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A Neuro-Symbolic Perspective on Large Language Models (LLMs)
Building applications with LLMs at the core using our Symbolic API facilitates the integration of classical and differentiable programming in Python.

Conceptually, SymbolicAI is a framework that leverages machine learning – specifically LLMs – as its foundation, and composes operations based on task-specific prompting. We adopt a divide-and-conquer approach to break down a complex problem into smaller, more manageable problems. Consequently, each operation addresses a simpler task. By reassembling these operations, we can resolve the complex problem. Moreover, our design principles enable us to transition seamlessly between differentiable and classical programming, allowing us to harness the power of both paradigms.

https://github.com/Xpitfire/symbolicai