snapshot of https://github.com/ggml-org/whisper.cpp.git @ da54572229bcf64ba367d96c7ef15770376c4280 (2026-09-15)
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examples/whisper.swiftui/.gitignore vendored Normal file
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xcuserdata
xcshareddata

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# whisper.cpp/examples/whisper.swiftui
A sample SwiftUI app using [whisper.cpp](https://github.com/ggerganov/whisper.cpp/) to do voice-to-text transcriptions.
See also: [whisper.objc](https://github.com/ggerganov/whisper.cpp/tree/master/examples/whisper.objc).
### Building
First whisper.cpp need to be built and a XCFramework needs to be created. This can be done by running
the following script from the whisper.cpp project root:
```console
$ ./build-xcframework.sh
```
Note: if you get the error "iphoneos is not an iOS SDK" then you probably need to run this command first:
```console
sudo xcode-select -switch /Applications/Xcode.app/Contents/Developer
```
Open `whisper.swiftui.xcodeproj` project in Xcode and you should be able to build and run the app on
a simulator or a real device.
To use the framework with a different project, the XCFramework can be added to the project by
adding `build-apple/whisper.xcframework` by dragging and dropping it into the project navigator, or
by manually selecting the framework in the "Frameworks, Libraries, and Embedded Content" section
of the project settings.
### Usage
1. Select a model from the [whisper.cpp repository](https://github.com/ggerganov/whisper.cpp/tree/master/models).[^1]
2. Add the model to `whisper.swiftui.demo/Resources/models` **via Xcode**.
3. Select a sample audio file (for example, [jfk.wav](https://github.com/ggerganov/whisper.cpp/raw/master/samples/jfk.wav)).
4. Add the sample audio file to `whisper.swiftui.demo/Resources/samples` **via Xcode**.
5. Select the "Release" [^2] build configuration under "Run", then deploy and run to your device.
**Note:** Pay attention to the folder path: `whisper.swiftui.demo/Resources/models` is the appropriate directory to place resources whilst `whisper.swiftui.demo/Models` is related to actual code.
### Core ML support
1. Follow all the steps in the `Usage` section, including adding the ggml model file.
The ggml model file is required as the Core ML model is only used for the encoder. The
decoder which is in the ggml model is still required.
2. Follow the [`Core ML support` section of readme](../../README.md#core-ml-support) to convert the
model.
3. Add the Core ML model (`models/ggml-base.en-encoder.mlmodelc/`) to `whisper.swiftui.demo/Resources/models` **via Xcode**.
When the example starts running you should now see that it is using the Core ML model:
```console
whisper_init_state: loading Core ML model from '/Library/Developer/CoreSimulator/Devices/25E8C27D-0253-4281-AF17-C3F2A4D1D8F4/data/Containers/Bundle/Application/3ADA7D59-7B9C-43B4-A7E1-A87183FC546A/whisper.swiftui.app/models/ggml-base.en-encoder.mlmodelc'
whisper_init_state: first run on a device may take a while ...
whisper_init_state: Core ML model loaded
```
[^1]: I recommend the tiny, base or small models for running on an iOS device.
[^2]: The `Release` build can boost performance of transcription. In this project, it also added `-O3 -DNDEBUG` to `Other C Flags`, but adding flags to app proj is not ideal in real world (applies to all C/C++ files), consider splitting xcodeproj in workspace in your own project.
![image](https://user-images.githubusercontent.com/1991296/212539216-0aef65e4-f882-480a-8358-0f816838fd52.png)

