base on A video translation and dubbing tool powered by LLMs, offering professional-grade translations and one-click full-process deployment. It can generate content optimized for platforms like YouTube，TikTok, and Shorts. 基于AI大模型的视频翻译和配音工具，专业级翻译，一键部署全流程，可以生成适配抖音，小红书，哔哩哔哩，视频号，TikTok，Youtube Shorts等形态的内容 <div align="center"> <img src="/docs/images/logo.jpg" alt="KlicStudio" height="90"> # Minimalist AI Video Translation and Dubbing Tool <a href="https://trendshift.io/repositories/13360" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13360" alt="KrillinAI%2FKlicStudio | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> **[English](/README.md)｜[简体中文](/docs/zh/README.md)｜[日本語](/docs/jp/README.md)｜[한국어](/docs/kr/README.md)｜[Tiếng Việt](/docs/vi/README.md)｜[Français](/docs/fr/README.md)｜[Deutsch](/docs/de/README.md)｜[Español](/docs/es/README.md)｜[Português](/docs/pt/README.md)｜[Русский](/docs/rus/README.md)｜[اللغة العربية](/docs/ar/README.md)** [](https://x.com/KrillinAI) [](https://jq.qq.com/?_wv=1027&k=754069680) [](https://space.bilibili.com/242124650) </div> ## Project Introduction ([Try the online version now!](https://www.klic.studio/)) Klic Studio is a versatile audio and video localization and enhancement solution developed by Krillin AI. This minimalist yet powerful tool integrates video translation, dubbing, and voice cloning, supporting both landscape and portrait formats to ensure perfect presentation on all major platforms (Bilibili, Xiaohongshu, Douyin, WeChat Video, Kuaishou, YouTube, TikTok, etc.). With an end-to-end workflow, you can transform raw materials into beautifully ready-to-use cross-platform content with just a few clicks. ## Key Features and Functions: 🎯 **One-click Start**: No complex environment configuration required, automatic dependency installation, ready to use immediately, with a new desktop version for easier access! 📥 **Video Acquisition**: Supports yt-dlp downloads or local file uploads 📜 **Accurate Recognition**: High-accuracy speech recognition based on Whisper 🧠 **Intelligent Segmentation**: Subtitle segmentation and alignment using LLM 🔄 **Terminology Replacement**: One-click replacement of professional vocabulary 🌍 **Professional Translation**: LLM translation with context to maintain natural semantics 🎙️ **Voice Cloning**: Offers selected voice tones from CosyVoice or custom voice cloning 🎬 **Video Composition**: Automatically processes landscape and portrait videos and subtitle layout 💻 **Cross-Platform**: Supports Windows, Linux, macOS, providing both desktop and server versions ## Effect Demonstration The image below shows the effect of the subtitle file generated after importing a 46-minute local video and executing it with one click, without any manual adjustments. There are no omissions or overlaps, the segmentation is natural, and the translation quality is very high.  <table> <tr> <td width="33%"> ### Subtitle Translation --- https://github.com/user-attachments/assets/bba1ac0a-fe6b-4947-b58d-ba99306d0339 </td> <td width="33%"> ### Dubbing --- https://github.com/user-attachments/assets/0b32fad3-c3ad-4b6a-abf0-0865f0dd2385 </td> <td width="33%"> ### Portrait Mode --- https://github.com/user-attachments/assets/c2c7b528-0ef8-4ba9-b8ac-f9f92f6d4e71 </td> </tr> </table> ## 🔍 Supported Speech Recognition Services _**All local models in the table below support automatic installation of executable files + model files; you just need to choose, and Klic will prepare everything for you.**_ | Service Source | Supported Platforms | Model Options | Local/Cloud | Remarks | |------------------------|---------------------|------------------------------------------|-------------|-----------------------------| | **OpenAI Whisper** | All Platforms | - | Cloud | Fast speed and good effect | | **FasterWhisper** | Windows/Linux | `tiny`/`medium`/`large-v2` (recommended medium+) | Local | Faster speed, no cloud service cost | | **WhisperKit** | macOS (M-series only) | `large-v2` | Local | Native optimization for Apple chips | | **WhisperCpp** | All Platforms | `large-v2` | Local | Supports all platforms | | **Alibaba Cloud ASR** | All Platforms | - | Cloud | Avoids network issues in mainland China | ## 🚀 Large Language Model Support ✅ Compatible with all cloud/local large language model services that comply with **OpenAI API specifications**, including but not limited to: - OpenAI - Gemini - DeepSeek - Tongyi Qianwen - Locally deployed open-source models - Other API services compatible with OpenAI format ## 🎤 TTS Text-to-Speech Support - Alibaba Cloud Voice Service - OpenAI TTS ## Language Support Input languages supported: Chinese, English, Japanese, German, Turkish, Korean, Russian, Malay (continuously increasing) Translation languages supported: English, Chinese, Russian, Spanish, French, and 101 other languages ## Interface Preview  ## 🚀 Quick Start ### Basic Steps First, download the executable file that matches your device system from the [Release](https://github.com/KrillinAI/KlicStudio/releases), then follow the tutorial below to choose between the desktop version or non-desktop version. Place the software download in an empty folder, as running it will generate some directories, and keeping it in an empty folder will make management easier. 