Fix/language unification (#283)
* [changes]add user_summary language unification * [add]Entity extraction, user memory, emotion suggestions, unified language type for writing * [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields. * [changes]add user_summary language unification * [add]Entity extraction, user memory, emotion suggestions, unified language type for writing * [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields. * [changes]Modify the code based on the AI review
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乐力齐
@@ -57,24 +57,57 @@ class EmotionAnalyticsService:
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self.emotion_repo = EmotionRepository(connector)
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logger.info("情绪分析服务初始化完成")
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# 情绪类型的中英文映射
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EMOTION_TYPE_TRANSLATIONS = {
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'joy': {'zh': '喜悦', 'en': 'Joy'},
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'sadness': {'zh': '悲伤', 'en': 'Sadness'},
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'anger': {'zh': '愤怒', 'en': 'Anger'},
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'fear': {'zh': '恐惧', 'en': 'Fear'},
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'surprise': {'zh': '惊讶', 'en': 'Surprise'},
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'neutral': {'zh': '中性', 'en': 'Neutral'}
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}
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def _translate_emotion_type(self, emotion_type: str, language: str = "zh") -> str:
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"""将情绪类型翻译成指定语言
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Args:
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emotion_type: 情绪类型（英文key）
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language: 目标语言 ("zh" 或 "en")
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Returns:
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翻译后的情绪类型名称
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"""
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if emotion_type in self.EMOTION_TYPE_TRANSLATIONS:
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return self.EMOTION_TYPE_TRANSLATIONS[emotion_type].get(language, emotion_type)
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return emotion_type
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async def get_emotion_tags(
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self,
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end_user_id: str,
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emotion_type: Optional[str] = None,
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start_date: Optional[str] = None,
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end_date: Optional[str] = None,
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limit: int = 10
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limit: int = 10,
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language: str = "zh"
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) -> Dict[str, Any]:
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"""获取情绪标签统计
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查询指定用户的情绪类型分布，包括计数、百分比和平均强度。
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确保返回所有6个情绪维度（joy、sadness、anger、fear、surprise、neutral），
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即使某些维度没有数据也会返回count=0的记录。
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Args:
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end_user_id: 用户ID
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emotion_type: 情绪类型过滤
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start_date: 开始日期
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end_date: 结束日期
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limit: 返回数量限制
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language: 输出语言 ("zh" 中文, "en" 英文)
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"""
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try:
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logger.info(f"获取情绪标签统计: user={end_user_id}, type={emotion_type}, "
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f"start={start_date}, end={end_date}, limit={limit}")
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f"start={start_date}, end={end_date}, limit={limit}, language={language}")
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# 调用仓储层查询
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tags = await self.emotion_repo.get_emotion_tags(
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@@ -91,15 +124,17 @@ class EmotionAnalyticsService:
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# 将查询结果转换为字典，方便查找
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tags_dict = {tag["emotion_type"]: tag for tag in tags}
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# 补全缺失的情绪维度
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# 补全缺失的情绪维度，并翻译 emotion_type
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complete_tags = []
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for emotion in all_emotion_types:
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if emotion in tags_dict:
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complete_tags.append(tags_dict[emotion])
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tag = tags_dict[emotion].copy()
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tag["emotion_type"] = self._translate_emotion_type(emotion, language)
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complete_tags.append(tag)
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else:
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# 如果该情绪类型不存在，添加默认值
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complete_tags.append({
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"emotion_type": emotion,
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"emotion_type": self._translate_emotion_type(emotion, language),
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"count": 0,
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"percentage": 0.0,
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"avg_intensity": 0.0
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@@ -475,6 +510,7 @@ class EmotionAnalyticsService:
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self,
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end_user_id: str,
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db: Session,
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language: str = "zh",
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) -> Dict[str, Any]:
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"""生成个性化情绪建议
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@@ -483,6 +519,7 @@ class EmotionAnalyticsService:
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Args:
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end_user_id: 宿主ID（用户组ID）
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db: 数据库会话
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language: 输出语言 ("zh" 中文, "en" 英文)
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Returns:
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Dict: 包含个性化建议的响应：
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@@ -533,7 +570,7 @@ class EmotionAnalyticsService:
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user_profile = await self._get_simple_user_profile(end_user_id)
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# 6. 构建LLM prompt
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prompt = await self._build_suggestion_prompt(health_data, patterns, user_profile)
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prompt = await self._build_suggestion_prompt(health_data, patterns, user_profile, language)
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# 7. 调用LLM生成建议（使用配置中的LLM）
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if llm_client is None:
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@@ -554,12 +591,12 @@ class EmotionAnalyticsService:
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except Exception as e:
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logger.error(f"LLM 结构化输出失败: {str(e)}")
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# 返回默认建议
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suggestions_response = self._get_default_suggestions(health_data)
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suggestions_response = self._get_default_suggestions(health_data, language)
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# 8. 验证建议数量（3-5条）
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if len(suggestions_response.suggestions) < 3:
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logger.warning(f"建议数量不足: {len(suggestions_response.suggestions)}")
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suggestions_response = self._get_default_suggestions(health_data)
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suggestions_response = self._get_default_suggestions(health_data, language)
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elif len(suggestions_response.suggestions) > 5:
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logger.warning(f"建议数量过多: {len(suggestions_response.suggestions)}")
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suggestions_response.suggestions = suggestions_response.suggestions[:5]
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@@ -624,7 +661,8 @@ class EmotionAnalyticsService:
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self,
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health_data: Dict[str, Any],
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patterns: Dict[str, Any],
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user_profile: Dict[str, Any]
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user_profile: Dict[str, Any],
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language: str = "zh"
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) -> str:
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"""构建情绪建议生成的prompt
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@@ -632,6 +670,7 @@ class EmotionAnalyticsService:
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health_data: 情绪健康数据
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patterns: 情绪模式分析结果
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user_profile: 用户画像数据
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language: 输出语言 ("zh" 中文, "en" 英文)
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Returns:
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str: LLM prompt
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@@ -643,66 +682,114 @@ class EmotionAnalyticsService:
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prompt = await render_emotion_suggestions_prompt(
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health_data=health_data,
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patterns=patterns,
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user_profile=user_profile
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user_profile=user_profile,
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language=language
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)
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return prompt
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def _get_default_suggestions(self, health_data: Dict[str, Any]) -> EmotionSuggestionsResponse:
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def _get_default_suggestions(self, health_data: Dict[str, Any], language: str = "zh") -> EmotionSuggestionsResponse:
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"""获取默认建议（当LLM调用失败时使用）
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Args:
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health_data: 情绪健康数据
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language: 输出语言 ("zh" 中文, "en" 英文)
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Returns:
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EmotionSuggestionsResponse: 默认建议
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"""
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health_score = health_data.get('health_score', 0)
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if health_score >= 80:
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summary = "您的情绪健康状况优秀，请继续保持积极的生活态度。"
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elif health_score >= 60:
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summary = "您的情绪健康状况良好，可以通过一些调整进一步提升。"
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elif health_score >= 40:
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summary = "您的情绪健康需要关注，建议采取一些改善措施。"
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else:
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summary = "您的情绪健康需要重点关注，建议寻求专业帮助。"
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if language == "en":
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if health_score >= 80:
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summary = "Your emotional health is excellent. Keep up the positive attitude."
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elif health_score >= 60:
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summary = "Your emotional health is good. Some adjustments can further improve it."
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elif health_score >= 40:
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summary = "Your emotional health needs attention. Consider taking improvement measures."
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else:
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summary = "Your emotional health needs serious attention. Consider seeking professional help."
