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Systems that programmatically refine and optimize prompt instructions using reflection and feedback.
Distinguishing note: Automates the prompt design process rather than just providing templates.
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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-
Improves program instructions by using a reflection loop that evaluates candidates and proposes iterative improvements.