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Components that transform module inputs into structured prompts and parse model completions into typed data.
Distinguishing note: Focuses on the translation layer between application logic and LLM interfaces.
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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-
Provides automated transformation of inputs into structured prompts and parses model responses into consistent data formats.