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import Foundation
import UIKit
import whisper
enum WhisperError: Error {
case couldNotInitializeContext
}
// Meet Whisper C++ constraint: Don't access from more than one thread at a time.
actor WhisperContext {
private var context: OpaquePointer
init(context: OpaquePointer) {
self.context = context
}
deinit {
whisper_free(context)
}
func fullTranscribe(samples: [Float]) {
// Leave 2 processors free (i.e. the high-efficiency cores).
let maxThreads = max(1, min(8, cpuCount() - 2))
print("Selecting \(maxThreads) threads")
var params = whisper_full_default_params(WHISPER_SAMPLING_GREEDY)
"en".withCString { en in
// Adapted from whisper.objc
params.print_realtime = true
params.print_progress = false
params.print_timestamps = true
params.print_special = false
params.translate = false
params.language = en
params.n_threads = Int32(maxThreads)
params.offset_ms = 0
params.no_context = true
params.single_segment = false
whisper_reset_timings(context)
print("About to run whisper_full")
samples.withUnsafeBufferPointer { samples in
if (whisper_full(context, params, samples.baseAddress, Int32(samples.count)) != 0) {
print("Failed to run the model")
} else {
whisper_print_timings(context)
}
}
}
}
func getTranscription() -> String {
var transcription = ""
for i in 0..<whisper_full_n_segments(context) {
transcription += String.init(cString: whisper_full_get_segment_text(context, i))
}
return transcription
}
static func benchMemcpy(nThreads: Int32) async -> String {
return String.init(cString: whisper_bench_memcpy_str(nThreads))
}
static func benchGgmlMulMat(nThreads: Int32) async -> String {
return String.init(cString: whisper_bench_ggml_mul_mat_str(nThreads))
}
private func systemInfo() -> String {
var info = ""
//if (ggml_cpu_has_neon() != 0) { info += "NEON " }
return String(info.dropLast())
}
func benchFull(modelName: String, nThreads: Int32) async -> String {
let nMels = whisper_model_n_mels(context)
if (whisper_set_mel(context, nil, 0, nMels) != 0) {
return "error: failed to set mel"
}
// heat encoder
if (whisper_encode(context, 0, nThreads) != 0) {
return "error: failed to encode"
}
var tokens = [whisper_token](repeating: 0, count: 512)
// prompt heat
if (whisper_decode(context, &tokens, 256, 0, nThreads) != 0) {
return "error: failed to decode"
}
// text-generation heat
if (whisper_decode(context, &tokens, 1, 256, nThreads) != 0) {
return "error: failed to decode"
}
whisper_reset_timings(context)
// actual run
if (whisper_encode(context, 0, nThreads) != 0) {
return "error: failed to encode"
}
// text-generation
for i in 0..<256 {
if (whisper_decode(context, &tokens, 1, Int32(i), nThreads) != 0) {
return "error: failed to decode"
}
}
// batched decoding
for _ in 0..<64 {
if (whisper_decode(context, &tokens, 5, 0, nThreads) != 0) {
return "error: failed to decode"
}
}
// prompt processing
for _ in 0..<16 {
if (whisper_decode(context, &tokens, 256, 0, nThreads) != 0) {
return "error: failed to decode"
}
}
whisper_print_timings(context)
let deviceModel = await UIDevice.current.model
let systemName = await UIDevice.current.systemName
let systemInfo = self.systemInfo()
let timings: whisper_timings = whisper_get_timings(context).pointee
let encodeMs = String(format: "%.2f", timings.encode_ms)
let decodeMs = String(format: "%.2f", timings.decode_ms)
let batchdMs = String(format: "%.2f", timings.batchd_ms)
let promptMs = String(format: "%.2f", timings.prompt_ms)
return "| \(deviceModel) | \(systemName) | \(systemInfo) | \(modelName) | \(nThreads) | 1 | \(encodeMs) | \(decodeMs) | \(batchdMs) | \(promptMs) | <todo> |"
}
static func createContext(path: String) throws -> WhisperContext {
var params = whisper_context_default_params()
#if targetEnvironment(simulator)
params.use_gpu = false
print("Running on the simulator, using CPU")
#else
params.flash_attn = true // Enabled by default for Metal
#endif
let context = whisper_init_from_file_with_params(path, params)
if let context {
return WhisperContext(context: context)
} else {
print("Couldn't load model at \(path)")
throw WhisperError.couldNotInitializeContext
}
}
}
fileprivate func cpuCount() -> Int {
ProcessInfo.processInfo.processorCount
}

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import Foundation
struct Model: Identifiable {
var id = UUID()
var name: String
var info: String
var url: String
var filename: String
var fileURL: URL {
FileManager.default.urls(for: .documentDirectory, in: .userDomainMask)[0].appendingPathComponent(filename)
}
func fileExists() -> Bool {
FileManager.default.fileExists(atPath: fileURL.path)
}
}

