Fix/memory bug fix (#111)
* 图谱数据量限制数量去掉 * 图谱数据量限制数量去掉 * 图谱数据量限制数量去掉 * 用户详情优化 * 用户详情优化 * 用户详情优化 * 用户详情优化 * 用户详情优化
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@@ -15,6 +15,8 @@ from neo4j.time import DateTime as Neo4jDateTime
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import json
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from datetime import datetime
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from app.schemas.memory_episodic_schema import EmotionType
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logger = logging.getLogger(__name__)
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class MemoryEntityService:
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@@ -123,7 +125,7 @@ class MemoryEntityService:
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extracted_entity_list = self._deduplicate_dict_list(extracted_entity_list)
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# 合并所有数据并处理相同text的合并
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all_timeline_data = memory_summary_list + statement_list + extracted_entity_list
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all_timeline_data = memory_summary_list + statement_list
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all_timeline_data = self._merge_same_text_items(all_timeline_data)
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result = {
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@@ -496,11 +498,11 @@ class MemoryEmotion:
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length_data.append(emotion_intensity)
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if emotion_type is not None and emotion_intensity is not None and formatted_created_at is not None:
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# 使用(emotion_type, created_at)作为分组键
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if emotion_type in {"joy", "surprise"}:
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if emotion_type in {EmotionType.JOY_TYPE, EmotionType.SURPRISE_TYPE}:
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emotion_type='positive'
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elif emotion_type in {"sadness", "fear", "anger"}:
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elif emotion_type in {EmotionType.SANDROWNESS_TYPE, EmotionType.FEAR_TYPE, EmotionType.ANGET_TYPE}:
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emotion_type='negative'
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elif emotion_type=='neutral':
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elif emotion_type==EmotionType.NEUTRAL_TYPE:
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emotion_type='neutral'
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group_key = (emotion_type, formatted_created_at)
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# 累加emotion_intensity
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@@ -15,6 +15,8 @@ from app.core.memory.utils.llm.llm_utils import MemoryClientFactory
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from app.db import get_db_context
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from app.repositories.end_user_repository import EndUserRepository
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from app.repositories.neo4j.neo4j_connector import Neo4jConnector
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from app.schemas.memory_episodic_schema import type_mapping, EmotionType, EmotionSubject
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from app.services.memory_base_service import MemoryBaseService
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from app.services.memory_config_service import MemoryConfigService
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from pydantic import BaseModel, Field
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@@ -1332,7 +1334,7 @@ async def analytics_graph_data(
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db: Session,
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end_user_id: str,
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node_types: Optional[List[str]] = None,
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limit: int = 100,
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limit: int = 130,
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depth: int = 1,
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center_node_id: Optional[str] = None
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) -> Dict[str, Any]:
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@@ -1416,12 +1418,14 @@ async def analytics_graph_data(
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elementId(n) as id,
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labels(n)[0] as label,
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properties(n) as properties
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LIMIT $limit
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"""
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node_params = {
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"group_id": end_user_id,
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# "limit": limit
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"limit": limit
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}
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# 执行节点查询
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node_results = await _neo4j_connector.execute_query(node_query, **node_params)
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@@ -1576,10 +1580,15 @@ async def _extract_node_properties(label: str, properties: Dict[str, Any],node_
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for field in allowed_fields:
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if field in properties:
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value = properties[field]
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if str(field) == 'entity_type':
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value=type_mapping.get(value,'')
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if str(field)=="emotion_type":
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value=EmotionType.EMOTION_MAPPING.get(value)
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if str(field)=="emotion_subject":
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value=EmotionSubject.SUBJECT_MAPPING.get(value)
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# 清理 Neo4j 特殊类型
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filtered_props[field] = _clean_neo4j_value(value)
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filtered_props['associative_memory']=[i['rel_count'] for i in node_results][0]
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print(filtered_props)
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return filtered_props
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