base on On-device Speech Recognition for Apple Silicon <div align="center"> <a href="https://github.com/argmaxinc/WhisperKit#gh-light-mode-only"> <img src="https://github.com/user-attachments/assets/f0699c07-c29f-45b6-a9c6-f6d491b8f791" alt="WhisperKit" width="20%" /> </a> <a href="https://github.com/argmaxinc/WhisperKit#gh-dark-mode-only"> <img src="https://github.com/user-attachments/assets/1be5e31c-de42-40ab-9b85-790cb911ed47" alt="WhisperKit" width="20%" /> </a> # WhisperKit [](https://github.com/argmaxinc/whisperkit/actions/workflows/pre-release-tests.yml) [](LICENSE.md) [](https://swiftpackageindex.com/argmaxinc/WhisperKit) [](https://swiftpackageindex.com/argmaxinc/WhisperKit) [](https://discord.gg/G5F5GZGecC) </div> WhisperKit is a Swift package that integrates OpenAI's popular [Whisper](https://github.com/openai/whisper) speech recognition model with Apple's CoreML framework for efficient, local inference on Apple devices. Check out the demo app on [TestFlight](https://testflight.apple.com/join/LPVOyJZW). [[Blog Post]](https://www.takeargmax.com/blog/whisperkit) [[Python Tools Repo]](https://github.com/argmaxinc/whisperkittools) ## Table of Contents - [Installation](#installation) - [Swift Package Manager](#swift-package-manager) - [Prerequisites](#prerequisites) - [Xcode Steps](#xcode-steps) - [Package.swift](#packageswift) - [Homebrew](#homebrew) - [Getting Started](#getting-started) - [Quick Example](#quick-example) - [Model Selection](#model-selection) - [Generating Models](#generating-models) - [Swift CLI](#swift-cli) - [Contributing \& Roadmap](#contributing--roadmap) - [License](#license) - [Citation](#citation) ## Installation ### Swift Package Manager WhisperKit can be integrated into your Swift project using the Swift Package Manager. ### Prerequisites - macOS 14.0 or later. - Xcode 15.0 or later. ### Xcode Steps 1. Open your Swift project in Xcode. 2. Navigate to `File` > `Add Package Dependencies...`. 3. Enter the package repository URL: `https://github.com/argmaxinc/whisperkit`. 4. Choose the version range or specific version. 5. Click `Finish` to add WhisperKit to your project. ### Package.swift If you're using WhisperKit as part of a swift package, you can include it in your Package.swift dependencies as follows: ```swift dependencies: [ .package(url: "https://github.com/argmaxinc/WhisperKit.git", from: "0.9.0"), ], ``` Then add `WhisperKit` as a dependency for your target: ```swift .target( name: "YourApp", dependencies: ["WhisperKit"] ), ``` ### Homebrew You can install `WhisperKit` command line app using [Homebrew](https://brew.sh) by running the following command: ```bash brew install whisperkit-cli ``` ## Getting Started To get started with WhisperKit, you need to initialize it in your project. ### Quick Example This example demonstrates how to transcribe a local audio file: ```swift import WhisperKit // Initialize WhisperKit with default settings Task { let pipe = try? await WhisperKit() let transcription = try? await pipe!.transcribe(audioPath: "path/to/your/audio.{wav,mp3,m4a,flac}")?.text print(transcription) } ``` ### Model Selection WhisperKit automatically downloads the recommended model for the device if not specified. You can also select a specific model by passing in the model name: ```swift let pipe = try? await WhisperKit(WhisperKitConfig(model: "large-v3")) ``` This method also supports glob search, so you can use wildcards to select a model: ```swift let pipe = try? await WhisperKit(WhisperKitConfig(model: "distil*large-v3")) ``` Note that the model search must return a single model from the source repo, otherwise an error will be thrown. For a list of available models, see our [HuggingFace repo](https://huggingface.co/argmaxinc/whisperkit-coreml). ### Generating Models WhisperKit also comes with the supporting repo [`whisperkittools`](https://github.com/argmaxinc/whisperkittools) which lets you create and deploy your own fine tuned versions of Whisper in CoreML format to HuggingFace. Once generated, they can be loaded by simply changing the repo name to the one used to upload the model: ```swift let config = WhisperKitConfig(model: "large-v3", modelRepo: "username/your-model-repo") let pipe = try? await WhisperKit(config) ``` ### Swift CLI The Swift CLI allows for quick testing and debugging outside of an Xcode project. To install it, run the following: ```bash git clone https://github.com/argmaxinc/whisperkit.git cd whisperkit ``` Then, setup the environment and download your desired model. ```bash make setup make download-model MODEL=large-v3 ``` **Note**: 1. This will download only the model specified by `MODEL` (see what's available in our [HuggingFace repo](https://huggingface.co/argmaxinc/whisperkit-coreml), where we use the prefix `openai_whisper-{MODEL}`) 2. Before running `download-model`, make sure [git-lfs](https://git-lfs.com) is installed If you would like download all available models to your local folder, use this command instead: ```bash make download-models ``` You can then run them via the CLI with: ```bash swift run whisperkit-cli transcribe --model-path "Models/whisperkit-coreml/openai_whisper-large-v3" --audio-path "path/to/your/audio.{wav,mp3,m4a,flac}" ``` Which should print a transcription of the audio file. If you would like to stream the audio directly from a microphone, use: ```bash swift run whisperkit-cli transcribe --model-path "Models/whisperkit-coreml/openai_whisper-large-v3" --stream ``` ## Contributing & Roadmap Our goal is to make WhisperKit better and better over time and we'd love your help! Just search the code for "TODO" for a variety of features that are yet to be built. Please refer to our [contribution guidelines](CONTRIBUTING.md) for submitting issues, pull requests, and coding standards, where we also have a public roadmap of features we are looking forward to building in the future. ## License WhisperKit is released under the MIT License. See [LICENSE](LICENSE) for more details. ## Citation If you use WhisperKit for something cool or just find it useful, please drop us a note at [[email protected]](mailto:[email protected])! If you use WhisperKit for academic work, here is the BibTeX: ```bibtex @misc{whisperkit-argmax, title = {WhisperKit}, author = {Argmax, Inc.}, year = {2024}, URL = {https://github.com/argmaxinc/WhisperKit} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"7447","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"