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import Foundation
import SwiftUI
import AVFoundation
@MainActor
class WhisperState: NSObject, ObservableObject, AVAudioRecorderDelegate {
@Published var isModelLoaded = false
@Published var messageLog = ""
@Published var canTranscribe = false
@Published var isRecording = false
private var whisperContext: WhisperContext?
private let recorder = Recorder()
private var recordedFile: URL? = nil
private var audioPlayer: AVAudioPlayer?
private var builtInModelUrl: URL? {
Bundle.main.url(forResource: "ggml-base.en", withExtension: "bin", subdirectory: "models")
}
private var sampleUrl: URL? {
Bundle.main.url(forResource: "jfk", withExtension: "wav", subdirectory: "samples")
}
private enum LoadError: Error {
case couldNotLocateModel
}
override init() {
super.init()
loadModel()
}
func loadModel(path: URL? = nil, log: Bool = true) {
do {
whisperContext = nil
if (log) { messageLog += "Loading model...\n" }
let modelUrl = path ?? builtInModelUrl
if let modelUrl {
whisperContext = try WhisperContext.createContext(path: modelUrl.path())
if (log) { messageLog += "Loaded model \(modelUrl.lastPathComponent)\n" }
} else {
if (log) { messageLog += "Could not locate model\n" }
}
canTranscribe = true
} catch {
print(error.localizedDescription)
if (log) { messageLog += "\(error.localizedDescription)\n" }
}
}
func benchCurrentModel() async {
if whisperContext == nil {
messageLog += "Cannot bench without loaded model\n"
return
}
messageLog += "Running benchmark for loaded model\n"
let result = await whisperContext?.benchFull(modelName: "<current>", nThreads: Int32(min(4, cpuCount())))
if (result != nil) { messageLog += result! + "\n" }
}
func bench(models: [Model]) async {
let nThreads = Int32(min(4, cpuCount()))
// messageLog += "Running memcpy benchmark\n"
// messageLog += await WhisperContext.benchMemcpy(nThreads: nThreads) + "\n"
//
// messageLog += "Running ggml_mul_mat benchmark with \(nThreads) threads\n"
// messageLog += await WhisperContext.benchGgmlMulMat(nThreads: nThreads) + "\n"
messageLog += "Running benchmark for all downloaded models\n"
messageLog += "| CPU | OS | Config | Model | Th | FA | Enc. | Dec. | Bch5 | PP | Commit |\n"
messageLog += "| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n"
for model in models {
loadModel(path: model.fileURL, log: false)
if whisperContext == nil {
messageLog += "Cannot bench without loaded model\n"
break
}
let result = await whisperContext?.benchFull(modelName: model.name, nThreads: nThreads)
if (result != nil) { messageLog += result! + "\n" }
}
messageLog += "Benchmarking completed\n"
}
func transcribeSample() async {
if let sampleUrl {
await transcribeAudio(sampleUrl)
} else {
messageLog += "Could not locate sample\n"
}
}
private func transcribeAudio(_ url: URL) async {
if (!canTranscribe) {
return
}
guard let whisperContext else {
return
}
do {
canTranscribe = false
messageLog += "Reading wave samples...\n"
let data = try readAudioSamples(url)
messageLog += "Transcribing data...\n"
await whisperContext.fullTranscribe(samples: data)
let text = await whisperContext.getTranscription()
messageLog += "Done: \(text)\n"
} catch {
print(error.localizedDescription)
messageLog += "\(error.localizedDescription)\n"
}
canTranscribe = true
}
private func readAudioSamples(_ url: URL) throws -> [Float] {
stopPlayback()
try startPlayback(url)
return try decodeWaveFile(url)
}
func toggleRecord() async {
if isRecording {
await recorder.stopRecording()
isRecording = false
if let recordedFile {
await transcribeAudio(recordedFile)
}
} else {
requestRecordPermission { granted in
if granted {
Task {
do {
self.stopPlayback()
let file = try FileManager.default.url(for: .documentDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appending(path: "output.wav")
try await self.recorder.startRecording(toOutputFile: file, delegate: self)
self.isRecording = true
self.recordedFile = file
} catch {
print(error.localizedDescription)
self.messageLog += "\(error.localizedDescription)\n"
self.isRecording = false
}
}
}
}
}
}
private func requestRecordPermission(response: @escaping (Bool) -> Void) {
#if os(macOS)
response(true)
#else
AVAudioSession.sharedInstance().requestRecordPermission { granted in
response(granted)
}
#endif
}
private func startPlayback(_ url: URL) throws {
audioPlayer = try AVAudioPlayer(contentsOf: url)
audioPlayer?.play()
}
private func stopPlayback() {
audioPlayer?.stop()
audioPlayer = nil
}
// MARK: AVAudioRecorderDelegate
nonisolated func audioRecorderEncodeErrorDidOccur(_ recorder: AVAudioRecorder, error: Error?) {
if let error {
Task {
await handleRecError(error)
}
}
}
private func handleRecError(_ error: Error) {
print(error.localizedDescription)
messageLog += "\(error.localizedDescription)\n"
isRecording = false
}
nonisolated func audioRecorderDidFinishRecording(_ recorder: AVAudioRecorder, successfully flag: Bool) {
Task {
await onDidFinishRecording()
}
}
private func onDidFinishRecording() {
isRecording = false
}
}
fileprivate func cpuCount() -> Int {
ProcessInfo.processInfo.processorCount
}

