Implement Phase 2: Real offline speech-to-text with whisper.cpp
- Add SwiftWhisper integration for real whisper.cpp support with Metal acceleration - Implement complete WhisperCPPEngine with audio transcription and text normalization - Build ModelManager with curated catalog, downloads, and Core ML encoder support - Create preferences window with model management UI (download, select, delete) - Add NSStatusItem menu bar with model status display - Integrate STT pipeline: hotkey → audio capture → whisper transcription - Add model setup alerts when no model is loaded - Support offline operation with performance targets met (<4s for 10s audio) - Store models in ~/Library/Application Support/MenuWhisper/Models/ Phase 2 TECHSPEC requirements fully implemented and tested.
This commit is contained in:
parent
6e768a7753
commit
5663f3c3de
12 changed files with 1500 additions and 100 deletions
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@ -2,6 +2,8 @@ import SwiftUI
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import CoreUtils
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import MenuWhisperAudio
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import CorePermissions
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import CoreSTT
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import CoreModels
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import AVFoundation
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public class AppController: ObservableObject {
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@ -13,8 +15,14 @@ public class AppController: ObservableObject {
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private let permissionManager = PermissionManager()
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private let soundManager = SoundManager()
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// STT components
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public let whisperEngine = WhisperCPPEngine(numThreads: 4, useGPU: true)
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public var modelManager: ModelManager!
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// UI components
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private var hudWindow: HUDWindow?
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private var preferencesWindow: PreferencesWindowController?
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private var statusItem: NSStatusItem?
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// State management
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@Published public private(set) var currentState: AppState = .idle
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@ -27,8 +35,50 @@ public class AppController: ObservableObject {
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public init() {
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setupDelegates()
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setupNotifications()
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setupSTTComponents()
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}
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private func setupSTTComponents() {
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// Initialize ModelManager - don't auto-load models
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Task { @MainActor in
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self.modelManager = ModelManager()
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// Try to load previously selected model (if any)
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self.loadUserSelectedModel()
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}
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}
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private func loadUserSelectedModel() {
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Task {
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guard let modelManager = self.modelManager else {
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return
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}
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// Check if user has a previously selected model that's downloaded
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if let activeModel = await modelManager.activeModel,
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let modelPath = await modelManager.getModelPath(for: activeModel),
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FileManager.default.fileExists(atPath: modelPath.path) {
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do {
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try await whisperEngine.loadModel(at: modelPath)
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logger.info("Loaded user's selected model: \(activeModel.name)")
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await MainActor.run {
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updateMenuModelStatus()
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}
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} catch {
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logger.error("Failed to load selected model: \(error)")
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}
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} else {
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logger.info("No valid model selected - user needs to download and select a model")
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await MainActor.run {
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updateMenuModelStatus()
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}
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}
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}
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}
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deinit {
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cleanup()
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}
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@ -36,6 +86,11 @@ public class AppController: ObservableObject {
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public func start() {
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logger.info("Starting app controller")
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// Setup status item menu on main actor
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Task { @MainActor in
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setupStatusItemMenu()
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}
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// Check microphone permission first
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checkMicrophonePermission { [weak self] granted in
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if granted {
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@ -46,6 +101,78 @@ public class AppController: ObservableObject {
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}
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}
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@MainActor
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private func setupStatusItemMenu() {
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statusItem = NSStatusBar.system.statusItem(withLength: NSStatusItem.squareLength)
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statusItem?.button?.image = NSImage(systemSymbolName: "mic", accessibilityDescription: "MenuWhisper")
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statusItem?.button?.imagePosition = .imageOnly
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let menu = NSMenu()
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// Status item
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let statusMenuItem = NSMenuItem()
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statusMenuItem.title = "MenuWhisper"
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statusMenuItem.isEnabled = false
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menu.addItem(statusMenuItem)
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menu.addItem(NSMenuItem.separator())
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// Model status
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let modelMenuItem = NSMenuItem()
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modelMenuItem.title = "Loading model..."
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modelMenuItem.isEnabled = false
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menu.addItem(modelMenuItem)
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menu.addItem(NSMenuItem.separator())
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// Preferences
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let preferencesMenuItem = NSMenuItem(title: "Preferences...", action: #selector(openPreferences), keyEquivalent: ",")
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preferencesMenuItem.target = self
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menu.addItem(preferencesMenuItem)
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// Test item - add direct preferences shortcut
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let testPrefsMenuItem = NSMenuItem(title: "Open Preferences (⇧⌘P)", action: #selector(openPreferences), keyEquivalent: "P")
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testPrefsMenuItem.keyEquivalentModifierMask = [.shift, .command]
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testPrefsMenuItem.target = self
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menu.addItem(testPrefsMenuItem)
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// Quit
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let quitMenuItem = NSMenuItem(title: "Quit MenuWhisper", action: #selector(quitApp), keyEquivalent: "q")
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quitMenuItem.target = self
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menu.addItem(quitMenuItem)
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statusItem?.menu = menu
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// Update model status periodically
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updateMenuModelStatus()
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}
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@objc private func openPreferences() {
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Task { @MainActor in
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showPreferences()
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}
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}
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@objc private func quitApp() {
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NSApplication.shared.terminate(nil)
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}
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@MainActor
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private func updateMenuModelStatus() {
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guard let menu = statusItem?.menu,
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menu.items.count > 3 else { return }
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let modelMenuItem = menu.items[2] // Model status item
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if let activeModel = modelManager?.activeModel, whisperEngine.isModelLoaded() {
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modelMenuItem.title = "Model: \(activeModel.name)"
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} else if modelManager?.activeModel != nil {
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modelMenuItem.title = "Model: Loading..."
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} else {
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modelMenuItem.title = "No model - click Preferences"
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}
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}
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private func setupDelegates() {
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hotkeyManager.delegate = self
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audioEngine.delegate = self
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@ -83,6 +210,15 @@ public class AppController: ObservableObject {
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return
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}
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// Check if a model is loaded before starting
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guard whisperEngine.isModelLoaded() else {
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logger.warning("No model loaded - showing setup alert")
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Task { @MainActor in
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showModelSetupAlert()
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}
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return
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}
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logger.info("Starting listening")
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currentState = .listening
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@ -114,11 +250,7 @@ public class AppController: ObservableObject {
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currentState = .processing
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showHUD(state: .processing)
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// For Phase 1, we'll just simulate processing and return to idle
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// In Phase 2, this is where we'd call the STT engine
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DispatchQueue.main.asyncAfter(deadline: .now() + 1.0) {
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self.finishProcessing()
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}
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// The audio will be processed in the AudioEngine delegate when capture completes
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}
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private func finishProcessing() {
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@ -132,6 +264,57 @@ public class AppController: ObservableObject {
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}
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}
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private func performTranscription(audioData: Data) {
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logger.info("Starting STT transcription for \(audioData.count) bytes")
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Task {
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do {
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guard whisperEngine.isModelLoaded() else {
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logger.error("No model loaded for transcription")
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await showTranscriptionError("No speech recognition model loaded")
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return
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}
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let startTime = Date()
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let transcription = try await whisperEngine.transcribe(audioData: audioData, language: "auto")
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let duration = Date().timeIntervalSince(startTime)
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logger.info("Transcription completed in \(String(format: "%.2f", duration))s: \"\(transcription)\"")
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// For now, just print the result - in Phase 3 we'll inject it
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await MainActor.run {
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print("🎤 TRANSCRIPTION RESULT: \(transcription)")
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showTranscriptionResult(transcription)
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}
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} catch {
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logger.error("Transcription failed: \(error)")
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await showTranscriptionError("Speech recognition failed: \(error.localizedDescription)")
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}
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}
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}
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@MainActor
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private func showTranscriptionResult(_ text: String) {
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// For Phase 2, we'll just show it in logs and console
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// In Phase 3, this will inject the text into the active app
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logger.info("Transcription result: \(text)")
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finishProcessing()
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}
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@MainActor
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private func showTranscriptionError(_ message: String) {
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logger.error("Transcription error: \(message)")
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currentState = .error
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showError(message)
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// Return to idle after showing error
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DispatchQueue.main.asyncAfter(deadline: .now() + 2.0) {
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self.currentState = .idle
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self.hideHUD()
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}
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}
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private func cancelDictation() {
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logger.info("Cancelling dictation")
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stopDictationTimer()
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currentState = .idle
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}
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@MainActor
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public func showPreferences() {
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guard let modelManager = modelManager else {
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logger.error("ModelManager not initialized yet")
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return
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}
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if preferencesWindow == nil {
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preferencesWindow = PreferencesWindowController(
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modelManager: modelManager,
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whisperEngine: whisperEngine
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)
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}
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preferencesWindow?.showWindow(nil)
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preferencesWindow?.window?.makeKeyAndOrderFront(nil)
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NSApp.activate(ignoringOtherApps: true)
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}
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@MainActor
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private func showModelSetupAlert() {
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let alert = NSAlert()
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alert.messageText = "No Speech Recognition Model"
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alert.informativeText = "You need to download and select a speech recognition model before using MenuWhisper.\n\nWould you like to open Preferences to download a model?"
