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Dspy prompt optimizer

Skill tangweigang-jpg/doramagic-skills/skills/dspy-prompt-optimizer

DSPy:把 LLM 程序写成可组合 Module + 声明式 Signature 的 Python 框架。通过 14 个 teleprompter(optimizer)从 train + dev 集自动编译 prompt 与 few-shot demo。 DSPy: a Python framework for building LLM programs as composable Modules with declarative Signatures. 14 teleprompter (optimizer) classes auto-compile prompts and few-shot demos from train + dev sets. LM access is unified via LiteLLM; 2-tier cache (LRU + diskcache).From its SKILL.md

Install
npx -y skills add tangweigang-jpg/doramagic-skills --skill dspy-prompt-optimizer

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SKILL.md

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这个 skill 适合什么用户?能做哪些任务?

概览

DSPy 是把 LLM 程序写成可组合 Module + 声明式 Signature 的 Python 框架(github.com/stanfordnlp/dspy)。可插拔 Adapter 格式化消息和解析响应;LM 客户端层包装 LiteLLM 提供统一 provider 访问;14 个 teleprompter (optimizer)类从 train + dev 集自动编译 prompt 和 few-shot demo。

下层是 2 层缓存(LRUCache 内存 + diskcache FanoutCache 磁盘)和 3 层遥测(Settings.trace、Module.hist...

Doramagic 晶体页: https://doramagic.ai/zh/crystal/dspy-prompt-optimizer

知识规模

  • 44 条约束 (8 fatal + 36 non-fatal)
  • 上游源码: stanfordnlp/dspy @ commit da4ae194
  • 蓝图 ID: finance-bp-137

用法

Host AI(Claude Code / Cursor / OpenClaw)读 references/seed.yaml,按其中的:

  • intent_router 匹配用户意图
  • architecture 理解项目架构
  • constraints 应用 anti-pattern 约束
  • business_decisions 参考核心设计决策

FAQ 摘要

这个 skill 适合什么用户?能做哪些任务?

适合需要把 LLM 流水线工程化的研究员和工程师:用 Signature 替代手写prompt、用 teleprompter(如 MIPROv2、BootstrapFewShot)从数据自动优化 prompt + few-shot。覆盖 RAG / agent / 分类 / 抽取等用例。访问 doramagic.ai/r/dspy 查看完整说明。

需要准备什么环境?依赖什么?

Python 3.10+,至少一个 LM provider 通过 LiteLLM 访问(默认接受 'provider/model' 字符串如 'openai/gpt-4o-mini');可写磁盘用于 ~/.dspy_cache(或 DSPY_CACHEDIR 覆盖)。MIPROv2 离散搜索可选 optuna(懒加载);asyncify 可选 anyio。

会踩哪些坑?这个 skill 怎么防护?

本 skill 内置 44 条约束(8 条 fatal)。CRITICAL 安全坑:(1) 默认 Cache(restrict_pickle=False) + diskcache pickle.load 在被污染的 ~/.dspy_cache shard 上 = RCE,无用户 opt-in;(2) MIPROv2 估算 LM 调用数但不在超预算时中止(静默失控成本);


完整文档: 见 references/seed.yaml (v6.1 schema). 浏览页: https://doramagic.ai/zh/crystal/dspy-prompt-optimizer

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