sn2md 0.1.0

Converts Supernote exports to markdown

Supernote to Markdown converter (sn2md)

sn2md is a command-line tool to convert Supernote .note files into markdown. It leverages OpenAI GPT-4o to convert images and text from Supernote files into a structured markdown document.

Features

• Converts Supernote .note files to markdown.
• Supports conversion of images to markdown using the Mermaid diagramming tool.
• Automatically handles math equations using $ and $$ style math blocks.
• Generates a markdown file with metadata and embedded images.

Installation

pip install sn2md

Setup your OPENAI_API_KEY environment variable.

Development

git clone https://github.com/yourusername/supernote-importer.git
cd supernote-importer
poetry install

Usage

To import a single Supernote .note file, use the file command:

# import one .note file:
sn2md file <path_to_note_file> --output <output_directory>

# import a directory of .note files:
sn2md directory <path_to_directory> --output <output_directory>

Notes:

• A cache file is also generated, so repeated runs don't recreate the same data. You can force a refresh by running with the --force flag.

Custom Templates

You can provide your own jinja template, if you prefer to customize the markdown output. The default template is:

---
created: {{year_month_day}}
tags: supernote
---

{{markdown}}

# Images
{% for image in images %}
- ![{{ image.name }}]({{image.name}})
{% endfor %}

Variables supplied to the template:

• year_month_day: The date the note was created (eg, 2024-05-12).
• markdown: The markdown content of the note.
• images: an array of image objects with the following properties:
  • name: The name of the image file.
  • rel_path: The relative path to the image file to where the file was run from.
  • abs_path: The absolute path to the image file.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

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

Acknowledgements

• Supernote for their amazing note-taking devices.
• LangChain for providing the core libraries used in this project.
• OpenAI for the GPT-4 model.