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alert.alertStyle = .informational
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alert.addButton(withTitle: "Open Preferences")
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alert.addButton(withTitle: "Cancel")
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let response = alert.runModal()
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if response == .alertFirstButtonReturn {
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showPreferences()
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}
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}
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private func cleanup() {
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stopDictationTimer()
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audioEngine.stopCapture()
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hotkeyManager.disableHotkey()
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preferencesWindow?.close()
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NotificationCenter.default.removeObserver(self)
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}
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}
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@ -226,7 +445,15 @@ extension AppController: AudioEngineDelegate {
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public func audioEngine(_ engine: AudioEngine, didCaptureAudio data: Data) {
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logger.info("Audio capture completed: \(data.count) bytes")
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// In Phase 2, this is where we'd send the data to STT
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// Only process if we're in the processing state
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guard currentState == .processing else {
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logger.warning("Ignoring audio data - not in processing state")
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return
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}
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// Perform STT transcription
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performTranscription(audioData: data)
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}
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public func audioEngineDidStartCapture(_ engine: AudioEngine) {
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@ -1,64 +1,26 @@
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import SwiftUI
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import CoreUtils
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@main
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struct MenuWhisperApp: App {
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@StateObject private var appController = AppController()
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class AppDelegate: NSObject, NSApplicationDelegate {
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private let appController = AppController()
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var body: some Scene {
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MenuBarExtra("Menu-Whisper", systemImage: "mic") {
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MenuBarContentView()
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.environmentObject(appController)
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.onAppear {
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appController.start()
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}
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}
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func applicationDidFinishLaunching(_ notification: Notification) {
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appController.start()
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}
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}
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struct MenuBarContentView: View {
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@EnvironmentObject var appController: AppController
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@main
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struct MenuWhisperApp: App {
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@NSApplicationDelegateAdaptor(AppDelegate.self) var appDelegate
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var body: some View {
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VStack(alignment: .leading, spacing: 4) {
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Text("Menu-Whisper")
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.font(.headline)
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Text(appController.currentState.displayName)
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.font(.subheadline)
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.foregroundColor(stateColor)
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if appController.currentState == .listening {
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Text("Press ⌘⇧V or Esc to stop")
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.font(.caption)
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.foregroundColor(.secondary)
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}
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Divider()
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Button("Preferences...") {
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// TODO: Open preferences window in Phase 4
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}
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Button("Quit") {
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NSApplication.shared.terminate(nil)
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}
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var body: some Scene {
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// Use a hidden window scene since we're using NSStatusItem for the menu bar
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WindowGroup {
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EmptyView()
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}
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.padding(.horizontal, 4)
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.windowStyle(.hiddenTitleBar)
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.windowResizability(.contentSize)
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.defaultSize(width: 0, height: 0)
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}
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}
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private var stateColor: Color {
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switch appController.currentState {
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case .idle:
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return .primary
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case .listening:
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return .blue
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case .processing:
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return .orange
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case .injecting:
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return .green
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case .error:
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return .red
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}
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}
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}
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342
Sources/App/PreferencesWindow.swift
Normal file
342
Sources/App/PreferencesWindow.swift
Normal file
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@ -0,0 +1,342 @@
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import SwiftUI
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import CoreModels
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import CoreSTT
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import CoreUtils
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class PreferencesWindowController: NSWindowController {
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private let modelManager: ModelManager
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private let whisperEngine: WhisperCPPEngine
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init(modelManager: ModelManager, whisperEngine: WhisperCPPEngine) {
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self.modelManager = modelManager
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self.whisperEngine = whisperEngine
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let window = NSWindow(
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contentRect: NSRect(x: 0, y: 0, width: 600, height: 500),
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styleMask: [.titled, .closable, .miniaturizable, .resizable],
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backing: .buffered,
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defer: false
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)
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super.init(window: window)
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window.title = "MenuWhisper Preferences"
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window.center()
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window.contentView = NSHostingView(
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rootView: PreferencesView(
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modelManager: modelManager,
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whisperEngine: whisperEngine,
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onClose: { [weak self] in
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self?.close()
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}
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)
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)
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}
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required init?(coder: NSCoder) {
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fatalError("init(coder:) has not been implemented")
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}
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}
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struct PreferencesView: View {
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@ObservedObject var modelManager: ModelManager
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let whisperEngine: WhisperCPPEngine
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let onClose: () -> Void
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@State private var selectedTab = 0
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@State private var isDownloading: [String: Bool] = [:]
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@State private var downloadProgress: [String: Double] = [:]
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@State private var showingDeleteAlert = false
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@State private var modelToDelete: ModelInfo?
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var body: some View {
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TabView(selection: $selectedTab) {
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ModelsTab(
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modelManager: modelManager,
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whisperEngine: whisperEngine,
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isDownloading: $isDownloading,
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downloadProgress: $downloadProgress,
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showingDeleteAlert: $showingDeleteAlert,
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modelToDelete: $modelToDelete
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)
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.tabItem {
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Label("Models", systemImage: "brain.head.profile")
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}
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.tag(0)
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GeneralTab()
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.tabItem {
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Label("General", systemImage: "gearshape")
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}
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.tag(1)
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}
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.frame(width: 600, height: 500)
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.alert("Delete Model", isPresented: $showingDeleteAlert) {
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Button("Cancel", role: .cancel) {
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modelToDelete = nil
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}
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Button("Delete", role: .destructive) {
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if let model = modelToDelete {
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deleteModel(model)
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}
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modelToDelete = nil
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}
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} message: {
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if let model = modelToDelete {
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Text("Are you sure you want to delete '\(model.name)'? This action cannot be undone.")
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}
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}
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}
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private func deleteModel(_ model: ModelInfo) {
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do {
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try modelManager.deleteModel(model)
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} catch {
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print("Failed to delete model: \(error)")
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}
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}
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}
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struct ModelsTab: View {
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@ObservedObject var modelManager: ModelManager
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let whisperEngine: WhisperCPPEngine
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@Binding var isDownloading: [String: Bool]
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@Binding var downloadProgress: [String: Double]
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@Binding var showingDeleteAlert: Bool
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@Binding var modelToDelete: ModelInfo?
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var body: some View {
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VStack(alignment: .leading, spacing: 16) {
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Text("Speech Recognition Models")
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.font(.title2)
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.fontWeight(.semibold)
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Text("Download and manage speech recognition models. Larger models provide better accuracy but use more memory and processing time.")
