prompts/optimize_prompt.yaml

name: optimize_prompt
description: 优化prompt
format: jinja2
temperature: 0.7
max_tokens: 4000
prompt: |
  你是一个专业的meta prompt工程师，请基于下面的prompt分析，改进老版prompt。

  prompt分析如下：
  <analysis>
  {{report}}
  </analysis>

  老版prompt如下:
  <oldPrompt>
  {{prompt}}
  </oldPrompt>

  参考上面的分析，改进老版prompt，内容包含：
  <template>
  [定义清晰、专业角色，描述任务的意图和应用场景]

  [列出输入参数，用xml标签包裹，模型参数用"\{\{ \}\}"表示，jinja2格式渲染]

  [列出任务的关键步骤、要求、定义等]

  [列出对任务有帮助的分析，并在prompt中说明要置于<analysis>标签中]

  [格式要求]

  [引导开始，并在prompt中说明结果输出要置于<output>标签中]
  </template>

  按照每块的要求，直接生成内容，不要列出标题，不要遗漏老版prompt中的关键内容，例如下面的示例：

  <example>
  You are an intelligent text classification system specialized in matching sentences to Wikipedia article titles. Your task is to identify which Wikipedia article a given sentence most likely belongs to, based on a provided list of article titles.

  First, review the following list of Wikipedia article titles:
  <article_titles>
  {titles}
  </article_titles>

  Now, consider this sentence that needs to be classified:
  <sentence_to_classify>
  {sentence}
  </sentence_to_classify>

  Your goal is to determine which article title from the provided list best matches the given sentence. Follow these steps:

  1. List the key concepts from the sentence
  2. Compare each key concept with the article titles
  3. Rank the top 3 most relevant titles and explain why they are relevant
  4. Select the most appropriate article title that best encompasses or relates to the sentence's content

  Wrap your analysis in <analysis> tags. Include the following:
  - List of key concepts from the sentence
  - Comparison of each key concept with the article titles
  - Ranking of top 3 most relevant titles with explanations
  - Your final choice and reasoning

  After your analysis, provide your final answer: the single most appropriate Wikipedia article title from the list.

  Output only the chosen article title, without any additional text or explanation.
  </example>

  在<prompt>标签中输出新版prompt，不要输出其他内容，用{{language}}输出。