GPT CodeSlicer

GPT CodeSlicer is a Visual Studio Code extension that simplifies organizing multi-file code outputs generated by ChatGPT or similar tools. It uses delimiter comments (e.g., // path/to/file.ext) to identify file boundaries and automatically splits the content into properly structured files and folders.

Features

• Multi-file Splitting: Easily split concatenated multi-file code snippets based on delimiter comments.
• Flexible Input Sources:
  • Split code from the currently active file in the editor.
  • Split code directly from the system clipboard.
• Dynamic Output Directories:
  • Choose a custom folder.
  • Use the same directory as the source file.
  • Select a folder or file in the Explorer and split directly into that location.
• Optional Formatting: If enabled via gptCodeSlicer.runFormatterOnSave, the extension will run the VS Code formatter on each created file after splitting, respecting the user's editor settings for indentation.
• Optional Context Menu Entry: Control whether the clipboard splitting command appears in the Explorer context menu by toggling gptCodeSlicer.showInContextMenu.
• Automatic Folder Creation: Automatically creates directories as specified in the file paths.
• File Overwrite Prompt: If a file already exists, you are asked whether to overwrite or skip it.

Commands

1. GPT CodeSlicer: Split Files to Folder (splitter.splitFileToFolder)
   Prompts for a target directory and splits the currently open file into separate files.

2. GPT CodeSlicer: Split Files Here (splitter.splitFileToSameFolder)
   Splits the currently open file and saves the resulting files into the same directory as the source file.

3. GPT CodeSlicer: Split Clipboard to Folder (splitter.splitClipboardToFolder)
   Splits the system clipboard content into files, prompting for a target directory.

4. GPT CodeSlicer: Split Clipboard to Selected Folder (splitter.splitClipboardToSelectedFolder)
   Splits the clipboard content directly into the folder (or the folder of a selected file) chosen in the Explorer panel.
   Controlled by the gptCodeSlicer.showInContextMenu setting.

Configuration

Extension Settings:

• gptCodeSlicer.showInContextMenu (boolean)
  Default: true
  When true, displays the "Split Clipboard to Selected Folder" command in the Explorer context menu. Set it to false to reduce clutter if desired.

• gptCodeSlicer.runFormatterOnSave (boolean)
  Default: false
  When true, the extension runs the VS Code formatter on each created file after splitting. It uses the user's editor.tabSize and editor.insertSpaces settings to determine formatting style.

Example (settings.json):

{
  "gptCodeSlicer.showInContextMenu": false,
  "gptCodeSlicer.runFormatterOnSave": true
}

Example

Splitting from Clipboard to a Selected Folder with Formatting

Setup:

• Copy text containing delimiters into your clipboard, for example:

  // pages/Home.js
  export default function Home() {
    return <h1>Home Page</h1>;
  }
  
  // pages/About.js
  export default function About() {
    return <h1>About Page</h1>;
  }
  

• Enable formatting in your settings.json:

  "gptCodeSlicer.runFormatterOnSave": true
  

Action:

• In VS Code’s Explorer, right-click on a folder named website.
• If gptCodeSlicer.showInContextMenu is true, select GPT CodeSlicer: Split Clipboard to Selected Folder.
• The files are created and then formatted automatically based on your editor settings (editor.tabSize, editor.insertSpaces).

Result:

website/
└── pages/
    ├── Home.js   (formatted)
    └── About.js  (formatted)

Installation

You can install this extension directly from the VS Code Marketplace by searching for "GPT CodeSlicer."

Build and Install Locally

1. Clone the repository:

   git clone https://github.com/RuslanSay/gpt-codeslicer.git
   cd gpt-codeslicer
   

2. Install dependencies and compile:

   npm install
   npm run compile
   

3. Install the extension in VS Code:

   code --install-extension gpt-codeslicer-1.1.8.vsix
   

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for details.