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.font(.caption)
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.foregroundColor(.secondary)
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// Current Model Status
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VStack(alignment: .leading, spacing: 8) {
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Text("Current Model")
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.font(.headline)
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if let activeModel = modelManager.activeModel {
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HStack {
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VStack(alignment: .leading) {
|
||||
Text(activeModel.name)
|
||||
.font(.body)
|
||||
.fontWeight(.medium)
|
||||
Text("\(activeModel.sizeMB) MB • \(activeModel.qualityTier) quality • \(activeModel.estimatedRAM)")
|
||||
.font(.caption)
|
||||
.foregroundColor(.secondary)
|
||||
}
|
||||
|
||||
Spacer()
|
||||
|
||||
Circle()
|
||||
.fill(whisperEngine.isModelLoaded() ? Color.green : Color.orange)
|
||||
.frame(width: 8, height: 8)
|
||||
|
||||
Text(whisperEngine.isModelLoaded() ? "Loaded" : "Loading...")
|
||||
.font(.caption)
|
||||
.foregroundColor(whisperEngine.isModelLoaded() ? .green : .orange)
|
||||
}
|
||||
.padding(12)
|
||||
.background(Color(NSColor.controlBackgroundColor))
|
||||
.cornerRadius(8)
|
||||
} else {
|
||||
Text("No model selected")
|
||||
.foregroundColor(.secondary)
|
||||
.padding(12)
|
||||
.frame(maxWidth: .infinity, alignment: .leading)
|
||||
.background(Color(NSColor.controlBackgroundColor))
|
||||
.cornerRadius(8)
|
||||
}
|
||||
}
|
||||
|
||||
// Available Models
|
||||
VStack(alignment: .leading, spacing: 8) {
|
||||
Text("Available Models")
|
||||
.font(.headline)
|
||||
|
||||
ScrollView {
|
||||
LazyVStack(spacing: 8) {
|
||||
ForEach(modelManager.availableModels) { model in
|
||||
ModelRow(
|
||||
model: model,
|
||||
modelManager: modelManager,
|
||||
whisperEngine: whisperEngine,
|
||||
isDownloading: isDownloading[model.name] ?? false,
|
||||
downloadProgress: downloadProgress[model.name] ?? 0.0,
|
||||
onDownload: {
|
||||
downloadModel(model)
|
||||
},
|
||||
onSelect: {
|
||||
selectModel(model)
|
||||
},
|
||||
onDelete: {
|
||||
modelToDelete = model
|
||||
showingDeleteAlert = true
|
||||
}
|
||||
)
|
||||
}
|
||||
}
|
||||
}
|
||||
.frame(maxHeight: 200)
|
||||
}
|
||||
|
||||
Spacer()
|
||||
}
|
||||
.padding(20)
|
||||
}
|
||||
|
||||
private func downloadModel(_ model: ModelInfo) {
|
||||
isDownloading[model.name] = true
|
||||
downloadProgress[model.name] = 0.0
|
||||
|
||||
Task {
|
||||
do {
|
||||
try await modelManager.downloadModel(model) { progress in
|
||||
DispatchQueue.main.async {
|
||||
downloadProgress[model.name] = progress.progress
|
||||
}
|
||||
}
|
||||
|
||||
DispatchQueue.main.async {
|
||||
isDownloading[model.name] = false
|
||||
downloadProgress[model.name] = 1.0
|
||||
}
|
||||
} catch {
|
||||
DispatchQueue.main.async {
|
||||
isDownloading[model.name] = false
|
||||
downloadProgress[model.name] = 0.0
|
||||
}
|
||||
print("Download failed: \(error)")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private func selectModel(_ model: ModelInfo) {
|
||||
modelManager.setActiveModel(model)
|
||||
|
||||
Task {
|
||||
do {
|
||||
if let modelPath = modelManager.getModelPath(for: model) {
|
||||
try await whisperEngine.loadModel(at: modelPath)
|
||||
}
|
||||
} catch {
|
||||
print("Failed to load model: \(error)")
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
struct ModelRow: View {
|
||||
let model: ModelInfo
|
||||
@ObservedObject var modelManager: ModelManager
|
||||
let whisperEngine: WhisperCPPEngine
|
||||
|
||||
let isDownloading: Bool
|
||||
let downloadProgress: Double
|
||||
let onDownload: () -> Void
|
||||
let onSelect: () -> Void
|
||||
let onDelete: () -> Void
|
||||
|
||||
private var isActive: Bool {
|
||||
modelManager.activeModel?.name == model.name
|
||||
}
|
||||
|
||||
var body: some View {
|
||||
HStack(spacing: 12) {
|
||||
VStack(alignment: .leading, spacing: 4) {
|
||||
HStack {
|
||||
Text(model.name)
|
||||
.font(.body)
|
||||
.fontWeight(.medium)
|
||||
|
||||
if isActive {
|
||||
Text("ACTIVE")
|
||||
.font(.caption)
|
||||
.fontWeight(.semibold)
|
||||
.foregroundColor(.white)
|
||||
.padding(.horizontal, 6)
|
||||
.padding(.vertical, 2)
|
||||
.background(Color.blue)
|
||||
.cornerRadius(4)
|
||||
}
|
||||
}
|
||||
|
||||
Text("\(model.sizeMB) MB • \(model.qualityTier) quality • \(model.estimatedRAM)")
|
||||
.font(.caption)
|
||||
.foregroundColor(.secondary)
|
||||
|
||||
if !model.notes.isEmpty {
|
||||
Text(model.notes)
|
||||
.font(.caption)
|
||||
.foregroundColor(.secondary)
|
||||
.lineLimit(2)
|
||||
}
|
||||
}
|
||||
|
||||
Spacer()
|
||||
|
||||
VStack(spacing: 8) {
|
||||
if model.isDownloaded {
|
||||
HStack(spacing: 8) {
|
||||
if !isActive {
|
||||
Button("Select") {
|
||||
onSelect()
|
||||
}
|
||||
.buttonStyle(.bordered)
|
||||
}
|
||||
|
||||
Button("Delete") {
|
||||
onDelete()
|
||||
}
|
||||
.buttonStyle(.bordered)
|
||||
.foregroundColor(.red)
|
||||
}
|
||||
} else {
|
||||
if isDownloading {
|
||||
VStack {
|
||||
ProgressView(value: downloadProgress)
|
||||
.frame(width: 80)
|
||||
Text("\(Int(downloadProgress * 100))%")
|
||||
.font(.caption)
|
||||
}
|
||||
} else {
|
||||
Button("Download") {
|
||||
onDownload()
|
||||
}
|
||||
.buttonStyle(.bordered)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
.padding(12)
|
||||
.background(isActive ? Color.blue.opacity(0.1) : Color(NSColor.controlBackgroundColor))
|
||||
.cornerRadius(8)
|
||||
.overlay(
|
||||
RoundedRectangle(cornerRadius: 8)
|
||||
.stroke(isActive ? Color.blue : Color.clear, lineWidth: 2)
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
struct GeneralTab: View {
|
||||
var body: some View {
|
||||
VStack(alignment: .leading, spacing: 16) {
|
||||
Text("General Settings")
|
||||
.font(.title2)
|
||||
.fontWeight(.semibold)
|
||||
|
||||
Text("Additional settings will be available in Phase 4.")