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suggestions = [
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EmotionSuggestion(
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type="emotion_balance",
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title="保持情绪平衡",
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content="通过正念冥想和深呼吸练习，帮助您更好地管理情绪波动，提升情绪稳定性。",
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priority="high",
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actionable_steps=[
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"每天早晨进行5-10分钟的正念冥想",
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"感到情绪波动时，进行3次深呼吸",
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"记录每天的情绪变化，识别触发因素"
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]
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),
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EmotionSuggestion(
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type="activity_recommendation",
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title="增加户外活动",
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content="适度的户外运动可以有效改善情绪，增强身心健康。建议每周进行3-4次户外活动。",
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priority="medium",
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actionable_steps=[
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"每周安排2-3次30分钟的散步",
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"周末尝试户外运动如骑行或爬山",
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"在户外活动时关注周围环境，放松心情"
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]
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),
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EmotionSuggestion(
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type="social_connection",
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title="加强社交联系",
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content="与朋友和家人保持良好的社交联系，可以提供情感支持，改善情绪健康。",
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priority="medium",
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actionable_steps=[
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"每周至少与一位朋友或家人深入交流",
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"参加感兴趣的社交活动或兴趣小组",
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"主动分享自己的感受和想法"
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]
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)
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]
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suggestions = [
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EmotionSuggestion(
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type="Emotion Balance",
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title="Maintain Emotional Balance",
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content="Through mindfulness meditation and deep breathing exercises, help you better manage emotional fluctuations and improve emotional stability.",
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priority="High",
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actionable_steps=[
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"Practice 5-10 minutes of mindfulness meditation every morning",
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"Take 3 deep breaths when feeling emotional fluctuations",
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"Record daily emotional changes to identify triggers"
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]
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),
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EmotionSuggestion(
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type="Activity Recommendation",
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title="Increase Outdoor Activities",
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content="Moderate outdoor exercise can effectively improve mood and enhance physical and mental health. Recommend 3-4 outdoor activities per week.",
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priority="Medium",
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actionable_steps=[
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"Schedule 2-3 30-minute walks per week",
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"Try outdoor sports like cycling or hiking on weekends",
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"Focus on surroundings and relax during outdoor activities"
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]
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),
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EmotionSuggestion(
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type="Social Connection",
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title="Strengthen Social Connections",
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content="Maintaining good social connections with friends and family can provide emotional support and improve emotional health.",
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priority="Medium",
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actionable_steps=[
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"Have a deep conversation with at least one friend or family member weekly",
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"Join social activities or interest groups you enjoy",
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"Actively share your feelings and thoughts"
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]
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)
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]
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else:
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if health_score >= 80:
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summary = "您的情绪健康状况优秀，请继续保持积极的生活态度。"
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elif health_score >= 60:
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summary = "您的情绪健康状况良好，可以通过一些调整进一步提升。"
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elif health_score >= 40:
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summary = "您的情绪健康需要关注，建议采取一些改善措施。"
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else:
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summary = "您的情绪健康需要重点关注，建议寻求专业帮助。"
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suggestions = [
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EmotionSuggestion(
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type="情绪平衡",
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title="保持情绪平衡",
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content="通过正念冥想和深呼吸练习，帮助您更好地管理情绪波动，提升情绪稳定性。",
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priority="高",
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actionable_steps=[
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"每天早晨进行5-10分钟的正念冥想",
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"感到情绪波动时，进行3次深呼吸",
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"记录每天的情绪变化，识别触发因素"
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]
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),
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EmotionSuggestion(
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type="活动建议",
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title="增加户外活动",
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content="适度的户外运动可以有效改善情绪，增强身心健康。建议每周进行3-4次户外活动。",
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priority="中",
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actionable_steps=[
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"每周安排2-3次30分钟的散步",
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"周末尝试户外运动如骑行或爬山",
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"在户外活动时关注周围环境，放松心情"
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]
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),
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EmotionSuggestion(
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type="社交联系",
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title="加强社交联系",
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content="与朋友和家人保持良好的社交联系，可以提供情感支持，改善情绪健康。",
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priority="中",
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actionable_steps=[
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"每周至少与一位朋友或家人深入交流",
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"参加感兴趣的社交活动或兴趣小组",
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"主动分享自己的感受和想法"
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]
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)
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]
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return EmotionSuggestionsResponse(
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health_summary=summary,
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