domains we announced last year, this year at WWDC25 we announced that Visual Intelligence will be added to iOS 26 and macOS Tahoe. When my App Intent doesn't show up as an action in Shortcuts, where do I start in figuring out what went wrong? App Intents are statically extracted. You can check the ExtractMetadata info in Xcode's build log. What do I need to do to make sure my App Intents work well with Spotlight+? Check out our WWDC25 sessions on App Intents, including Explore new advances in App Intents and Develop for Shortcuts and Spotlight with App Intents. Mostly, make sure that your intent can run from the parameter summary alone, no required parameters without default values that are not already in the parameter summary. Does Spotlight+ on macOS support App Shortcuts? Not directly, but it shows the App Intents your App Shortcuts are sitting on top of. I’m wondering if the on-device Foundation Models framework API can be integrated into an app to act strictly as an app in-universe AI assistant, responding only within the boundaries of the app’s fictional context. Is such controlled, context-limited interaction supported? FM API runs inside the process of your app only and does not automatically integrate with any remaining part of the system (unless you choose to implement your own tool and utilize tool calling). You can provide any instructions and prompts you want to the model. If a country does not support Apple Intelligence yet, can the Foundation Models framework work? FM API works on Apple Intelligence-enabled devices in supported regions and won’t work in regions where Apple Intelligence is not yet supported

After more than a year since the announcement, I'm still unable to get this feature working properly and wondering if there are known issues or missing implementation details. Current Setup: Device: iPhone 16 Pro Max iOS: 26 beta 3 Development: Tested on both Xcode 16 and Xcode 26 Implementation: Following the official documentation examples The Problem: Semantic search simply doesn't work. Lexical search functions normally, but enabling semantic search produces identical results to having it disabled. It's as if the feature isn't actually processing. Error Output (Xcode 26): [QPNLU][qid=5] Error Domain=com.apple.SpotlightEmbedding.EmbeddingModelError Code=-8007 "Text embedding generation timeout (timeout=100ms)" [CSUserQuery][qid=5] got a nil / empty embedding data dictionary [CSUserQuery][qid=5] semanticQuery failed to generate, using "(false)" In Xcode 16, there are no error messages at all - the semantic search just silently fails. Missing Resources: The sample application mentioned during the WWDC24 presentation doesn't appear to have been released, which makes it difficult to verify if my implementation is correct. Would really appreciate any guidance or clarification on the current status of this feature. Has anyone in the community successfully implemented this?

When I use ChatGPT in Xcode, the following error is displayed： It was working fine before, but suddenly it became like this, without changing any configuration. Why?

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!

My app lets you create images with Image Playground. When the user approves an image I move it to the documents dir from the temp storage. With over a year of usage I’ve created a lot of images over time. Out of nowhere the app stopped loading my custom creations from Image Playground saying it couldn’t find the files. It still had my VoiceOver strings I had added for each image and still had the custom categories I assigned them. Debug code to look in the docs dir doesn’t find them. I downloaded the app’s container and only see the images I created as a test after the problem started. But my ~70MB app is still taking up 300MB on my iPhone so it feels like they’re there but not accessible. Is there anything else I can try?

Things I did: created an Intents Extension target added "Supported Intents" to both my main app target and the intent extension, with "INAddTasksIntent" and "INCreateNoteIntent" created the AppIntentVocabulary in my main app target created the handlers in the code in the Intents Extension target class AddTaskIntentHandler: INExtension, INAddTasksIntentHandling { func resolveTaskTitles(for intent: INAddTasksIntent) async -> [INSpeakableStringResolutionResult] { if let taskTitles = intent.taskTitles { return taskTitles.map { INSpeakableStringResolutionResult.success(with: $0) } } else { return [INSpeakableStringResolutionResult.needsValue()] } } func handle(intent: INAddTasksIntent) async -> INAddTasksIntentResponse { // my code to handle this... let response = INAddTasksIntentResponse(code: .success, userActivity: nil) response.addedTasks = tasksCreated.map { INTask( title: INSpeakableString(spokenPhrase: $0.name), status: .notCompleted, taskType: .completable, spatialEventTrigger: nil, temporalEventTrigger: intent.temporalEventTrigger, createdDateComponents: DateHelper.localCalendar().dateComponents([.year, .month, .day, .minute, .hour], from: Date.now), modifiedDateComponents: nil, identifier: $0.id ) } return response } } class AddItemIntentHandler: INExtension, INCreateNoteIntentHandling { func resolveTitle(for intent: INCreateNoteIntent) async -> INSpeakableStringResolutionResult { if let title = intent.title { return INSpeakableStringResolutionResult.success(with: title) } else { return INSpeakableStringResolutionResult.needsValue() } } func resolveGroupName(for intent: INCreateNoteIntent) async -> INSpeakableStringResolutionResult { if let groupName = intent.groupName { return INSpeakableStringResolutionResult.success(with: groupName) } else { return INSpeakableStringResolutionResult.needsValue() } } func handle(intent: INCreateNoteIntent) async -> INCreateNoteIntentResponse { do { // my code for handling this... let response = INCreateNoteIntentResponse(code: .success, userActivity: nil) response.createdNote = INNote( title: INSpeakableString(spokenPhrase: itemName), contents: itemNote.map { [INTextNoteContent(text: $0)] } ?? [], groupName: INSpeakableString(spokenPhrase: list.name), createdDateComponents: DateHelper.localCalendar().dateComponents([.day, .month, .year, .hour, .minute], from: Date.now), modifiedDateComponents: nil, identifier: newItem.id ) return response } catch { return INCreateNoteIntentResponse(code: .failure, userActivity: nil) } } } uninstalled my app restarted my physical device and simulator Yet, when I say "Remind me to buy dog food in Index" (Index is the name of my app), as stated in the examples of INAddTasksIntent, Siri proceeds to say that a list named "Index" doesn't exist in apple Reminders app, instead of processing the request in my app. Am I missing something?