|
||||
.font(.body)
|
||||
.foregroundColor(.secondary)
|
||||
|
||||
Spacer()
|
||||
}
|
||||
.padding(20)
|
||||
}
|
||||
}
|
||||
36
Sources/App/Resources/Info.plist
Normal file
36
Sources/App/Resources/Info.plist
Normal file
|
|
@ -0,0 +1,36 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
|
||||
<plist version="1.0">
|
||||
<dict>
|
||||
<key>CFBundleDevelopmentRegion</key>
|
||||
<string>en</string>
|
||||
<key>CFBundleDisplayName</key>
|
||||
<string>Menu-Whisper</string>
|
||||
<key>CFBundleExecutable</key>
|
||||
<string>MenuWhisper</string>
|
||||
<key>CFBundleIdentifier</key>
|
||||
<string>com.menuwhisper.app</string>
|
||||
<key>CFBundleInfoDictionaryVersion</key>
|
||||
<string>6.0</string>
|
||||
<key>CFBundleName</key>
|
||||
<string>Menu-Whisper</string>
|
||||
<key>CFBundlePackageType</key>
|
||||
<string>APPL</string>
|
||||
<key>CFBundleShortVersionString</key>
|
||||
<string>1.0.0</string>
|
||||
<key>CFBundleVersion</key>
|
||||
<string>1</string>
|
||||
<key>LSMinimumSystemVersion</key>
|
||||
<string>13.0</string>
|
||||
<key>LSUIElement</key>
|
||||
<true/>
|
||||
<key>NSHumanReadableCopyright</key>
|
||||
<string>Copyright © 2025. All rights reserved.</string>
|
||||
<key>NSMicrophoneUsageDescription</key>
|
||||
<string>Menu-Whisper needs access to your microphone to capture speech for offline transcription. Your audio data never leaves your device.</string>
|
||||
<key>NSSupportsAutomaticTermination</key>
|
||||
<true/>
|
||||
<key>NSSupportsSuddenTermination</key>
|
||||
<false/>
|
||||
</dict>
|
||||
</plist>
|
||||
|
|
@ -0,0 +1,77 @@
|
|||
/* Menu-Whisper - English Localization */
|
||||
|
||||
/* General */
|
||||
"app.name" = "Menu-Whisper";
|
||||
"general.ok" = "OK";
|
||||
"general.cancel" = "Cancel";
|
||||
"general.continue" = "Continue";
|
||||
"general.settings" = "Settings";
|
||||
"general.quit" = "Quit";
|
||||
|
||||
/* Menu Bar */
|
||||
"menubar.idle" = "Idle";
|
||||
"menubar.listening" = "Listening";
|
||||
"menubar.processing" = "Processing";
|
||||
"menubar.preferences" = "Preferences...";
|
||||
"menubar.quit" = "Quit Menu-Whisper";
|
||||
|
||||
/* HUD States */
|
||||
"hud.listening" = "Listening...";
|
||||
"hud.processing" = "Transcribing...";
|
||||
"hud.cancel" = "Press Esc to cancel";
|
||||
|
||||
/* Permissions */
|
||||
"permissions.microphone.title" = "Microphone Access Required";
|
||||
"permissions.microphone.message" = "Menu-Whisper needs access to your microphone to perform speech-to-text transcription.";
|
||||
"permissions.accessibility.title" = "Accessibility Access Required";
|
||||
"permissions.accessibility.message" = "Menu-Whisper needs Accessibility access to insert transcribed text into applications.";
|
||||
"permissions.input_monitoring.title" = "Input Monitoring Required";
|
||||
"permissions.input_monitoring.message" = "Menu-Whisper needs Input Monitoring access to register global hotkeys.";
|
||||
"permissions.open_settings" = "Open System Settings";
|
||||
|
||||
/* Preferences Window */
|
||||
"preferences.title" = "Menu-Whisper Preferences";
|
||||
"preferences.general" = "General";
|
||||
"preferences.models" = "Models";
|
||||
"preferences.hotkeys" = "Hotkeys";
|
||||
"preferences.insertion" = "Text Insertion";
|
||||
"preferences.advanced" = "Advanced";
|
||||
|
||||
/* General Preferences */
|
||||
"preferences.general.hotkey" = "Global Hotkey:";
|
||||
"preferences.general.mode" = "Activation Mode:";
|
||||
"preferences.general.mode.push_to_talk" = "Push-to-talk";
|
||||
"preferences.general.mode.toggle" = "Toggle";
|
||||
"preferences.general.sounds" = "Play sounds for start/stop";
|
||||
"preferences.general.limit" = "Dictation time limit (minutes):";
|
||||
|
||||
/* Model Preferences */
|
||||
"preferences.models.title" = "Speech Recognition Models";
|
||||
"preferences.models.active" = "Active Model:";
|
||||
"preferences.models.language" = "Language:";
|
||||
"preferences.models.language.auto" = "Auto-detect";
|
||||
"preferences.models.download" = "Download";
|
||||
"preferences.models.delete" = "Delete";
|
||||
"preferences.models.size" = "Size:";
|
||||
"preferences.models.languages" = "Languages:";
|
||||
|
||||
/* Insertion Preferences */
|
||||
"preferences.insertion.method" = "Insertion Method:";
|
||||
"preferences.insertion.method.paste" = "Paste (⌘V)";
|
||||
"preferences.insertion.method.type" = "Type characters";
|
||||
"preferences.insertion.preview" = "Show preview before inserting";
|
||||
"preferences.insertion.secure_input" = "Secure Input Detected";
|
||||
"preferences.insertion.secure_input.message" = "Text insertion is disabled in secure contexts. Text has been copied to clipboard.";
|
||||
|
||||
/* Errors */
|
||||
"error.audio.failed" = "Failed to access microphone";
|
||||
"error.model.not_found" = "Speech recognition model not found";
|
||||
"error.model.load_failed" = "Failed to load speech recognition model";
|
||||
"error.transcription.failed" = "Speech transcription failed";
|
||||
"error.download.failed" = "Model download failed";
|
||||
"error.download.verification_failed" = "Model verification failed";
|
||||
|
||||
/* Success Messages */
|
||||
"success.model.downloaded" = "Model downloaded successfully";
|
||||
"success.settings.exported" = "Settings exported successfully";
|
||||
"success.settings.imported" = "Settings imported successfully";
|
||||
|
|
@ -0,0 +1,77 @@
|
|||
/* Menu-Whisper - Spanish Localization */
|
||||
|
||||
/* General */
|
||||
"app.name" = "Menu-Whisper";
|
||||
"general.ok" = "Aceptar";
|
||||
"general.cancel" = "Cancelar";
|
||||
"general.continue" = "Continuar";
|
||||
"general.settings" = "Configuración";
|
||||
"general.quit" = "Salir";
|
||||
|
||||
/* Menu Bar */
|
||||
"menubar.idle" = "Inactivo";
|
||||
"menubar.listening" = "Escuchando";
|
||||
"menubar.processing" = "Procesando";
|
||||
"menubar.preferences" = "Preferencias...";
|
||||
"menubar.quit" = "Salir de Menu-Whisper";
|
||||
|
||||
/* HUD States */
|
||||
"hud.listening" = "Escuchando...";
|
||||
"hud.processing" = "Transcribiendo...";
|
||||
"hud.cancel" = "Presiona Esc para cancelar";
|
||||
|
||||
/* Permissions */
|
||||
"permissions.microphone.title" = "Acceso al Micrófono Requerido";
|
||||
"permissions.microphone.message" = "Menu-Whisper necesita acceso a tu micrófono para realizar la transcripción de voz a texto.";
|
||||
"permissions.accessibility.title" = "Acceso de Accesibilidad Requerido";
|
||||
"permissions.accessibility.message" = "Menu-Whisper necesita acceso de Accesibilidad para insertar texto transcrito en aplicaciones.";
|
||||
"permissions.input_monitoring.title" = "Monitoreo de Entrada Requerido";
|
||||
"permissions.input_monitoring.message" = "Menu-Whisper necesita acceso de Monitoreo de Entrada para registrar atajos de teclado globales.";
|
||||
"permissions.open_settings" = "Abrir Configuración del Sistema";
|
||||
|
||||
/* Preferences Window */
|
||||
"preferences.title" = "Preferencias de Menu-Whisper";
|
||||
"preferences.general" = "General";
|
||||
"preferences.models" = "Modelos";
|
||||
"preferences.hotkeys" = "Atajos";
|
||||
"preferences.insertion" = "Inserción de Texto";
|
||||
"preferences.advanced" = "Avanzado";
|
||||
|
||||
/* General Preferences */
|
||||
"preferences.general.hotkey" = "Atajo Global:";
|
||||
"preferences.general.mode" = "Modo de Activación:";
|
||||
"preferences.general.mode.push_to_talk" = "Presionar para hablar";
|
||||
"preferences.general.mode.toggle" = "Alternar";
|
||||
"preferences.general.sounds" = "Reproducir sonidos al iniciar/detener";
|
||||
"preferences.general.limit" = "Límite de tiempo de dictado (minutos):";
|
||||
|
||||
/* Model Preferences */
|
||||
"preferences.models.title" = "Modelos de Reconocimiento de Voz";
|
||||
"preferences.models.active" = "Modelo Activo:";
|
||||
"preferences.models.language" = "Idioma:";
|
||||
"preferences.models.language.auto" = "Detección automática";
|
||||
"preferences.models.download" = "Descargar";
|
||||
"preferences.models.delete" = "Eliminar";
|
||||
"preferences.models.size" = "Tamaño:";
|
||||
"preferences.models.languages" = "Idiomas:";
|
||||
|
||||
/* Insertion Preferences */
|
||||
"preferences.insertion.method" = "Método de Inserción:";
|
||||
"preferences.insertion.method.paste" = "Pegar (⌘V)";
|
||||
"preferences.insertion.method.type" = "Escribir caracteres";
|
||||
"preferences.insertion.preview" = "Mostrar vista previa antes de insertar";
|
||||
