embedding

A local UI package for turning a zip of .md or .txt chunks into embedding vectors.

What it does

• launches with the embedding command
• lets you choose an embedding model from a dropdown or type a custom model name
• reads a zip of .md or .txt files
• creates one embedding vector per file
• exports a zip with:
  • embedding_summary.json
  • embedding_manifest.csv
  • *_embeddings.jsonl (optional)
  • *_embeddings.csv (optional)
  • *_embeddings.npz (optional)

Install

pip install embedding

Run

embedding

Suggested input

Use a zip produced after your chunking step, such as the recursive chunk zip that contains many small .md chunk files.

Suggested output use

• jsonl for readable records and pipelines
• csv for spreadsheet-style inspection
• npz for loading embeddings directly into NumPy / Python

Notes

• This package creates embeddings from local text files using sentence-transformers models.
• It does not call an LLM by itself.
• It stores one vector per input chunk file.

Ownership note

The package metadata and copyright notice are set to Wenxi Wang. You should still verify PyPI package-name availability, trademark questions, and any legal or patent issues yourself before publishing.