| title | emoji | colorFrom | colorTo | sdk | app_file | pinned | 
|---|---|---|---|---|---|---|
Lightweight Embeddings API  | 
  👻 / 🧬  | 
  purple  | 
  indigo  | 
  docker  | 
  app.py  | 
  false  | 
  
LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.
- Free and Unlimited: A completely free API service with no limits on usage, making it accessible for everyone.
 - Multilingual Support: Seamlessly process text in over 100+ languages for global applications.
 - Text and Image Embeddings: Generate high-quality embeddings from text or image-text pairs using state-of-the-art models.
 - Reranking Support: Includes powerful reranking capabilities for both text and image inputs.
 - Optimized for Speed: Built with lightweight transformer models and efficient backends for rapid inference, even on low-resource systems.
 - Flexible Model Support: Use a range of transformer models tailored to diverse use cases:
- Text models: 
snowflake-arctic-embed-l-v2.0,bge-m3,gte-multilingual-base,paraphrase-multilingual-MiniLM-L12-v2,paraphrase-multilingual-mpnet-base-v2,multilingual-e5-small,multilingual-e5-base,multilingual-e5-large. - Image model: 
siglip-base-patch16-256-multilingual 
 - Text models: 
 - Production-Ready: Easily deploy anywhere with Docker for hassle-free setup.
 - Interactive Playground: Test embeddings and reranking directly via a Gradio-powered interface alongside detailed REST API documentation.
 
- Search and Ranking: Generate embeddings for advanced similarity-based ranking in search engines.
 - Recommendation Systems: Use embeddings for personalized recommendations based on user input or preferences.
 - Multimodal Applications: Combine text and image embeddings to power tasks like product catalog indexing, content moderation, or multimodal retrieval.
 - Language Understanding: Enable semantic text analysis, summarization, or classification in multiple languages.
 
git clone https://github.com/lh0x00/lightweight-embeddings.git
cd lightweight-embeddingsMake sure Docker is installed and running on your machine.
docker build -t lightweight-embeddings .
docker run -p 7860:7860 lightweight-embeddingsThe API will now be accessible at http://localhost:7860.
/v1/embeddings: Generate text or image embeddings using the model of your choice./v1/rank: Rank candidate inputs based on similarity to a query.
- Visit the Swagger UI for detailed, interactive documentation.
 - Explore additional resources with ReDoc.
 
- Test text and image embedding generation in the browser with a user-friendly Gradio interface.
 - Simply visit 
http://localhost:7860after starting the server to access the playground. 
- Documentation: Explore full documentation
 - Hugging Face Space: Try the live demo
 - GitHub Repository: View source code
 
- Performance-Oriented: Delivers rapid results without compromising on quality, ideal for real-world deployment.
 - Highly Adaptable: Works in diverse environments, from cloud clusters to local devices.
 - Developer-Friendly: Intuitive API design with robust documentation and an integrated playground for experimentation.
 
- lamhieu / lh0x00 – Creator and Maintainer (GitHub, HuggingFace)
 
Contributions are welcome! Check out the contribution guidelines.
This project is licensed under the MIT License. See the LICENSE file for details.