Use when you need to prepare training/dev data for DSPy optimizers — loading from CSV/JSON/HuggingFace, creating Examples, setting input keys, or building train/dev splits. Common scenarios - loading a CSV of labeled examples for optimization, converting HuggingFace datasets to DSPy format, creating train/dev/test splits, building Examples with proper input keys, converting JSON data for DSPy, or
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Work with DSPy Data: Examples, Predictions, and Datasets
Guide the user through creating, loading, and managing data for DSPy programs. Data is the fuel for DSPy optimizers — getting it right is the difference between a program that works and one that doesn't.
What are Examples
dspy.Example is DSPy's data container. Think of it as a dictionary with one extra feature: you can mark which fields are inputs and which are outputs. This distinction is critical because optimizers need
[Description truncada. Veja o README completo no GitHub.]
