Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.

Features

  • Integrate AI models and workflows on any type of data directly with your existing databases
  • Develop composable AI workflows and future-proof your AI stack
  • Deploy Superduper on your existing infrastructure
  • Documentation available
  • By transforming the database into the central AI platform, Superduper consolidates enterprise AI

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Frameworks, Python LLM Inference Tool

Registered

2024-10-24