Use when you need DSPy infrastructure - caching control, debugging with inspect_history, saving/loading optimized programs, or runtime validation with Refine/BestOfN. Common scenarios - controlling the cache to avoid stale results, debugging with inspect_history to see raw prompts, saving and loading optimized programs, or validating outputs with reward functions. For streaming see /dspy-streaming
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DSPy Utilities: Caching, Debugging, Save/Load, and Validation
Guide the user through DSPy's utility functions -- controlling caching, debugging calls, persisting optimized programs, and enforcing runtime constraints with reward functions.
Looking for streaming, async, or MCP? These have dedicated skills now:
- Streaming tokens to a UI -- see /dspy-streaming
- Async execution and FastAPI -- see /dspy-async
- MCP server integration -- see /dspy-mcp
Step 1: Which utility d
[Description truncada. Veja o README completo no GitHub.]