"preferences.insertion.secure_input" = "Entrada Segura Detectada";
|
||||
"preferences.insertion.secure_input.message" = "La inserción de texto está deshabilitada en contextos seguros. El texto se ha copiado al portapapeles.";
|
||||
|
||||
/* Errors */
|
||||
"error.audio.failed" = "Error al acceder al micrófono";
|
||||
"error.model.not_found" = "Modelo de reconocimiento de voz no encontrado";
|
||||
"error.model.load_failed" = "Error al cargar el modelo de reconocimiento de voz";
|
||||
"error.transcription.failed" = "Error en la transcripción de voz";
|
||||
"error.download.failed" = "Error en la descarga del modelo";
|
||||
"error.download.verification_failed" = "Error en la verificación del modelo";
|
||||
|
||||
/* Success Messages */
|
||||
"success.model.downloaded" = "Modelo descargado exitosamente";
|
||||
"success.settings.exported" = "Configuración exportada exitosamente";
|
||||
"success.settings.imported" = "Configuración importada exitosamente";
|
||||
160
Sources/App/Resources/model-catalog.json
Normal file
160
Sources/App/Resources/model-catalog.json
Normal file
|
|
@ -0,0 +1,160 @@
|
|||
{
|
||||
"models": [
|
||||
{
|
||||
"name": "whisper-tiny",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 39,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "tiny",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin",
|
||||
"notes": "Fastest model, suitable for real-time applications with basic accuracy."
|
||||
},
|
||||
{
|
||||
"name": "whisper-tiny.en",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 39,
|
||||
"languages": ["en"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "tiny",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en.bin",
|
||||
"notes": "English-only tiny model, slightly more accurate for English than multilingual tiny."
|
||||
},
|
||||
{
|
||||
"name": "whisper-base",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 142,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "base",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin",
|
||||
"notes": "Good balance of speed and accuracy, recommended for most use cases."
|
||||
},
|
||||
{
|
||||
"name": "whisper-base.en",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 142,
|
||||
"languages": ["en"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "base",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin",
|
||||
"notes": "English-only base model, optimal for English-only applications."
|
||||
},
|
||||
{
|
||||
"name": "whisper-small",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 466,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "small",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.bin",
|
||||
"notes": "Excellent balance of speed and accuracy for M1/M2/M3 machines."
|
||||
},
|
||||
{
|
||||
"name": "whisper-small.en",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 466,
|
||||
"languages": ["en"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "small",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en.bin",
|
||||
"notes": "English-only small model, high accuracy for English-only use."
|
||||
},
|
||||
{
|
||||
"name": "whisper-medium",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 1540,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "medium",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.bin",
|
||||
"notes": "Higher accuracy but slower, requires more RAM (2-3GB)."
|
||||
},
|
||||
{
|
||||
"name": "whisper-medium.en",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 1540,
|
||||
"languages": ["en"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "medium",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en.bin",
|
||||
"notes": "English-only medium model, very high accuracy for English."
|
||||
},
|
||||
{
|
||||
"name": "whisper-large-v2",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 3090,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "large",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2.bin",
|
||||
"notes": "Highest accuracy but slowest, requires significant RAM (4-5GB)."
|
||||
},
|
||||
{
|
||||
"name": "whisper-large-v3",
|
||||
"family": "OpenAI-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 3090,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "large",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin",
|
||||
"notes": "Latest large model with improved accuracy, requires significant RAM (4-5GB)."
|
||||
},
|
||||
{
|
||||
"name": "distil-whisper-large-v2",
|
||||
"family": "Distil-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 1540,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "large",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/distil-whisper/distil-large-v2/resolve/main/ggml-distil-large-v2.bin",
|
||||
"notes": "Distilled large model, 2x faster than large-v2 with similar accuracy."
|
||||
},
|
||||
{
|
||||
"name": "distil-whisper-large-v3",
|
||||
"family": "Distil-Whisper",
|
||||
"format": "bin",
|
||||
"size_mb": 1540,
|
||||
"languages": ["multilingual"],
|
||||
"recommended_backend": "whisper.cpp",
|
||||
"quality_tier": "large",
|
||||
"license": "MIT",
|
||||
"sha256": "",
|
||||
"download_url": "https://huggingface.co/distil-whisper/distil-large-v3/resolve/main/ggml-distil-large-v3.bin",
|
||||
"notes": "Latest distilled model, excellent balance of speed and accuracy."
|
||||
}
|
||||
]
|
||||
}
|
||||
|
|
@ -1,5 +1,6 @@
|
|||
import Foundation
|
||||
import CoreUtils
|
||||
import CryptoKit
|
||||
|
||||
public struct ModelInfo: Codable, Identifiable {
|
||||
public let id = UUID()
|
||||
|
|
@ -22,49 +23,401 @@ public struct ModelInfo: Codable, Identifiable {
|
|||
case qualityTier = "quality_tier"
|
||||
case downloadURL = "download_url"
|
||||
}
|
||||
|
||||
public var fileURL: URL {
|
||||
let appSupport = FileManager.default.urls(for: .applicationSupportDirectory, in: .userDomainMask).first!
|
||||
let modelsDirectory = appSupport.appendingPathComponent("MenuWhisper/Models")
|
||||
return modelsDirectory.appendingPathComponent(filename)
|
||||
}
|
||||
|
||||
public var filename: String {
|
||||
return "\(name).bin"
|
||||
}
|
||||
|
||||
public var isDownloaded: Bool {
|
||||
return FileManager.default.fileExists(atPath: fileURL.path)
|
||||
}
|
||||
|
||||
public var estimatedRAM: String {
|
||||
switch qualityTier {
|
||||
case "tiny":
|
||||
return "~0.5GB"
|
||||
case "base":
|
||||
return "~1GB"
|
||||
case "small":
|
||||
return "~1.5-2GB"
|
||||
case "medium":
|
||||
return "~2-3GB"
|
||||
case "large":
|
||||
return "~4-5GB"
|
||||
default:
|
||||
return "Unknown"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public struct ModelCatalog: Codable {
|
||||
public let models: [ModelInfo]
|
||||
}
|
||||
|
||||
public struct DownloadProgress {
|
||||
public let bytesDownloaded: Int64
|
||||
public let totalBytes: Int64
|
||||
public let progress: Double
|
||||
|
||||
public var progressText: String {
|
||||
let downloaded = ByteCountFormatter.string(fromByteCount: bytesDownloaded, countStyle: .binary)
|
||||
let total = ByteCountFormatter.string(fromByteCount: totalBytes, countStyle: .binary)
|
||||
return "\(downloaded) / \(total)"
|
||||
}
|
||||
}
|
||||
|
||||
public enum ModelError: Error, LocalizedError {
|
||||
case catalogNotFound
|
||||
case invalidCatalog
|
||||
case downloadFailed(String)
|
||||
case checksumMismatch
|
||||
case diskSpaceInsufficient
|
||||
case modelNotFound
|
||||
case deleteFailed(String)
|
||||
|
||||
public var errorDescription: String? {
|
||||
switch self {
|
||||
case .catalogNotFound:
|
||||
return "Model catalog not found"
|
||||
case .invalidCatalog:
|
||||
return "Invalid model catalog format"
|
||||
case .downloadFailed(let reason):
|
||||
return "Download failed: \(reason)"
|
||||
case .checksumMismatch:
|
||||
return "Downloaded file checksum does not match expected value"
|
||||
case .diskSpaceInsufficient:
|
||||
return "Insufficient disk space to download model"
|
||||
case .modelNotFound:
|
||||
return "Model file not found"
|
||||
case .deleteFailed(let reason):
|
||||
return "Failed to delete model: \(reason)"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@MainActor
|
||||
public class ModelManager: ObservableObject {
|
||||
private let logger = Logger(category: "ModelManager")
|
||||
|
||||
@Published public private(set) var availableModels: [ModelInfo] = []
|
||||
@Published public private(set) var downloadedModels: [ModelInfo] = []
|
||||
@Published public private(set) var activeModel: ModelInfo?
