AutoClip

https://github.com/zhouxiaoka/autoclip
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AutoClip is an open-source AI video clipping tool that automatically cuts and renders highlight...
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### Environment setup and verification for autoclip

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/DEVELOPER_GUIDE.md

Set up the development environment for the repository: clone, create and activate a virtual environment, install Python dependencies and frontend packages, then run backend tests and frontend lint, typecheck, tests, and build.

```bash
git clone https://github.com/zhouxiaoka/autoclip.git
cd autoclip
python3 -m venv venv
source venv/bin/activate
python -m pip install -r requirements.txt
(cd frontend && npm ci)
python -m pytest backend/tests -q
(cd frontend && npm run lint && npm run typecheck && npm test && npm run build)
```

--------------------------------

### Test environment setup

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/SPEECH_RECOGNITION_SETUP.md

For test environments, no installation is needed; the system will automatically generate test subtitle files.

```bash
# 无需安装，使用测试字幕
# 系统会自动生成测试字幕文件
```

--------------------------------

### Install base model for development

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/SPEECH_RECOGNITION_SETUP.md

Install the base model for development environments, balancing speed and accuracy.

```bash
pip install openai-whisper
```

--------------------------------

### Install autoclip from source

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/CLI_AND_MCP.md

Clones the repository, creates and activates a virtual environment, installs dependencies, and installs the package in editable mode to provide the autoclip and autoclip-mcp commands. Requires ffmpeg in PATH and optionally faster-whisper for local transcription.

```bash
git clone https://github.com/zhouxiaoka/autoclip.git && cd autoclip
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
pip install -e .            # 得到 autoclip / autoclip-mcp 两个命令
```

--------------------------------

### Preview community board setup

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/COMMUNITY_BOARD.md

Runs the setup script in preview mode to show what categories are missing and how to fix them, without making changes.

```bash
python3 scripts/setup_community_board.py
```

--------------------------------

### Logging for speech recognition

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/SPEECH_RECOGNITION_REDESIGN.md

Python logging setup and examples for logging the start, success, and failure of speech recognition operations.

```python
import logging
logger = logging.getLogger(__name__)

# 语音识别开始
logger.info(f"开始语音识别: {video_path}")

# 语音识别成功
logger.info(f"语音识别成功: {output_path}")

# 语音识别失败
logger.error(f"语音识别失败: {error}")
```

--------------------------------

### Clone and prepare .env

Source: https://github.com/zhouxiaoka/autoclip/blob/main/DOCKER.md

Clones the repository, enters the project directory, and copies the environment template to .env for initial setup.

```bash
git clone https://github.com/zhouxiaoka/autoclip.git
cd autoclip
cp env.example .env
```

--------------------------------

### Start backend with python main.py

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/SYSTEM_REBUILD_GUIDE.md

Starts the backend service. Run from the project root; first change to the backend directory. The service listens on port 8000.

```bash
cd backend
python main.py
```

--------------------------------

### 命令行运行 app 查看后端输出

Source: https://github.com/zhouxiaoka/autoclip/blob/main/BUILD_GUIDE.md

直接运行 app 可执行文件以查看后端日志。应看到 'Backend started on port: XXXXX' 和 'Application startup complete'。

```bash
'/Applications/AutoClip Desktop.app/Contents/MacOS/autoclip-desktop'
```

--------------------------------

### AutoClip contribution workflow commands

Source: https://github.com/zhouxiaoka/autoclip/blob/main/CONTRIBUTING.md

These bash commands cover the workflow for contributing to AutoClip: cloning and setting up the repository, installing dependencies, running quality checks and tests, and submitting a pull request. They apply to macOS/Linux for web development; Windows desktop setups require different toolchain steps.

```bash
cd autoclip
git remote add upstream https://github.com/zhouxiaoka/autoclip.git
git fetch upstream
git switch -c fix/your-change upstream/main

```

```bash
python3 -m venv venv
source venv/bin/activate
python -m pip install -r requirements.txt
(cd frontend && npm ci)
cp env.example .env

```

```bash
python scripts/quality_gate.py --report /absolute/local/evidence/quality.json

```

```bash
python -m pytest backend/tests -q
# 开发时可先运行与改动相关的现有测试文件

```

```bash
cd frontend
npm run lint
npm run typecheck
npm test
npm run build

```

```bash
git add -p
git commit -m "fix: describe the problem being resolved"
git push -u origin fix/your-change

```

--------------------------------

### Test Whisper and FFmpeg installation

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/OPTIONAL_SRT_UPLOAD_GUIDE.md

Verify that Whisper and FFmpeg are correctly installed and accessible from the command line. Use this when debugging Whisper installation issues.

```bash
whisper --help
ffmpeg -version
```

--------------------------------

### Verify Windows installation

Source: https://github.com/zhouxiaoka/autoclip/blob/main/RELEASE_CHECKLIST.md

Run Windows installation verification using the installed Python; checks ffmpeg, Chinese filenames, yt-dlp, backend startup, and source guard.

```bash
scripts/verify_windows_install.py
```

--------------------------------

### Install wheel and run autoclip produce with --portrait-style podcast

Source: https://github.com/zhouxiaoka/autoclip/blob/main/docs/RELEASE_1_5.md

Install the wheel in a fresh virtual environment (Python 3.11 recommended, FFmpeg/FFprobe on PATH), then produce a portrait-style video from an existing SRT and export kits. Use --force-reinstall --no-deps to replace an older 1.5.0 candidate wheel; Windows activation uses .venv\Scripts\Activate.ps1.

```bash
# 解压到一个目录后，建立同事自己的虚拟环境。建议 Python 3.11，需 FFmpeg / FFprobe 在 PATH。
python3 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt
python -m pip install --force-reinstall --no-deps autoclip-1.5.0-py3-none-any.whl
autoclip --version

# 复用已保存的桌面模型配置；已有字幕可跳过语音识别。
autoclip produce /absolute/path/talk.mp4 --srt /absolute/path/talk.srt --platform douyin --portrait-style podcast --json
autoclip outputs PROJECT_ID --export-kits
```
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