Mobile AI with LM Studio: iOS Development Mastery

Capture a photo on iOS, send it to the LM Studio vision model via the local server, and display the generated image description in the app.

Improve iOS apps by capturing a photo, encoding it as base64, and generating a description from a vision LLM hosted on LM Studio via a private server in Swift.

Prepare an iOS network call to Vision LLM by converting an image URL to data, encoding it in base64, and outlining the request body structure for a private server interaction.

Construct the LLM vision request body for LM Studio, setting the local model, building messages with role and content, and embedding a base64 image with token and stream options.

Learn how to send a network request to Vision LLM in LM Studio using a prepared payload to generate image descriptions, and verify the response with an example of penguins.

Learn to fetch a photo from the iPhone, encode its data in base64, and send it to the LM Studio API via the simulator, including saving the image to Photos.

Rename the send button to select photo, add a UI image view with constraints, and wire an outlet to display the chosen image in a new iOS photo selection UI.

Connects a select photo button to an image view by implementing an ibaction and wiring outlets. Sets up a photo picker with uiimagepickercontroller and delegates to open the photo library.

Learn to integrate the image picker: select an image from the gallery using UIImagePickerController, convert it to JPEG data, handle dismissal, and cancellation, and prepare for backend upload.

Modify iOS code to send image data from the image picker to a private server, replacing image URLs with base64 image data and display generated description in the text area.

Create a travel buddy iPhone app by configuring a travel-focused system message in the AI manager and connecting to a private LM Studio chat server.

Create a language learning iPhone app in Xcode using the AI manager to generate text with a private server chat, Lingua Chat prompts guiding French phrase practice and real-time translation.

Develop an online dating coaching app that analyzes chat screenshots, queries a private LLM for response suggestions, and helps users craft replies to secure a date.

Use the Vision framework to read text from screenshots by building a text recognition manager in Swift. Employ VNRecognizeTextRequest to extract the main dating chat text.

Learn to extract text from screenshots with a text recognition manager integrated with the image picker and vision manager, then send the extracted text to a private llm server.

Craft a system message to make the AI an online dating and relationship psychology expert. Develop editing code for a private LM server, including a dating menu and conversation extraction.

Send a request to a private LM server from an iOS app using a system message and I manager, then display the server reply in the UI with progress feedback.

Test and demonstrate a private LM server–driven dating coach inside an iOS app, validating UI changes, main-thread handling, text recognition, and real conversations to land a date.

Build the AI dating coach iOS app UI by adding a table view controller with dynamic prototype cells to show multiple conversation threads.

Configure a table view cell to show thread color and the conversation name. Set the row height to 44 pixels and add constraints.

Enhance the iOS table view with a header, a plus button, and a prototype cell featuring a disclosure accessory, while configuring constraints and colors to enable tapping into conversations.

Create the message and thread data models for the ai assisted dating coach iOS app, with a text or image message and a codable thread class for local storage.

Fix thread decodable conformance by ensuring messages are non-nil and codable, add coding keys for id, ribbon color, person name, and messages, and implement decode/encode logic.

Learn to create UI color convenience extensions to initialize from hex strings and encode colors back to hex, plus building a thread manager with mock data for save and retrieval.

Create a thread manager to handle multiple conversations by adding, saving, loading, and deleting threads, with a singleton shared instance and local storage for images and thread data.

Create and manage a thread manager singleton, store and retrieve an array of threads from user defaults using JSON encoding and decoding, and handle encoding and decoding errors.

Save and retrieve images to local storage by saving ui images as jpeg in the documents directory, using file URLs and paths, with do-catch error handling and path-based retrieval.

Learn to add and delete threads in a chat-like structure by updating a thread array, guarding against out-of-bounds indices, and saving changes to local storage.

Create the thread list view controller that drives the table view, wire it to the storyboard, and populate it with mock threads and a configurable thread cell.

Develop a table view driven thread list, handle row selection and deselection to load a thread and its details, add mock threads, and wire storyboard connections for the thread cell.

Tap the plus button to open an alert, enter the person’s name, and create a new thread with a color and unique id using the add new thread workflow.

learn to implement adding a new thread, display the new conversation in the list, refresh the table view, and apply a random ribbon color via the thread manager saving locally.

Learn to implement a thread manager in iOS development to save and retrieve conversations, populate threads on view load, and add new threads to the list.

Implement a swipe-to-delete for the thread list that removes a thread via the thread manager, saves changes locally, and updates the table view.

rename the view controller to thread details view controller, pass the selected thread from the list, and load messages into a scroll view with proper constraints.

Instantiate the thread details view controller from the storyboard, load the messages of the selected thread, and present or push it to display text and images.

Load and display text messages in a thread by iterating thread messages, creating labels, and laying them out in a scroll view with a dynamic y offset.

Load existing text messages and extend the view to display image messages by checking image paths, creating an image view with aspect fit, and updating the scroll view's content size.

Fix the nil text issue and extend the message view to support images by saving image paths with a generated uuid file name and displaying text and image together.

Test the thread image messaging feature in the simulator, adding messages with images and ensuring loading works while avoiding duplicates, and updating the thread via the thread manager.

Append new messages in the thread details view and update the thread via the thread manager to preserve history on app reload, while debugging the missing thread image.

Modify the thread message model to save only the image name (uuid) and load images from the documents directory, then display them in the thread details view controller.

Save live messages to the current thread by uploading a photo, displaying it in the conversation, and saving the image when it returns from the backend.