|
||||
@Published public private(set) var downloadProgress: [String: DownloadProgress] = [:]
|
||||
|
||||
private let modelsDirectory: URL
|
||||
private let urlSession: URLSession
|
||||
private var downloadTasks: [String: URLSessionDownloadTask] = [:]
|
||||
|
||||
public init() {
|
||||
let appSupport = FileManager.default.urls(for: .applicationSupportDirectory, in: .userDomainMask).first!
|
||||
modelsDirectory = appSupport.appendingPathComponent("MenuWhisper/Models")
|
||||
|
||||
// Configure URLSession for downloads
|
||||
let config = URLSessionConfiguration.default
|
||||
config.timeoutIntervalForRequest = 30
|
||||
config.timeoutIntervalForResource = 3600 // 1 hour for large model downloads
|
||||
urlSession = URLSession(configuration: config)
|
||||
|
||||
try? FileManager.default.createDirectory(at: modelsDirectory, withIntermediateDirectories: true)
|
||||
|
||||
// Ensure we have models available - use fallback approach first
|
||||
createFallbackCatalog()
|
||||
|
||||
// Try to load from JSON file as well
|
||||
loadModelCatalog()
|
||||
|
||||
refreshDownloadedModels()
|
||||
loadActiveModelPreference()
|
||||
}
|
||||
|
||||
public func downloadModel(_ model: ModelInfo) async throws {
|
||||
deinit {
|
||||
// Cancel any active downloads
|
||||
downloadTasks.values.forEach { $0.cancel() }
|
||||
}
|
||||
|
||||
public func downloadModel(_ model: ModelInfo, progressCallback: @escaping (DownloadProgress) -> Void = { _ in }) async throws {
|
||||
logger.info("Starting download for model: \(model.name)")
|
||||
// TODO: Implement model download with progress tracking and SHA256 verification in Phase 2
|
||||
|
||||
// Check if already downloaded
|
||||
if model.isDownloaded {
|
||||
logger.info("Model \(model.name) already downloaded")
|
||||
return
|
||||
}
|
||||
|
||||
// Download both .bin and .mlmodelc files
|
||||
try await downloadModelFile(model, progressCallback: progressCallback)
|
||||
try await downloadCoreMlEncoder(model)
|
||||
|
||||
// Refresh downloaded models list
|
||||
refreshDownloadedModels()
|
||||
logger.info("Model \(model.name) downloaded completely with Core ML support")
|
||||
}
|
||||
|
||||
private func downloadModelFile(_ model: ModelInfo, progressCallback: @escaping (DownloadProgress) -> Void = { _ in }) async throws {
|
||||
// Check disk space
|
||||
let requiredSpace = Int64(model.sizeMB) * 1024 * 1024
|
||||
let availableSpace = try getAvailableDiskSpace()
|
||||
|
||||
if availableSpace < requiredSpace * 2 { // Need 2x space for download + final file
|
||||
throw ModelError.diskSpaceInsufficient
|
||||
}
|
||||
|
||||
guard let url = URL(string: model.downloadURL) else {
|
||||
throw ModelError.downloadFailed("Invalid download URL")
|
||||
}
|
||||
|
||||
// Create temporary file for download
|
||||
let tempURL = modelsDirectory.appendingPathComponent("\(model.name).tmp")
|
||||
|
||||
do {
|
||||
let (tempFileURL, response) = try await urlSession.download(from: url)
|
||||
|
||||
guard let httpResponse = response as? HTTPURLResponse,
|
||||
(200..<300).contains(httpResponse.statusCode) else {
|
||||
throw ModelError.downloadFailed("HTTP error: \(String(describing: (response as? HTTPURLResponse)?.statusCode))")
|
||||
}
|
||||
|
||||
// Verify SHA256 checksum if provided
|
||||
if !model.sha256.isEmpty {
|
||||
try await verifyChecksum(fileURL: tempFileURL, expectedSHA256: model.sha256)
|
||||
}
|
||||
|
||||
// Move to final location
|
||||
if FileManager.default.fileExists(atPath: model.fileURL.path) {
|
||||
try FileManager.default.removeItem(at: model.fileURL)
|
||||
}
|
||||
|
||||
try FileManager.default.moveItem(at: tempFileURL, to: model.fileURL)
|
||||
logger.info("Model file \(model.name).bin downloaded successfully")
|
||||
|
||||
} catch {
|
||||
// Clean up temp files on error
|
||||
try? FileManager.default.removeItem(at: tempURL)
|
||||
throw ModelError.downloadFailed(error.localizedDescription)
|
||||
}
|
||||
}
|
||||
|
||||
private func downloadCoreMlEncoder(_ model: ModelInfo) async throws {
|
||||
// Map model names to Core ML encoder URLs
|
||||
let encoderURLString: String
|
||||
switch model.name {
|
||||
case "whisper-tiny":
|
||||
encoderURLString = "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny-encoder.mlmodelc.zip"
|
||||
case "whisper-base":
|
||||
encoderURLString = "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base-encoder.mlmodelc.zip"
|
||||
case "whisper-small":
|
||||
encoderURLString = "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small-encoder.mlmodelc.zip"
|
||||
default:
|
||||
logger.info("No Core ML encoder available for \(model.name)")
|
||||
return
|
||||
}
|
||||
|
||||
guard let encoderURL = URL(string: encoderURLString) else {
|
||||
logger.warning("Invalid Core ML encoder URL for \(model.name)")
|
||||
return
|
||||
}
|
||||
|
||||
do {
|
||||
logger.info("Downloading Core ML encoder for \(model.name)")
|
||||
let (tempFileURL, response) = try await urlSession.download(from: encoderURL)
|
||||
|
||||
guard let httpResponse = response as? HTTPURLResponse,
|
||||
(200..<300).contains(httpResponse.statusCode) else {
|
||||
logger.warning("Core ML encoder download failed for \(model.name)")
|
||||
return
|
||||
}
|
||||
|
||||
// Extract zip to models directory
|
||||
let encoderName = "\(model.name)-encoder.mlmodelc"
|
||||
let encoderPath = modelsDirectory.appendingPathComponent(encoderName)
|
||||
|
||||
// Remove existing encoder if present
|
||||
if FileManager.default.fileExists(atPath: encoderPath.path) {
|
||||
try? FileManager.default.removeItem(at: encoderPath)
|
||||
}
|
||||
|
||||
// Unzip the Core ML model
|
||||
let process = Process()
|
||||
process.executableURL = URL(fileURLWithPath: "/usr/bin/unzip")
|
||||
process.arguments = ["-q", tempFileURL.path, "-d", modelsDirectory.path]
|
||||
|
||||
try process.run()
|
||||
process.waitUntilExit()
|
||||
|
||||
// Rename from ggml-*-encoder.mlmodelc to whisper-*-encoder.mlmodelc
|
||||
let extractedPath = modelsDirectory.appendingPathComponent("ggml-\(model.name.replacingOccurrences(of: "whisper-", with: ""))-encoder.mlmodelc")
|
||||
if FileManager.default.fileExists(atPath: extractedPath.path) {
|
||||
try FileManager.default.moveItem(at: extractedPath, to: encoderPath)
|
||||
logger.info("Core ML encoder for \(model.name) installed successfully")
|
||||
}
|
||||
|
||||
} catch {
|
||||
logger.warning("Failed to download Core ML encoder for \(model.name): \(error)")
|
||||
// Don't throw - Core ML is optional, model will work without it
|
||||
}
|
||||
}
|
||||
|
||||
public func cancelDownload(for model: ModelInfo) {
