Merge #21 into develop from feature/emotion-engine

feature/情绪引擎

* feature/emotion-engine: (7 commits squashed)

  - [feature]Emotion Engine Development

  - [feature]Emotion Engine Development

  - Merge branch 'feature/emotion-engine' of codeup.aliyun.com:redbearai/python/redbear-mem-open into feature/emotion-engine

  - [fix]1.Fix the front-end files;2.Cache Management Deletion;3.Delete "check_code.py"

  - [fix]1.Fix the front-end files;2.Cache Management Deletion;3.Delete "check_code.py"

  - Merge branch 'feature/emotion-engine' of codeup.aliyun.com:redbearai/python/redbear-mem-open into feature/emotion-engine

  - [fix]fix vite.config.ts

Signed-off-by: 乐力齐 <accounts_690c7b0af9007d7e338af636@mail.teambition.com>
Commented-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>
Commented-by: 乐力齐 <accounts_690c7b0af9007d7e338af636@mail.teambition.com>
Reviewed-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>
Merged-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>

CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/21

api/app/repositories/neo4j/emotion_repository.py

@@ -0,0 +1,246 @@
+# -*- coding: utf-8 -*-
+"""情绪数据仓储模块
+
+本模块提供情绪数据的查询功能，用于情绪分析和统计。
+
+Classes:
+    EmotionRepository: 情绪数据仓储，提供情绪标签、词云、健康指数等查询方法
+"""
+
+from typing import List, Dict, Optional, Any
+from datetime import datetime, timedelta
+import json
+
+from app.repositories.neo4j.neo4j_connector import Neo4jConnector
+from app.core.logging_config import get_business_logger
+
+logger = get_business_logger()
+
+
+class EmotionRepository:
+    """情绪数据仓储
+    
+    提供情绪数据的查询和统计功能，包括：
+    - 情绪标签统计
+    - 情绪词云数据
+    - 时间范围内的情绪数据查询
+    
+    Attributes:
+        connector: Neo4j连接器实例
+    """
+    
+    def __init__(self, connector: Neo4jConnector):
+        """初始化情绪数据仓储
+        
+        Args:
+            connector: Neo4j连接器实例
+        """
+        self.connector = connector
+        logger.info("情绪数据仓储初始化完成")
+    
+    async def get_emotion_tags(
+        self,
+        group_id: str,
+        emotion_type: Optional[str] = None,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        limit: int = 10
+    ) -> List[Dict[str, Any]]:
+        """获取情绪标签统计
+        
+        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。
+        
+        Args:
+            group_id: 用户组ID（宿主ID）
+            emotion_type: 可选的情绪类型过滤（joy/sadness/anger/fear/surprise/neutral）
+            start_date: 可选的开始日期（ISO格式字符串）
+            end_date: 可选的结束日期（ISO格式字符串）
+            limit: 返回结果的最大数量
+            
+        Returns:
+            List[Dict]: 情绪标签列表，每个包含：
+                - emotion_type: 情绪类型
+                - count: 该类型的数量
+                - percentage: 占比百分比
+                - avg_intensity: 平均强度
+        """
+        # 构建查询条件
+        where_clauses = ["s.group_id = $group_id", "s.emotion_type IS NOT NULL"]
+        params = {"group_id": group_id, "limit": limit}
+        
+        if emotion_type:
+            where_clauses.append("s.emotion_type = $emotion_type")
+            params["emotion_type"] = emotion_type
+        
+        if start_date:
+            where_clauses.append("s.created_at >= $start_date")
+            params["start_date"] = start_date
+        
+        if end_date:
+            where_clauses.append("s.created_at <= $end_date")
+            params["end_date"] = end_date
+        
+        where_str = " AND ".join(where_clauses)
+        
+        # 优化的 Cypher 查询：使用索引，减少中间结果
+        query = f"""
+        MATCH (s:Statement)
+        WHERE {where_str}
+        WITH s.emotion_type as emotion_type, 
+             count(*) as count,
+             avg(s.emotion_intensity) as avg_intensity
+        WITH collect({{emotion_type: emotion_type, count: count, avg_intensity: avg_intensity}}) as results,
+             sum(count) as total_count
+        UNWIND results as result
+        RETURN result.emotion_type as emotion_type,
+               result.count as count,
+               toFloat(result.count) / total_count * 100 as percentage,
+               result.avg_intensity as avg_intensity
+        ORDER BY count DESC
+        LIMIT $limit
+        """
+        
+        try:
+            results = await self.connector.execute_query(query, **params)
+            formatted_results = [
+                {
+                    "emotion_type": record["emotion_type"],
+                    "count": record["count"],
+                    "percentage": round(record["percentage"], 2),
+                    "avg_intensity": round(record["avg_intensity"], 3) if record["avg_intensity"] else 0.0