【If it is the desktop version, i.e., the release file with "desktop," see here】 _The desktop version is newly released to address the issues of new users struggling to edit configuration files correctly, and there are some bugs that are continuously being updated._ 1. Double-click the file to start using it (the desktop version also requires configuration within the software) 【If it is the non-desktop version, i.e., the release file without "desktop," see here】 _The non-desktop version is the initial version, which has a more complex configuration but is stable in functionality and suitable for server deployment, as it provides a UI in a web format._ 1. Create a `config` folder within the folder, then create a `config.toml` file in the `config` folder. Copy the contents of the `config-example.toml` file from the source code's `config` directory into `config.toml`, and fill in your configuration information according to the comments. 2. Double-click or execute the executable file in the terminal to start the service 3. Open your browser and enter `http://127.0.0.1:8888` to start using it (replace 8888 with the port you specified in the configuration file) ### To: macOS Users 【If it is the desktop version, i.e., the release file with "desktop," see here】 Due to signing issues, the desktop version currently cannot be double-clicked to run or installed via dmg; you need to manually trust the application. The method is as follows: 1. Open the terminal in the directory where the executable file (assuming the file name is KlicStudio_1.0.0_desktop_macOS_arm64) is located 2. Execute the following commands in order: ``` sudo xattr -cr ./KlicStudio_1.0.0_desktop_macOS_arm64 sudo chmod +x ./KlicStudio_1.0.0_desktop_macOS_arm64 ./KlicStudio_1.0.0_desktop_macOS_arm64 ``` 【If it is the non-desktop version, i.e., the release file without "desktop," see here】 This software is not signed, so when running on macOS, after completing the file configuration in the "Basic Steps," you also need to manually trust the application. The method is as follows: 1. Open the terminal in the directory where the executable file (assuming the file name is KlicStudio_1.0.0_macOS_arm64) is located 2. Execute the following commands in order: ``` sudo xattr -rd com.apple.quarantine ./KlicStudio_1.0.0_macOS_arm64 sudo chmod +x ./KlicStudio_1.0.0_macOS_arm64 ./KlicStudio_1.0.0_macOS_arm64 ``` This will start the service ### Docker Deployment This project supports Docker deployment; please refer to the [Docker Deployment Instructions](./docker.md) ### Cookie Configuration Instructions (Optional) If you encounter issues with video downloads Please refer to the [Cookie Configuration Instructions](./get_cookies.md) to configure your Cookie information. ### Configuration Help (Must Read) The quickest and easiest configuration method: * Fill in `transcribe.provider.name` with `openai`, so you only need to fill in the `transcribe.openai` block and the large model configuration in the `llm` block to perform subtitle translation. (`app.proxy`, `model`, and `openai.base_url` can be filled in as needed) Using a local speech recognition model configuration method (balancing cost, speed, and quality): * Fill in `transcribe.provider.name` with `fasterwhisper`, `transcribe.fasterwhisper.model` with `large-v2`, and then fill in the `llm` block with the large model configuration to perform subtitle translation. The local model will be automatically downloaded and installed. (`app.proxy` and `openai.base_url` are the same as above) Text-to-speech (TTS) is optional; the configuration logic is the same as above. Fill in `tts.provider.name`, and then fill in the corresponding configuration block under `tts`. The voice codes in the UI should be filled in according to the documentation of the selected provider (the documentation address is in the common questions section below). Filling in Alibaba Cloud's AccessKey, Bucket, AppKey, etc., may be repetitive to ensure a clear configuration structure. Note: If using voice cloning, `tts` only supports selecting `aliyun`. **For obtaining Alibaba Cloud AccessKey, Bucket, and AppKey, please read**: [Alibaba Cloud Configuration Instructions](./aliyun.md) Please understand that the task = speech recognition + large model translation + voice service (TTS, etc., optional), which will help you understand the configuration file better. ## Frequently Asked Questions Please visit [Frequently Asked Questions](./faq.md) ## Contribution Guidelines 1. Do not submit useless files, such as .vscode, .idea, etc.; please use .gitignore to filter them out. 2. Do not submit config.toml; instead, submit config-example.toml. ## Contact Us 1. Join our QQ group for questions: 754069680 2. Follow our social media accounts, [Bilibili](https://space.bilibili.com/242124650), where we share quality content in the AI technology field every day. ## Star History [](https://star-history.com/#KrillinAI/KlicStudio&Date)", Assign "at most 3 tags" to the expected json: {"id":"13905","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"