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Basic modules that map inputs to outputs using a language model.
Distinguishing note: Focuses on the fundamental prediction unit, distinct from complex agentic modules.
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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-
Maps inputs to outputs using a language model as the fundamental prediction unit.