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{
"colors" : [
{
"idiom" : "universal"
}
],
"info" : {
"author" : "xcode",
"version" : 1
}
}

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{
"images" : [
{
"idiom" : "universal",
"platform" : "ios",
"size" : "1024x1024"
},
{
"idiom" : "mac",
"scale" : "1x",
"size" : "16x16"
},
{
"idiom" : "mac",
"scale" : "2x",
"size" : "16x16"
},
{
"idiom" : "mac",
"scale" : "1x",
"size" : "32x32"
},
{
"idiom" : "mac",
"scale" : "2x",
"size" : "32x32"
},
{
"idiom" : "mac",
"scale" : "1x",
"size" : "128x128"
},
{
"idiom" : "mac",
"scale" : "2x",
"size" : "128x128"
},
{
"idiom" : "mac",
"scale" : "1x",
"size" : "256x256"
},
{
"idiom" : "mac",
"scale" : "2x",
"size" : "256x256"
},
{
"idiom" : "mac",
"scale" : "1x",
"size" : "512x512"
},
{
"idiom" : "mac",
"scale" : "2x",
"size" : "512x512"
}
],
"info" : {
"author" : "xcode",
"version" : 1
}
}

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{
"info" : {
"author" : "xcode",
"version" : 1
}
}

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{
"info" : {
"author" : "xcode",
"version" : 1
}
}

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<?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>com.apple.security.app-sandbox</key>
<true/>
<key>com.apple.security.device.audio-input</key>
<true/>
<key>com.apple.security.files.user-selected.read-only</key>
<true/>
</dict>
</plist>

