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Fix/develop memory deail (#71)

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* 新增记忆空间详情

* 新增记忆空间详情

* 新增记忆关联的数量

* 修改记忆时间线

* 修改记忆时间线

* 修改记忆时间线

* Parameterize elementId in Cypher query

* 关系演化，互动频率优化

* 关系演化，互动频率优化

* 关系演化，互动频率优化

* 关系演化，互动频率优化

* 关系演化，互动频率优化

* 关系演化，互动频率优化

* 修改日期

* 修改日期

* 修改日期

* 修改日期

* 修改日期

* 修改日期

* 修改日期

* 输出删除多嵌套的data

---------

Co-authored-by: Ke Sun <33739460+keeees@users.noreply.github.com>
This commit is contained in:
lixinyue11
2026-01-12 13:55:21 +08:00
committed by GitHub
parent f6ca6a547f
commit eb7374cedc
1 changed files with 43 additions and 56 deletions
Download Patch File Download Diff File Expand all files Collapse all files

99
api/app/services/memory_entity_relationship_service.py
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@@ -64,24 +64,11 @@ class MemoryEntityService:
logger.info(f"成功获取时间线记忆数据: 总计 {len(timeline_data.get('timelines_memory', []))} 条")
return {
'success': True,
'data': timeline_data,
}
return timeline_data
except Exception as e:
logger.error(f"获取时间线记忆数据失败: {str(e)}", exc_info=True)
return {
'success': False,
'error': str(e),
'data': {
"MemorySummary": [],
"Statement": [],
"ExtractedEntity": [],
"timelines_memory": []
},
'total': 0
}
return str(e)
def _process_timeline_results(self, results: List[Dict[str, Any]]) -> Dict[str, Any]:
"""
处理时间线查询结果
@@ -432,7 +419,7 @@ class MemoryEmotion:
# 解析ISO格式的日期时间
dt = datetime.fromisoformat(iso_string.replace('Z', '+00:00'))
# 返回用户友好的格式：YYYY-MM-DD HH:MM:SS
return dt.strftime("%Y-%m-%d %H:%M:%S")
return dt.strftime("%Y.%m")
except (ValueError, AttributeError):
# 如果解析失败，返回原始字符串
return iso_string
@@ -463,37 +450,32 @@ class MemoryEmotion:
logger.info(f"成功获取 {len(final_data)} 条情绪数据")
return {
'success': True,
'data': final_data,
'total': len(final_data)
}
return final_data
except Exception as e:
logger.error(f"获取情绪数据失败: {str(e)}")
return {
'success': False,
'error': str(e),
'data': [],
'total': 0
}
return e
def _process_emotion_results(self, results: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""
处理情绪查询结果
处理情绪查询结果，按emotion_type和created_at分组并累加emotion_intensity
Args:
results: Neo4j查询结果
Returns:
处理后的情绪数据列表
处理后的情绪数据列表，相同emotion_type和created_at的记录会合并并累加intensity
"""
emotion_data = []
length_data=[]
from collections import defaultdict
# 用于按(emotion_type, created_at)分组累加intensity
emotion_groups = defaultdict(float)
# 检查results是否为空或不是列表
if not results or not isinstance(results, list):
logger.warning(f"情绪查询结果为空或格式不正确: {type(results)}")
return emotion_data
return []
for record in results:
# 检查record是否为字典类型
@@ -511,15 +493,33 @@ class MemoryEmotion:
emotion_type = record.get('emotion_type')
emotion_intensity = record.get('emotion_intensity')
if emotion_type !=None:
length_data.append(emotion_intensity)
if emotion_type is not None and emotion_intensity is not None:
# 只保留情绪相关的字段
emotion_record = {
'emotion_intensity': emotion_intensity,
'emotion_type': emotion_type,
'created_at': formatted_created_at
}
emotion_data.append(emotion_record)
if emotion_type is not None and emotion_intensity is not None and formatted_created_at is not None:
# 使用(emotion_type, created_at)作为分组键
group_key = (emotion_type, formatted_created_at)
# 累加emotion_intensity
try:
emotion_groups[group_key] += float(emotion_intensity)
except (ValueError, TypeError):
logger.warning(f"无法转换emotion_intensity为数字: {emotion_intensity}")
continue
# 转换为最终格式
emotion_data = [
{
'emotion_intensity': round(intensity / len(length_data) * 100, 2),
'emotion_type': emotion_type,
'created_at': created_at
}
for (emotion_type, created_at), intensity in emotion_groups.items()
]
# 按时间排序（最新的在前）
emotion_data.sort(key=lambda x: x.get('created_at', ''), reverse=True)
return emotion_data
@@ -593,7 +593,7 @@ class MemoryInteraction:
group_id = ori_data[0]['group_id']
Space_User = await self.connector.execute_query(Memory_Space_User, group_id=group_id)
if not Space_User:
return "不存在用户"
return '不存在用户'
user_id=Space_User[0]['id']
results = await self.connector.execute_query(Memory_Space_Associative, id=self.id,user_id=user_id)
@@ -608,25 +608,12 @@ class MemoryInteraction:
logger.info(f"成功获取 {len(final_data)} 条交互数据")
return {
'success': True,
'data': final_data,
'total': len(final_data)
}
return {
'success': False,
'data': [],
'total': 0
}
return final_data
return []
except Exception as e:
logger.error(f"获取交互数据失败: {str(e)}")
return {
'success': False,
'error': str(e),
'data': [],
'total': 0
}
return e
def _process_interaction_results(self, results: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""