I have built a MAC-OS machine intelligence application that uses Apple Intelligence. A part of the application is to preprocess text. For longer text content I have implemented chunking to get around the token limit. However the application performance is now limited by the fact that Apple Intelligence is sequential in operation. This has a large impact on the application performance. Is there any approach to operate Apple Intelligence in a parallel mode or even a streaming interface. As Apple Intelligence has Private Cloud Services I was hoping to be able to send multiple chunks in parallel as that would significantly improve performance. Any suggestions would be welcome. This could also be considered a request for a future enhancement.

I am trying to use @AppIntent(schema: .system.search) to search in my app via a Siri voice command, but I want to be able to return a .result that does not open the app, yet still get the model training benefits from the schema. Very new to this, this is my first app, so I would appreciate some guidance. I haven't gotten to the voice part, I tested on Shortcuts. Do I need to do AppIntents without the schema and wait until there is a search schema that does not open the app, or should I be using a different schema? What am I missing?

I opened a new project, iOS app, in XCode and then tabbed into the system_search snippet and built the project and got a build error. I can't imagine this was intended, at least not for new developers to the ecosystem like me. I solved it by tweaking a configuration I don't really understand advised here: https://github.com/apple/swift-openapi-generator/issues/796, hopefully that's a valid workaround

Hi everyone, I’m currently using macOS Version 15.3 Beta (24D5034f), and I’m encountering an issue with Apple Intelligence. The image generation tools seem to work fine, but everything else shows a message saying that it’s “not available at this time.” I’ve tried restarting my Mac and double-checked my settings, but the problem persists. Is anyone else experiencing this issue on the beta version? Are there any fixes or settings I might be overlooking? Any help or insights would be greatly appreciated! Thanks in advance!

HI, I've been modifying the Camera sample app found here: https://developer.apple.com/tutorials/sample-apps/capturingphotos-camerapreview ... in the processpreview images, I am calling in to the Vision APis to either detect a person or object, then I'm using the segmentation mask to extract the person and composite them onto a different background with some other filters. I am using coreimage to filter the CIImages, and converting and displaying as a SwiftUI Image. When running on my IPhone, it works fine. When running on my Iphone with the debugger, it crashes within a few seconds... Attached is a screenshot. At the top is an EXC_BAD_ACCESS in libRPAC.dylib`std::__1::__hash_table<std::__1::__hash_value_type<long, qos_info_t>, std::__1::__unordered_map_hasher<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::hash, std::__1::equal_to, true>, std::__1::__unordered_map_equal<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::equal_to, std::__1::hash, true>, std::__1::allocator<std::__1::__hash_value_type<long, qos_info_t>>>::__emplace_unique_key_args<long, std::__1::piecewise_construct_t const&, std::__1::tuple<long const&>, std::__1::tuple<>>: This was working fine a couple of days ago.. Not sure why it's popping up now. Am I correct in interpreting this as an LLDB issue? How do I fix it?

Hello Apple Developer Community, I'm exploring the integration of Apple Intelligence features into my mobile application and have a couple of questions regarding the current and upcoming API capabilities: Custom Prompt Support: Is there a way to pass custom prompts to Apple Intelligence to generate specific inferences? For instance, can we provide a unique prompt to the Writing Tools or Image Playground APIs to obtain tailored outputs? Direct Inference Capabilities: Beyond the predefined functionalities like text rewriting or image generation, does Apple Intelligence offer APIs that allow for more generalized inference tasks based on custom inputs? I understand that Apple has provided APIs such as Writing Tools, Image Playground, and Genmoji. However, I'm interested in understanding the extent of customization and flexibility these APIs offer, especially concerning custom prompts and generalized inference. Additionally, are there any plans or timelines for expanding these capabilities, perhaps with the introduction of new SDKs or frameworks that allow deeper integration and customization? Any insights, documentation links, or experiences shared would be greatly appreciated. Thank you in advance for your assistance!

Attempted to download the Adapter Toolkit linked to from https://developer.apple.com/apple-intelligence/foundation-models-adapter/. Failed on all attempts, with a "403 Forbidden" error. I had accepted the agreement on the first attempt. How would we get access please?

Apple's Image Playground primarily performs image generation on-device, but can use secure Private Cloud Compute for more complex requests that require larger models. Private Cloud Compute (PCC) For more complex tasks that require greater computational power than the device can provide, Image Playground leverages Apple's Private Cloud Compute. This system extends the privacy and security of the device to the cloud: Secure Environment: PCC runs on Apple silicon servers and uses a secure enclave to protect data, ensuring requests are processed in a verified, secure environment. No Data Storage: Data is never stored or made accessible to Apple when using PCC; it is used only to fulfill the specific request. Independent Verification: Independent experts are able to inspect the code running on these servers to verify Apple's privacy promises.