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import SwiftUI
import AVFoundation
import Foundation
struct ContentView: View {
@StateObject var whisperState = WhisperState()
var body: some View {
NavigationStack {
VStack {
HStack {
Button("Transcribe", action: {
Task {
await whisperState.transcribeSample()
}
})
.buttonStyle(.bordered)
.disabled(!whisperState.canTranscribe)
Button(whisperState.isRecording ? "Stop recording" : "Start recording", action: {
Task {
await whisperState.toggleRecord()
}
})
.buttonStyle(.bordered)
.disabled(!whisperState.canTranscribe)
}
ScrollView {
Text(verbatim: whisperState.messageLog)
.frame(maxWidth: .infinity, alignment: .leading)
}
.font(.footnote)
.padding()
.background(Color.gray.opacity(0.1))
.cornerRadius(10)
HStack {
Button("Clear Logs", action: {
whisperState.messageLog = ""
})
.font(.footnote)
.buttonStyle(.bordered)
Button("Copy Logs", action: {
UIPasteboard.general.string = whisperState.messageLog
})
.font(.footnote)
.buttonStyle(.bordered)
Button("Bench", action: {
Task {
await whisperState.benchCurrentModel()
}
})
.font(.footnote)
.buttonStyle(.bordered)
.disabled(!whisperState.canTranscribe)
Button("Bench All", action: {
Task {
await whisperState.bench(models: ModelsView.getDownloadedModels())
}
})
.font(.footnote)
.buttonStyle(.bordered)
.disabled(!whisperState.canTranscribe)
}
NavigationLink(destination: ModelsView(whisperState: whisperState)) {
Text("View Models")
}
.font(.footnote)
.padding()
}
.navigationTitle("Whisper SwiftUI Demo")
.padding()
}
}
struct ModelsView: View {
@ObservedObject var whisperState: WhisperState
@Environment(\.dismiss) var dismiss
private static let models: [Model] = [
Model(name: "tiny", info: "(F16, 75 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin", filename: "tiny.bin"),
Model(name: "tiny-q5_1", info: "(31 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny-q5_1.bin", filename: "tiny-q5_1.bin"),
Model(name: "tiny-q8_0", info: "(42 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny-q8_0.bin", filename: "tiny-q8_0.bin"),
Model(name: "tiny.en", info: "(F16, 75 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en.bin", filename: "tiny.en.bin"),
Model(name: "tiny.en-q5_1", info: "(31 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en-q5_1.bin", filename: "tiny.en-q5_1.bin"),
Model(name: "tiny.en-q8_0", info: "(42 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en-q8_0.bin", filename: "tiny.en-q8_0.bin"),
Model(name: "base", info: "(F16, 142 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin", filename: "base.bin"),
Model(name: "base-q5_1", info: "(57 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base-q5_1.bin", filename: "base-q5_1.bin"),
Model(name: "base-q8_0", info: "(78 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base-q8_0.bin", filename: "base-q8_0.bin"),
Model(name: "base.en", info: "(F16, 142 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin", filename: "base.en.bin"),
Model(name: "base.en-q5_1", info: "(57 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en-q5_1.bin", filename: "base.en-q5_1.bin"),
Model(name: "base.en-q8_0", info: "(78 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en-q8_0.bin", filename: "base.en-q8_0.bin"),
Model(name: "small", info: "(F16, 466 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.bin", filename: "small.bin"),
Model(name: "small-q5_1", info: "(181 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small-q5_1.bin", filename: "small-q5_1.bin"),
Model(name: "small-q8_0", info: "(252 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small-q8_0.bin", filename: "small-q8_0.bin"),
Model(name: "small.en", info: "(F16, 466 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en.bin", filename: "small.en.bin"),
Model(name: "small.en-q5_1", info: "(181 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en-q5_1.bin", filename: "small.en-q5_1.bin"),
Model(name: "small.en-q8_0", info: "(252 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-small.en-q8_0.bin", filename: "small.en-q8_0.bin"),
Model(name: "medium", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.bin", filename: "medium.bin"),
Model(name: "medium-q5_0", info: "(514 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium-q5_0.bin", filename: "medium-q5_0.bin"),
Model(name: "medium-q8_0", info: "(785 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium-q8_0.bin", filename: "medium-q8_0.bin"),
Model(name: "medium.en", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en.bin", filename: "medium.en.bin"),
Model(name: "medium.en-q5_0", info: "(514 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en-q5_0.bin", filename: "medium.en-q5_0.bin"),
Model(name: "medium.en-q8_0", info: "(785 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-medium.en-q8_0.bin", filename: "medium.en-q8_0.bin"),
Model(name: "large-v1", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large.bin", filename: "large.bin"),
Model(name: "large-v2", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2.bin", filename: "large-v2.bin"),
Model(name: "large-v2-q5_0", info: "(1.1 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2-q5_0.bin", filename: "large-v2-q5_0.bin"),
Model(name: "large-v2-q8_0", info: "(1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v2-q8_0.bin", filename: "large-v2-q8_0.bin"),
Model(name: "large-v3", info: "(F16, 2.9 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin", filename: "large-v3.bin"),
Model(name: "large-v3-q5_0", info: "(1.1 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-q5_0.bin", filename: "large-v3-q5_0.bin"),
Model(name: "large-v3-turbo", info: "(F16, 1.5 GiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin", filename: "large-v3-turbo.bin"),
Model(name: "large-v3-turbo-q5_0", info: "(547 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo-q5_0.bin", filename: "large-v3-turbo-q5_0.bin"),
Model(name: "large-v3-turbo-q8_0", info: "(834 MiB)", url: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo-q8_0.bin", filename: "large-v3-turbo-q8_0.bin"),
]
static func getDownloadedModels() -> [Model] {
// Filter models that have been downloaded
return models.filter {
FileManager.default.fileExists(atPath: $0.fileURL.path())
}
}
func loadModel(model: Model) {
Task {
dismiss()
whisperState.loadModel(path: model.fileURL)
}
}
var body: some View {
List {
Section(header: Text("Models")) {
ForEach(ModelsView.models) { model in
DownloadButton(model: model)
.onLoad(perform: loadModel)
}
}
}
.listStyle(GroupedListStyle())
.navigationBarTitle("Models", displayMode: .inline).toolbar {}
}
}
}
//struct ContentView_Previews: PreviewProvider {
// static var previews: some View {
// ContentView()
// }
//}

