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dspy-refine

Iterative self-improvement with dspy.Refine -- wraps any module, scores each attempt with a reward function, generates feedback on failures, and retries until a quality threshold is met. Use when you want outputs to improve through self-critique, need iterative revision of drafts, or want the LM to learn from its own mistakes within a single request. Also used for self-critique and revise, iterati

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Atualizado há 4 meses

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Como adicionar

/plugin marketplace add lebsral/DSPy-Programming-not-prompting-LMs-skills

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

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Ler descrição completa

Iterative Self-Improvement with dspy.Refine

Step 1: Understand the use case

Before writing code, clarify:

  1. What module are you wrapping? (ChainOfThought, Predict, ReAct, custom module?)
  2. What makes a good output? Can you express quality as a numeric score?
  3. How many retries are acceptable? (cost/latency budget)
  4. Is feedback useful? Would knowing why attempt 1 failed help attempt 2? If not, consider dspy.BestOfN instead.

When to use Refine (and when not to)

[Description truncada. Veja o README completo no GitHub.]

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