Liu Embeddings¶

Welcome to Liu Embeddings—a lightweight semantic search framework that combines embedding generation with vector storage.

💡 What is Liu Embeddings?¶

Liu Embeddings = embedding + storage

Save your money on expensive embedding models

Built on HuggingFace embeddings and ChromaDB vector storage, it provides a unified solution for small to medium projects requiring efficient embedding, storage, and retrieval operations.

🚀 Why Choose Liu Embeddings?¶

⚡ Easy to Use¶

• Minimal setup - Get started in minutes, not hours
• Zero configuration - Works out of the box with sensible defaults
• Automatic dependency management - No manual ChromaDB or HuggingFace setup needed

💰 Cost-Effective¶

• No expensive API calls - Use open-source HuggingFace models instead of paid embedding services
• Self-hosted solution - Avoid recurring costs associated with cloud-based embedding APIs

🏗️ Production Ready¶

• Integrated logging - Comprehensive logging for debugging and monitoring
• Validation & error handling - Robust input validation and error messages
• Batch operations - Efficient batch ingestion and export to JSON

📚 Quick Navigation¶

🎯 Core Features¶

• Unified API: Single interface for both embedding generation and vector storage
• Multiple Models: Support for MiniLM, MPNet, E5, and BGE transformers
• Semantic Search: Fast, accurate similarity search with metadata filtering
• CRUD Operations: Complete Create, Read, Update, Delete capabilities
• Batch Processing: Handle large datasets efficiently
• Text Processing: Intelligent chunking with overlap preservation

📦 Installation¶

pip install liuembeddings

⚡ Quick Start¶

from liuembeddings import LiuEmbeddings, LiuVectorStore

# Initialize
embedder = LiuEmbeddings(model_name="USE")
store = LiuVectorStore(embedder, collection_name="my_docs")

# Add documents
store.add_texts([
    "Python is a programming language",
    "JavaScript is for web development"
])

# Search
results, documents = store.similarity_search("What is Python?", n_results=1)
print(documents)

🧪 Try It Now¶

Looking for hands-on examples? Check out:

• Quick Start Guide - Step-by-step tutorials
• Examples & Workflows - Complete working examples
• API Reference - Detailed method documentation

👨‍💻 For Developers¶

• Developer Guide - Architecture, setup, and migration info
• GitHub Repository
• Package on PyPI

📄 License¶

MIT License - Free to use in personal and commercial projects

🤝 Contribute¶

Found a bug? Have a feature request? Contributions are welcome! Visit our GitHub repository.

Ready to get started? Head over to the Quick Start Guide!