public enum ModelVariant: CustomStringConvertible {
    case tiny
    case tinyEn
    case base
    case baseEn
    case small
    case smallEn
    case medium
    case mediumEn
    case large
    case largev2
    case largev3
    
    var isMultilingual: Bool {
        // Returns true for multilingual models
        // Returns false for .en variants
    }
}

// Get locally computed recommendations
let localSupport = WhisperKit.recommendedModels()
print("Default model: \(localSupport.default)")
print("Supported models: \(localSupport.supported)")

// Get recommendations from remote config
let remoteSupport = await WhisperKit.recommendedRemoteModels(
    from: "argmaxinc/whisperkit-coreml"
)
print("Recommended: \(remoteSupport.default)")

let deviceName = WhisperKit.deviceName()
print("Running on: \(deviceName)")

// Example device identifiers:
// - "iPhone15,2" (iPhone 14 Pro)
// - "iPad13,16" (iPad Pro M2)
// - "Mac14,2" (Mac Studio M2)

// Downloads and loads the default recommended model
let whisperKit = try await WhisperKit()

// Downloads a specific model
let whisperKit = try await WhisperKit(model: "base")

let modelFolder = try await WhisperKit.download(
    variant: "large-v3",
    from: "argmaxinc/whisperkit-coreml",
    progressCallback: { progress in
        print("Downloaded: \(progress.fractionCompleted * 100)%")
    }
)

print("Model saved to: \(modelFolder.path)")

let availableModels = try await WhisperKit.fetchAvailableModels(
    from: "argmaxinc/whisperkit-coreml"
)

print("Available models:")
for model in availableModels {
    print("  - \(model)")
}

// Use a local model folder
let whisperKit = try await WhisperKit(
    modelFolder: "/path/to/model/folder",
    download: false  // Disable automatic download
)

// Get bundled model path
guard let modelPath = Bundle.main.path(
    forResource: "openai_whisper-base",
    ofType: nil
) else {
    fatalError("Model not found in bundle")
}

let whisperKit = try await WhisperKit(
    modelFolder: modelPath,
    download: false
)

// Default: argmaxinc/whisperkit-coreml
let whisperKit = try await WhisperKit(model: "base")

let whisperKit = try await WhisperKit(
    model: "base",
    modelRepo: "your-username/your-repo",
    modelToken: "hf_your_token_here"  // If repo is private
)

let config = WhisperKitConfig(
    model: "base",
    modelEndpoint: "https://your-custom-endpoint.com"
)

let whisperKit = try await WhisperKit(config)

let whisperKit = try await WhisperKit(
    model: "large-v3",
    useBackgroundDownloadSession: true
)

let customBase = FileManager.default.urls(
    for: .documentDirectory,
    in: .userDomainMask
).first!

let whisperKit = try await WhisperKit(
    model: "base",
    downloadBase: customBase
)

let whisperKit = try await WhisperKit(
    model: "medium",
    prewarm: true  // Load and unload models sequentially
)

// Download but don't load models yet
let whisperKit = try await WhisperKit(
    model: "base",
    load: false
)

// Load later when needed
try await whisperKit.loadModels()

// Free memory when models aren't needed
await whisperKit.unloadModels()

// Reload when needed
try await whisperKit.loadModels()

let whisperKit = try await WhisperKit(model: "base")  // Multilingual

let (language, _) = try await whisperKit.detectLanguage(
    audioPath: "audio.wav"
)
print("Detected: \(language)")

let whisperKit = try await WhisperKit(model: "base.en")

var options = DecodingOptions(language: "en")
let results = try await whisperKit.transcribe(
    audioPath: "audio.wav",
    decodeOptions: options
)