Superlinked is a Python framework designed for AI engineers to build high-performance search and recommendation systems. It uniquely combines structured and unstructured data by encoding metadata alongside content into vectors, enhancing search relevance and enabling sophisticated querying.

How It Works

Superlinked allows users to define custom embedding models by composing pre-trained encoders (e.g., from sentence-transformers, open-clip) with custom encoders for numerical, categorical, and temporal data. This approach facilitates the creation of multi-modal vector spaces that capture complex relationships. The framework supports updating vectors with behavioral events and allows for query-time weighting and natural language querying, powered by LLMs.

Quick Start & Requirements

• Install: %pip install superlinked
• Prerequisites: Python, OpenAI API key for natural language query feature.
• Example: The README provides a comprehensive Python example demonstrating schema definition, index creation, data ingestion, and querying.
• Documentation: https://docs.superlinked.com/

Highlighted Details

• Supports embedding diverse data types: Text, Image, Number, Category, Time, Event.
• Integrates with popular vector databases: Redis, MongoDB, Qdrant.
• Enables RAG, semantic search, recommendation systems, and analytics use cases.
• Offers a self-hostable REST API server for production deployments.

Maintenance & Community

• Active development indicated by recent commits.
• Community support via GitHub issues and discussions for bug reports, feature requests, and general inquiries.
• Resources include a Vector DB Comparison and VectorHub learning hub.

Licensing & Compatibility

• License: Apache License 2.0.
• Compatibility: Permissive license suitable for commercial use and integration with closed-source applications.

Limitations & Caveats

The framework is actively evolving, with a mention of "early access" for managed cloud offerings, suggesting some features or services might be in beta or under development. The natural language query feature requires an OpenAI API key.