+                }
+                for record in results
+            ]
+            
+            return formatted_results
+        except Exception as e:
+            logger.error(f"查询情绪标签失败: {str(e)}", exc_info=True)
+            return []
+    
+    async def get_emotion_wordcloud(
+        self,
+        group_id: str,
+        emotion_type: Optional[str] = None,
+        limit: int = 50
+    ) -> List[Dict[str, Any]]:
+        """获取情绪词云数据
+        
+        查询情绪关键词及其频率，用于生成词云可视化。
+        
+        Args:
+            group_id: 用户组ID（宿主ID）
+            emotion_type: 可选的情绪类型过滤
+            limit: 返回关键词的最大数量
+            
+        Returns:
+            List[Dict]: 关键词列表，每个包含：
+                - keyword: 关键词
+                - frequency: 出现频率
+                - emotion_type: 关联的情绪类型
+                - avg_intensity: 平均强度
+        """
+        # 构建查询条件
+        where_clauses = ["s.group_id = $group_id", "s.emotion_keywords IS NOT NULL"]
+        params = {"group_id": group_id, "limit": limit}
+        
+        if emotion_type:
+            where_clauses.append("s.emotion_type = $emotion_type")
+            params["emotion_type"] = emotion_type
+        
+        where_str = " AND ".join(where_clauses)
+        
+        # 优化的 Cypher 查询：使用索引，减少不必要的计算
+        query = f"""
+        MATCH (s:Statement)
+        WHERE {where_str}
+        UNWIND s.emotion_keywords as keyword
+        WITH keyword, 
+             s.emotion_type as emotion_type,
+             count(*) as frequency,
+             avg(s.emotion_intensity) as avg_intensity
+        WHERE keyword IS NOT NULL AND keyword <> ''
+        RETURN keyword,
+               frequency,
+               emotion_type,
+               avg_intensity
+        ORDER BY frequency DESC
+        LIMIT $limit
+        """
+        
+        try:
+            results = await self.connector.execute_query(query, **params)
+            formatted_results = [
+                {
+                    "keyword": record["keyword"],
+                    "frequency": record["frequency"],
+                    "emotion_type": record["emotion_type"],
+                    "avg_intensity": round(record["avg_intensity"], 3) if record["avg_intensity"] else 0.0
+                }
+                for record in results
+            ]
+            
+            return formatted_results
+        except Exception as e:
+            logger.error(f"查询情绪词云失败: {str(e)}", exc_info=True)
+            return []
+    
+    async def get_emotions_in_range(
+        self,
+        group_id: str,
+        time_range: str = "30d"
+    ) -> List[Dict[str, Any]]:
+        """获取时间范围内的情绪数据
+        
+        查询指定时间范围内的所有情绪数据，用于健康指数计算。
+        
+        Args:
+            group_id: 用户组ID（宿主ID）
+            time_range: 时间范围（7d/30d/90d）
+            
+        Returns:
+            List[Dict]: 情绪数据列表，每个包含：
+                - emotion_type: 情绪类型
+                - emotion_intensity: 情绪强度
+                - created_at: 创建时间
+                - statement_id: 陈述句ID
+        """
+        # 解析时间范围
+        days_map = {"7d": 7, "30d": 30, "90d": 90}
+        days = days_map.get(time_range, 30)
+        
+        # 计算起始日期（使用字符串比较，避免时区问题）
+        start_date = (datetime.now() - timedelta(days=days)).isoformat()
+        
+        # 优化的 Cypher 查询：使用字符串比较避免时区问题
+        query = """
+        MATCH (s:Statement)
+        WHERE s.group_id = $group_id
+          AND s.emotion_type IS NOT NULL
+          AND s.created_at >= $start_date
+        RETURN s.id as statement_id,
+               s.emotion_type as emotion_type,
+               s.emotion_intensity as emotion_intensity,
+               s.created_at as created_at
+        ORDER BY s.created_at ASC
+        """
+        
+        try:
+            results = await self.connector.execute_query(
+                query,
+                group_id=group_id,
+                start_date=start_date
+            )
+            formatted_results = [
+                {
+                    "statement_id": record["statement_id"],
+                    "emotion_type": record["emotion_type"],
+                    "emotion_intensity": record["emotion_intensity"],
+                    "created_at": record["created_at"].isoformat() if hasattr(record["created_at"], "isoformat") else str(record["created_at"])
+                }
+                for record in results
+            ]
+            
+            return formatted_results
+        except Exception as e:
+            logger.error(f"查询时间范围情绪数据失败: {str(e)}", exc_info=True)
+            return []