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Awesome GitHub RepositoriesInterpretable AI Logic
Methods for extracting human-readable rules from model demonstrations to enhance program logic.
Distinguishing note: Focuses on rule extraction for interpretability rather than raw performance optimization.
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Awesome Interpretable AI Logic GitHub Repositories
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- stanfordnlp/dspy
stanfordnlp/dspy
32,291View on GitHubDSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently. The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-
Refines program logic by extracting clear rules from bootstrapped demonstrations.
Python