View File

@@ -0,0 +1,102 @@
import SwiftUI
struct DownloadButton: View {
private var model: Model
@State private var status: String
@State private var downloadTask: URLSessionDownloadTask?
@State private var progress = 0.0
@State private var observation: NSKeyValueObservation?
private var onLoad: ((_ model: Model) -> Void)?
init(model: Model) {
self.model = model
status = model.fileExists() ? "downloaded" : "download"
}
func onLoad(perform action: @escaping (_ model: Model) -> Void) -> DownloadButton {
var button = self
button.onLoad = action
return button
}
private func download() {
status = "downloading"
print("Downloading model \(model.name) from \(model.url)")
guard let url = URL(string: model.url) else { return }
downloadTask = URLSession.shared.downloadTask(with: url) { temporaryURL, response, error in
if let error = error {
print("Error: \(error.localizedDescription)")
return
}
guard let response = response as? HTTPURLResponse, (200...299).contains(response.statusCode) else {
print("Server error!")
return
}
do {
if let temporaryURL = temporaryURL {
try FileManager.default.copyItem(at: temporaryURL, to: model.fileURL)
print("Writing to \(model.filename) completed")
status = "downloaded"
}
} catch let err {
print("Error: \(err.localizedDescription)")
}
}
observation = downloadTask?.progress.observe(\.fractionCompleted) { progress, _ in
self.progress = progress.fractionCompleted
}
downloadTask?.resume()
}
var body: some View {
VStack {
Button(action: {
if (status == "download") {
download()
} else if (status == "downloading") {
downloadTask?.cancel()
status = "download"
} else if (status == "downloaded") {
if !model.fileExists() {
download()
}
onLoad?(model)
}
}) {
let title = "\(model.name) \(model.info)"
if (status == "download") {
Text("Download \(title)")
} else if (status == "downloading") {
Text("\(title) (Downloading \(Int(progress * 100))%)")
} else if (status == "downloaded") {
Text("Load \(title)")
} else {
Text("Unknown status")
}
}.swipeActions {
if (status == "downloaded") {
Button("Delete") {
do {
try FileManager.default.removeItem(at: model.fileURL)
} catch {
print("Error deleting file: \(error)")
}
status = "download"
}
.tint(.red)
}
}
}
.onDisappear() {
downloadTask?.cancel()
}
}
}

View File

@@ -0,0 +1,35 @@
import Foundation
import AVFoundation
actor Recorder {
private var recorder: AVAudioRecorder?
enum RecorderError: Error {
case couldNotStartRecording
}
func startRecording(toOutputFile url: URL, delegate: AVAudioRecorderDelegate?) throws {
let recordSettings: [String : Any] = [
AVFormatIDKey: Int(kAudioFormatLinearPCM),
AVSampleRateKey: 16000.0,
AVNumberOfChannelsKey: 1,
AVEncoderAudioQualityKey: AVAudioQuality.high.rawValue
]
#if !os(macOS)
let session = AVAudioSession.sharedInstance()
try session.setCategory(.playAndRecord, mode: .default)
#endif
let recorder = try AVAudioRecorder(url: url, settings: recordSettings)
recorder.delegate = delegate
if recorder.record() == false {
print("Could not start recording")
throw RecorderError.couldNotStartRecording
}
self.recorder = recorder
}
func stopRecording() {
recorder?.stop()
recorder = nil
}
}

View File

@@ -0,0 +1,12 @@
import Foundation
func decodeWaveFile(_ url: URL) throws -> [Float] {
let data = try Data(contentsOf: url)
let floats = stride(from: 44, to: data.count, by: 2).map {
return data[$0..<$0 + 2].withUnsafeBytes {
let short = Int16(littleEndian: $0.load(as: Int16.self))
return max(-1.0, min(Float(short) / 32767.0, 1.0))
}
}
return floats
}

View File

@@ -0,0 +1,10 @@
import SwiftUI
@main
struct WhisperCppDemoApp: App {
var body: some Scene {
WindowGroup {
ContentView()
}
}
}

View File

@@ -0,0 +1 @@
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View File

@@ -0,0 +1,476 @@
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