📦 embed-classify-cli

Node.js CLI tool for local text classification using word embeddings.

🚀 Features

• 🔄 Convert CSV to JSON embeddings using Xenova/all-MiniLM-L6-v2
• 🧠 Classify unlabelled text via pre-trained embeddings
• 📈 Optional evaluation of dataset performance
• 🗃️ Works with CSVs containing category and comment headers

Ideal for local NLP classification workflows.

📦 Getting Started

git clone https://github.com/allemandi/embed-classify-cli.git
cd embed-classify-cli
yarn install
yarn start

🛠️ Usage

1. Prepare Your CSVs

Input CSV files must include:

• category: Label for training data
• comment: Text content to embed or classify

2. Generate Embeddings

Generate embedding.json from labeled CSV:

node index.js csv-embedding -i ./data/training.csv

3. Classify New Text

Use trained embeddings to classify new input:

node index.js embedding-classification -i ./data/unclassified.csv -c ./data/embedding.json -o ./data/predicted.csv

Check configurable flags in index.js for more options.

⚙️ Configure Classification

Tune classification behavior in embedding-classification.js with these params:

• --weightedVotes
  Use averaged similarity scores
• --comparisonPercentage
  % of top similar samples to compare (0–100)
• --maxSamplesToSearch
  Limit how many samples are compared
• --similarityThresholdPercent
  Minimum cosine similarity to include in comparison

🔗 Related Projects

Check out these related projects that might interest you:

• Embed Classify Web
  Sleek, modern web app for text classification using embeddings.

• @allemandi/embed-utils
  Utilities for text classification using cosine similarity embeddings.

• Vector Knowledge Base
  A minimalist command-line knowledge system with semantic memory capabilities using vector embeddings for information retrieval.

🤝 Contributing

If you have ideas, improvements, or new features:

1. Fork the project
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

☕ Support

If this project has helped you or saved you time, consider buying me a coffee to help fuel more ideas and improvements!

💡 Acknowledgments

This project was developed with the help of AI tools (e.g., GitHub Copilot, Cursor, v0) for code suggestions, debugging, and optimizations.

📄 License

MIT