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Normalization and comparison tools for verifying model outputs against expected results.
Distinguishing note: Focuses on text normalization for evaluation rather than general string manipulation.
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DSPy 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-
Normalizes text outputs to ensure accurate comparisons against expected results during evaluation.