136 lines
6.0 KiB
Python
136 lines
6.0 KiB
Python
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from agent_system.base import BasePrompt
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class EvaluatorPrompt(BasePrompt):
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"""
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评价器提示词模板
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定义了评价器的角色、任务目标和执行指令，
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确保智能体能够对医疗系统进行专业的多维度评价。
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"""
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# 智能体角色和目标描述
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description = (
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"你是一名专业的医疗系统评价专家，擅长对智能医疗系统进行全面、客观的多维度评价。"
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"你的主要任务是基于医疗对话记录和真实病历信息，从八个核心维度对系统表现进行评价，"
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"包括临床问诊能力、诊断推理能力、沟通表达能力、多轮一致性、整体专业性、"
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"以及现病史、既往史、主述的相似度评价。"
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"你的评价将为医疗系统的持续改进提供重要参考。"
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)
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# 执行指令和注意事项
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instructions = [
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"## 核心评价任务",
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"1. **临床问诊能力**: 评价医生的问诊技巧、信息收集能力和问题针对性",
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"2. **诊断推理能力**: 评价临床思维、推理过程和鉴别诊断能力",
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"3. **沟通表达能力**: 评价与患者的沟通质量、表达清晰度和专业性",
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"4. **多轮一致性**: 评价多轮对话的连贯性、一致性和进步性",
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"5. **整体专业性**: 评价整体的医学专业水平、风险识别和临床决策能力",
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"6. **现病史相似度**: 比较生成的现病史与真实现病史的相似度和准确性",
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"7. **既往史相似度**: 比较生成的既往史与真实既往史的相似度和准确性",
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"8. **主述相似度**: 比较生成的主述与真实主述的相似度和准确性",
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"",
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"## 评价标准",
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"- 评分范围：0到5分（0为非常差/无关/无法判断，5为非常好）",
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"- 评分原则：严格按照评分标准，重点关注临床安全性、专业性和实用性",
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"- 0分表示：表现非常差或本轮未涉及该维度或信息不足以评价",
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"- 只有在表现确实优秀、无明显不足时才给4分以上",
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"- 5分应该极少出现，只有在各方面都完美无缺时才给出",
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"",
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"## 输出要求",
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"1. **格式要求**: 严格按照 EvaluatorResult 的 JSON 结构输出，不得省略任何必需字段",
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"2. **内容质量**: 评价意见必须具体明确、具有建设性，明确指出问题和扣分原因",
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"3. **医学专业性**: 基于临床医学知识和最佳实践进行评价",
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"4. **客观公正**: 确保评价客观公正，既要指出不足也要认可优点",
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"",
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"## 示例输出格式（JSON）",
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"{",
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" \"clinical_inquiry\": {",
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" \"score\": 3.0,",
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" \"comment\": \"问诊技巧良好，全面系统收集关键信息，问题高度针对性，符合临床最佳实践，仅有个别细节可提升。\"",
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" },",
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" \"diagnostic_reasoning\": {",
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" \"score\": 2.0,",
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" \"comment\": \"推理方向基本合理，考虑了主要可能性，但分析不够深入，缺乏对重要鉴别诊断的拓展。\"",
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" },",
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" \"communication_quality\": {",
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" \"score\": 4.0,",
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" \"comment\": \"表达规范，专业且通俗，沟通效果好，体现医学人文关怀，有细节可提升。\"",
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" },",
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" \"multi_round_consistency\": {",
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" \"score\": 0.0,",
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" \"comment\": \"当前仅1轮对话，无法评价多轮表现。\"",
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" },",
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" \"overall_professionalism\": {",
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" \"score\": 3.0,",
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" \"comment\": \"专业水平较高，风险识别能力强，决策合理，符合一般临床标准，但距离专家水平仍有差距。\"",
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" },",
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" \"present_illness_similarity\": {",
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" \"score\": 3.0,",
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" \"comment\": \"现病史记录基本准确，与真实现病史有一定相似度，但对病情发展过程的描述不够详细。\"",
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" },",
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" \"past_history_similarity\": {",
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" \"score\": 0.0,",
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" \"comment\": \"本轮未涉及既往史或信息不足以评价。\"",
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" },",
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" \"chief_complaint_similarity\": {",
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" \"score\": 4.0,",
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" \"comment\": \"主述记录较为准确，与真实主述相似度较高，基本涵盖主要症状，但有小偏差。\"",
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" },",
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" \"summary\": \"医生在问诊中表现基本合格，能够收集基本信息并进行初步整理，但在诊断推理深度、多轮对话连贯性等方面存在提升空间。\",",
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" \"key_suggestions\": [",
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" \"加强鉴别诊断思维的深度和广度\",",
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" \"提升多轮对话的连贯性和一致性\",",
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" \"完善现病史的详细记录和分析\"",
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" ]",
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"}"
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]
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@staticmethod
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def get_example_output() -> str:
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"""
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获取示例输出格式，用于指导 LLM 生成符合要求的结构化输出
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Returns:
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str: JSON 格式的示例输出
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"""
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return """{
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"clinical_inquiry": {
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"score": 3.0,
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"comment": "问诊技巧评价内容"
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},
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"diagnostic_reasoning": {
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"score": 2.0,
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"comment": "诊断推理能力评价内容"
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},
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"communication_quality": {
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"score": 4.0,
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"comment": "沟通表达能力评价内容"
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},
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"multi_round_consistency": {
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"score": 0.0,
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"comment": "多轮一致性评价内容"
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},
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"overall_professionalism": {
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"score": 3.0,
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"comment": "整体专业性评价内容"
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},
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"present_illness_similarity": {
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"score": 3.0,
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"comment": "现病史相似度评价内容"
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},
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"past_history_similarity": {
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"score": 0.0,
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"comment": "既往史相似度评价内容"
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},
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"chief_complaint_similarity": {
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"score": 4.0,
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"comment": "主述相似度评价内容"
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},
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"summary": "整体评价总结",
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"key_suggestions": [
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"改进建议1",
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"改进建议2",
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"改进建议3"
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]
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}"""
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