|
||||
if let task = downloadTasks[model.name] {
|
||||
task.cancel()
|
||||
downloadTasks.removeValue(forKey: model.name)
|
||||
downloadProgress.removeValue(forKey: model.name)
|
||||
logger.info("Cancelled download for model: \(model.name)")
|
||||
}
|
||||
}
|
||||
|
||||
public func deleteModel(_ model: ModelInfo) throws {
|
||||
logger.info("Deleting model: \(model.name)")
|
||||
// TODO: Implement model deletion in Phase 2
|
||||
|
||||
guard model.isDownloaded else {
|
||||
throw ModelError.modelNotFound
|
||||
}
|
||||
|
||||
do {
|
||||
try FileManager.default.removeItem(at: model.fileURL)
|
||||
logger.info("Model \(model.name) deleted successfully")
|
||||
|
||||
// Clear active model if it was the deleted one
|
||||
if activeModel?.name == model.name {
|
||||
activeModel = nil
|
||||
saveActiveModelPreference()
|
||||
}
|
||||
|
||||
refreshDownloadedModels()
|
||||
} catch {
|
||||
logger.error("Failed to delete model \(model.name): \(error)")
|
||||
throw ModelError.deleteFailed(error.localizedDescription)
|
||||
}
|
||||
}
|
||||
|
||||
public func setActiveModel(_ model: ModelInfo) {
|
||||
logger.info("Setting active model: \(model.name)")
|
||||
public func setActiveModel(_ model: ModelInfo?) {
|
||||
logger.info("Setting active model: \(model?.name ?? "none")")
|
||||
activeModel = model
|
||||
// TODO: Persist active model selection in Phase 2
|
||||
saveActiveModelPreference()
|
||||
}
|
||||
|
||||
public func getModelPath(for model: ModelInfo) -> URL? {
|
||||
guard model.isDownloaded else { return nil }
|
||||
return model.fileURL
|
||||
}
|
||||
|
||||
private func verifyChecksum(fileURL: URL, expectedSHA256: String) async throws {
|
||||
let data = try Data(contentsOf: fileURL)
|
||||
let hash = SHA256.hash(data: data)
|
||||
let hashString = hash.compactMap { String(format: "%02x", $0) }.joined()
|
||||
|
||||
if hashString.lowercased() != expectedSHA256.lowercased() {
|
||||
logger.error("Checksum mismatch: expected \(expectedSHA256), got \(hashString)")
|
||||
throw ModelError.checksumMismatch
|
||||
}
|
||||
}
|
||||
|
||||
private func getAvailableDiskSpace() throws -> Int64 {
|
||||
let attributes = try FileManager.default.attributesOfFileSystem(forPath: modelsDirectory.path)
|
||||
return attributes[.systemFreeSize] as? Int64 ?? 0
|
||||
}
|
||||
|
||||
private func loadModelCatalog() {
|
||||
// TODO: Load curated model catalog from bundled JSON in Phase 2
|
||||
logger.info("Loading model catalog")
|
||||
// Try to load additional models from JSON file if available
|
||||
if let catalogURL = Bundle.main.url(forResource: "model-catalog", withExtension: "json") {
|
||||
loadCatalogFromURL(catalogURL)
|
||||
} else if let resourcePath = Bundle.main.resourcePath {
|
||||
let resourceCatalog = URL(fileURLWithPath: resourcePath).appendingPathComponent("model-catalog.json")
|
||||
if FileManager.default.fileExists(atPath: resourceCatalog.path) {
|
||||
loadCatalogFromURL(resourceCatalog)
|
||||
}
|
||||
}
|
||||
// Note: Fallback catalog already created, so JSON is optional enhancement
|
||||
}
|
||||
|
||||
private func createFallbackCatalog() {
|
||||
// Create a minimal set of models without requiring the JSON file
|
||||
availableModels = [
|
||||
ModelInfo(
|
||||
name: "whisper-tiny",
|
||||
family: "OpenAI-Whisper",
|
||||
format: "bin",
|
||||
sizeMB: 89, // Updated to include Core ML encoder size
|
||||
languages: ["multilingual"],
|
||||
recommendedBackend: "whisper.cpp",
|
||||
qualityTier: "tiny",
|
||||
license: "MIT",
|
||||
sha256: "",
|
||||
downloadURL: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin",
|
||||
notes: "Fastest model, suitable for real-time applications. Includes Core ML acceleration."
|
||||
),
|
||||
ModelInfo(
|
||||
name: "whisper-base",
|
||||
family: "OpenAI-Whisper",
|
||||
format: "bin",
|
||||
sizeMB: 192, // Updated to include Core ML encoder size
|
||||
languages: ["multilingual"],
|
||||
recommendedBackend: "whisper.cpp",
|
||||
qualityTier: "base",
|
||||
license: "MIT",
|
||||
sha256: "",
|
||||
downloadURL: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin",
|
||||
notes: "Good balance of speed and accuracy. Includes Core ML acceleration."
|
||||
),
|
||||
ModelInfo(
|
||||
name: "whisper-small",
|
||||
family: "OpenAI-Whisper",
|
||||
format: "bin",
|
||||
sizeMB: 516, // Updated to include Core ML encoder size
|
||||
languages: ["multilingual"],
|
||||
recommendedBackend: "whisper.cpp",
|
||||
qualityTier: "small",
|
||||
license: "MIT",
|
||||
sha256: "",
|
||||
downloadURL: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.bin",
|
||||
notes: "Excellent balance of speed and accuracy. Includes Core ML acceleration."
|
||||
)
|
||||
]
|
||||
logger.info("Created fallback catalog with \(availableModels.count) models")
|
||||
}
|
||||
|
||||
private func loadCatalogFromURL(_ url: URL) {
|
||||
do {
|
||||
let data = try Data(contentsOf: url)
|
||||
let catalog = try JSONDecoder().decode(ModelCatalog.self, from: data)
|
||||
availableModels = catalog.models
|
||||
logger.info("Loaded \(availableModels.count) models from catalog")
|
||||
} catch {
|
||||
logger.error("Failed to load model catalog from \(url.path): \(error)")
|
||||
}
|
||||
}
|
||||
|
||||
private func refreshDownloadedModels() {
|
||||
// TODO: Scan models directory and populate downloadedModels in Phase 2
|
||||
logger.info("Refreshing downloaded models")
|
||||
|
||||
downloadedModels = availableModels.filter { $0.isDownloaded }
|
||||
logger.info("Found \(downloadedModels.count) downloaded models")
|
||||
}
|
||||
|
||||
private func saveActiveModelPreference() {
|
||||
if let activeModel = activeModel {
|
||||
UserDefaults.standard.set(activeModel.name, forKey: "MenuWhisper.ActiveModel")
|
||||
} else {
|
||||
UserDefaults.standard.removeObject(forKey: "MenuWhisper.ActiveModel")
|
||||
}
|
||||
}
|
||||
|
||||
private func loadActiveModelPreference() {
|
||||
guard let modelName = UserDefaults.standard.string(forKey: "MenuWhisper.ActiveModel") else {
|
||||
return
|
||||
}
|
||||
|
||||
activeModel = availableModels.first { $0.name == modelName && $0.isDownloaded }
|
||||
|
||||
if activeModel == nil {
|
||||
// Clear preference if model is no longer available or downloaded
|
||||
UserDefaults.standard.removeObject(forKey: "MenuWhisper.ActiveModel")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -1,35 +1,181 @@
|
|||
import Foundation
|
||||
import CoreUtils
|
||||
import SwiftWhisper
|
||||
|
||||
public class WhisperCPPEngine: STTEngine {
|
||||
private let logger = Logger(category: "WhisperCPPEngine")
|
||||
private var modelPath: URL?
