
KrillinAI
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
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KrillinAI is a video subtitle translation and dubbing tool based on AI large models, featuring speech recognition, intelligent sentence segmentation, professional translation, and one-click deployment of the entire process. It provides a one-stop workflow from video downloading to the final product, empowering cross-language cultural communication with AI. The tool supports multiple languages for input and translation, integrates features like automatic dependency installation, video downloading from platforms like YouTube and Bilibili, high-speed subtitle recognition, intelligent subtitle segmentation and alignment, custom vocabulary replacement, professional-level translation engine, and diverse external service selection for speech and large model services.
README:
Krillin AI is an all-in-one solution for effortless video localization and enhancement. This minimalist yet powerful tool handles everything from translation, dubbing to voice cloning,formatting—seamlessly converting videos between landscape and portrait modes for optimal display across all content platforms(YouTube, TikTok, Bilibili, Douyin, WeChat Channel, RedNote, Kuaishou). With its end-to-end workflow, Krillin AI transforms raw footage into polished, platform-ready content in just a few clicks.
🎯 One-Click Start - Launch your workflow instantly
📥 Video download - yt-dlp and local file uploading supported
📜 Precise Subtitles - Whisper-powered high-accuracy recognition
🧠 Smart Segmentation - LLM-based subtitle chunking & alignment
🌍 Professional Translation - Paragraph-level translation for consistency
🔄 Term Replacement - One-click domain-specific vocabulary swap
🎙️ Dubbing and Voice Cloning - CosyVoice selected or cloning voices
🎬 Video Composition - Auto-formatting for horizontal/vertical layouts
The following picture demonstrates the effect after the subtitle file, which was generated through a one-click operation after importing a 46-minute local video, was inserted into the track. There was no manual adjustment involved at all. There are no missing or overlapping subtitles, the sentence segmentation is natural, and the translation quality is also quite high.
https://github.com/user-attachments/assets/bba1ac0a-fe6b-4947-b58d-ba99306d0339 |
https://github.com/user-attachments/assets/0b32fad3-c3ad-4b6a-abf0-0865f0dd2385 |
Input languages: Chinese, English, Japanese, German, Turkish supported (more languages being added)
Translation languages: 56 languages supported, including English, Chinese, Russian, Spanish, French, etc.
- Download the executable file that matches your device system from the release and place it in an empty folder.
- Create a
config
folder inside the folder, then create aconfig.toml
file in theconfig
folder. Copy the content from theconfig-example.toml
file in the source code'sconfig
directory intoconfig.toml
and fill in your configuration information accordingly. - Double-click the executable file to start the service.
- Open a browser and enter
http://127.0.0.1:8888
to start using it (replace 8888 with the port you configured in theconfig.toml
file).
This software is not signed, so after completing the file configuration in the "Basic Steps," you will need to manually trust the application on macOS. Follow these steps:
- Open the terminal and navigate to the directory where the executable file (assuming the file name is
KrillinAI_1.0.0_macOS_arm64
) is located. - Execute the following commands in sequence:
sudo xattr -rd com.apple.quarantine ./KrillinAI_1.0.0_macOS_arm64
sudo chmod +x ./KrillinAI_1.0.0_macOS_arm64
./KrillinAI_1.0.0_macOS_arm64
This will start the service.
This project supports Docker deployment. Please refer to the Docker Deployment Instructions.
If you encounter video download failures, please refer to the Cookie Configuration Instructions to configure your cookie information.
The quickest and most convenient configuration method:
- Select
openai
for bothtranscription_provider
andllm_provider
. In this way, you only need to fill inopenai.apikey
in the following three major configuration item categories, namelyopenai
,local_model
, andaliyun
, and then you can conduct subtitle translation. (Fill inapp.proxy
,model
andopenai.base_url
as per your own situation.)
The configuration method for using the local speech recognition model (macOS is not supported for the time being) (a choice that takes into account cost, speed, and quality):
- Fill in
fasterwhisper
fortranscription_provider
andopenai
forllm_provider
. In this way, you only need to fill inopenai.apikey
andlocal_model.faster_whisper
in the following three major configuration item categories, namelyopenai
andlocal_model
, and then you can conduct subtitle translation. The local model will be downloaded automatically. (The same applies toapp.proxy
andopenai.base_url
as mentioned above.)
The following usage situations require the configuration of Alibaba Cloud:
- If
llm_provider
is filled withaliyun
, it indicates that the large model service of Alibaba Cloud will be used. Consequently, the configuration of thealiyun.bailian
item needs to be set up. - If
transcription_provider
is filled withaliyun
, or if the "voice dubbing" function is enabled when starting a task, the voice service of Alibaba Cloud will be utilized. Therefore, the configuration of thealiyun.speech
item needs to be filled in. - If the "voice dubbing" function is enabled and local audio files are uploaded for voice timbre cloning at the same time, the OSS cloud storage service of Alibaba Cloud will also be used. Hence, the configuration of the
aliyun.oss
item needs to be filled in. Configuration Guide: Alibaba Cloud Configuration Instructions
Please refer to Frequently Asked Questions
- Do not submit unnecessary files like
.vscode
,.idea
, etc. Please make good use of.gitignore
to filter them. - Do not submit
config.toml
; instead, submitconfig-example.toml
.
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