|
||||
private var isLoaded = false
|
||||
private var whisperInstance: Whisper?
|
||||
|
||||
public init() {
|
||||
// WhisperCPP integration will be implemented in Phase 2
|
||||
// Configuration
|
||||
private let numThreads: Int
|
||||
private let useGPU: Bool
|
||||
private var language: WhisperLanguage = .auto
|
||||
|
||||
public init(numThreads: Int = 0, useGPU: Bool = true) {
|
||||
self.numThreads = numThreads <= 0 ? min(8, max(1, ProcessInfo.processInfo.processorCount)) : numThreads
|
||||
self.useGPU = useGPU
|
||||
}
|
||||
|
||||
deinit {
|
||||
unloadModel()
|
||||
}
|
||||
|
||||
public func transcribe(audioData: Data, language: String?) async throws -> String {
|
||||
logger.info("Transcribing audio data")
|
||||
// TODO: Implement whisper.cpp integration in Phase 2
|
||||
throw STTError.transcriptionFailed("Not implemented yet")
|
||||
logger.info("Transcribing audio data of size: \(audioData.count) bytes")
|
||||
|
||||
guard let whisper = whisperInstance, isLoaded else {
|
||||
throw STTError.modelNotFound
|
||||
}
|
||||
|
||||
do {
|
||||
// Set language if specified
|
||||
if let language = language {
|
||||
setLanguage(language)
|
||||
}
|
||||
|
||||
// Convert audio data to float array
|
||||
let audioFrames = try convertAudioDataToFloats(audioData)
|
||||
logger.info("Converted audio to \(audioFrames.count) float samples")
|
||||
|
||||
// Perform transcription
|
||||
let segments = try await whisper.transcribe(audioFrames: audioFrames)
|
||||
|
||||
// Combine all segment texts
|
||||
let fullTranscription = segments.map { $0.text }.joined()
|
||||
let cleanedText = normalizeText(fullTranscription)
|
||||
|
||||
logger.info("Transcription completed, length: \(cleanedText.count) characters")
|
||||
return cleanedText
|
||||
|
||||
} catch let whisperError as WhisperError {
|
||||
logger.error("SwiftWhisper error: \(whisperError)")
|
||||
throw mapWhisperError(whisperError)
|
||||
} catch {
|
||||
logger.error("Transcription error: \(error)")
|
||||
throw STTError.transcriptionFailed(error.localizedDescription)
|
||||
}
|
||||
}
|
||||
|
||||
private func setLanguage(_ languageCode: String) {
|
||||
let whisperLanguage: WhisperLanguage
|
||||
|
||||
switch languageCode.lowercased() {
|
||||
case "auto":
|
||||
whisperLanguage = .auto
|
||||
case "en", "english":
|
||||
whisperLanguage = .english
|
||||
case "es", "spanish":
|
||||
whisperLanguage = .spanish
|
||||
case "fr", "french":
|
||||
whisperLanguage = .french
|
||||
case "de", "german":
|
||||
whisperLanguage = .german
|
||||
case "it", "italian":
|
||||
whisperLanguage = .italian
|
||||
case "pt", "portuguese":
|
||||
whisperLanguage = .portuguese
|
||||
case "ja", "japanese":
|
||||
whisperLanguage = .japanese
|
||||
case "ko", "korean":
|
||||
whisperLanguage = .korean
|
||||
case "zh", "chinese":
|
||||
whisperLanguage = .chinese
|
||||
case "ru", "russian":
|
||||
whisperLanguage = .russian
|
||||
default:
|
||||
logger.warning("Unknown language code: \(languageCode), using auto-detection")
|
||||
whisperLanguage = .auto
|
||||
}
|
||||
|
||||
self.language = whisperLanguage
|
||||
whisperInstance?.params.language = whisperLanguage
|
||||
}
|
||||
|
||||
private func mapWhisperError(_ error: WhisperError) -> STTError {
|
||||
switch error {
|
||||
case .instanceBusy:
|
||||
return STTError.transcriptionFailed("Whisper instance is busy")
|
||||
case .invalidFrames:
|
||||
return STTError.invalidAudioData
|
||||
case .cancelled:
|
||||
return STTError.transcriptionFailed("Transcription was cancelled")
|
||||
case .cancellationError(let cancellationError):
|
||||
return STTError.transcriptionFailed("Cancellation error: \(cancellationError)")
|
||||
}
|
||||
}
|
||||
|
||||
private func convertAudioDataToFloats(_ audioData: Data) throws -> [Float] {
|
||||
guard audioData.count % 2 == 0 else {
|
||||
throw STTError.invalidAudioData
|
||||
}
|
||||
|
||||
let sampleCount = audioData.count / 2
|
||||
var samples: [Float] = []
|
||||
samples.reserveCapacity(sampleCount)
|
||||
|
||||
audioData.withUnsafeBytes { bytes in
|
||||
let int16Samples = bytes.bindMemory(to: Int16.self)
|
||||
for sample in int16Samples {
|
||||
// Convert Int16 to Float in range [-1.0, 1.0]
|
||||
samples.append(Float(sample) / 32768.0)
|
||||
}
|
||||
}
|
||||
|
||||
return samples
|
||||
}
|
||||
|
||||
private func normalizeText(_ text: String) -> String {
|
||||
return text
|
||||
.trimmingCharacters(in: .whitespacesAndNewlines)
|
||||
.replacingOccurrences(of: " ", with: " ")
|
||||
.replacingOccurrences(of: "\u{201C}", with: "\"")
|
||||
.replacingOccurrences(of: "\u{201D}", with: "\"")
|
||||
.replacingOccurrences(of: "\u{2018}", with: "'")
|
||||
.replacingOccurrences(of: "\u{2019}", with: "'")
|
||||
.replacingOccurrences(of: "—", with: "-")
|
||||
.replacingOccurrences(of: "–", with: "-")
|
||||
}
|
||||
|
||||
public func isModelLoaded() -> Bool {
|
||||
return isLoaded
|
||||
return isLoaded && whisperInstance != nil
|
||||
}
|
||||
|
||||
public func loadModel(at path: URL) async throws {
|
||||
logger.info("Loading model at path: \(path.path)")
|
||||
|
||||
// Unload existing model first
|
||||
unloadModel()
|
||||
|
||||
guard FileManager.default.fileExists(atPath: path.path) else {
|
||||
throw STTError.modelNotFound
|
||||
}
|
||||
|
||||
// Create WhisperParams with our configuration
|
||||
let params = WhisperParams(strategy: .greedy)
|
||||
params.language = language
|
||||
|
||||
// Configure additional params if needed
|
||||
params.n_threads = Int32(numThreads)
|
||||
|
||||
// Initialize SwiftWhisper instance
|
||||
let whisper = Whisper(fromFileURL: path, withParams: params)
|
||||
|
||||
self.whisperInstance = whisper
|
||||
self.modelPath = path
|
||||
// TODO: Implement model loading in Phase 2
|
||||
isLoaded = true
|
||||
self.isLoaded = true
|
||||
|
||||
logger.info("Model loaded successfully with SwiftWhisper")
|
||||
}
|
||||
|
||||
public func unloadModel() {
|
||||
logger.info("Unloading model")
|
||||
|
||||
whisperInstance = nil
|
||||
modelPath = nil
|
||||
isLoaded = false
|
||||
|
||||
logger.info("Model unloaded")
|
||||
}
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue