用户详情优化
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@@ -11,6 +11,26 @@ from pydantic import BaseModel, Field, ConfigDict, field_validator, model_valida
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# ============================================================================
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# ============================================================================
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# 原 UserInput 相关 Schema (保留原有功能)
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# 原 UserInput 相关 Schema (保留原有功能)
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# ============================================================================
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# ============================================================================
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type_mapping = {
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"Person": "人物实体节点",
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"Organization": "组织实体节点",
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"ORG": "组织实体节点",
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"Location": "地点实体节点",
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"LOC": "地点实体节点",
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"Event": "事件实体节点",
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"Concept": "概念实体节点",
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"Time": "时间实体节点",
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"Position": "职位实体节点",
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"WorkRole": "职业实体节点",
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"System": "系统实体节点",
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"Policy": "政策实体节点",
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"HistoricalPeriod": "历史时期实体节点",
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"HistoricalState": "历史国家实体节点",
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"HistoricalEvent": "历史事件实体节点",
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"EconomicFactor": "经济因素实体节点",
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"Condition": "条件实体节点",
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"Numeric": "数值实体节点"
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}
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class UserInput(BaseModel):
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class UserInput(BaseModel):
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message: str
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message: str
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history: list[dict]
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history: list[dict]
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@@ -123,7 +123,7 @@ class MemoryEntityService:
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extracted_entity_list = self._deduplicate_dict_list(extracted_entity_list)
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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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# 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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all_timeline_data = self._merge_same_text_items(all_timeline_data)
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result = {
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result = {
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@@ -15,6 +15,7 @@ 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.db import get_db_context
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from app.repositories.end_user_repository import EndUserRepository
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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.repositories.neo4j.neo4j_connector import Neo4jConnector
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from app.schemas.memory_storage_schema import type_mapping
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from app.services.memory_base_service import MemoryBaseService
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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 app.services.memory_config_service import MemoryConfigService
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from pydantic import BaseModel, Field
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from pydantic import BaseModel, Field
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@@ -1332,7 +1333,7 @@ async def analytics_graph_data(
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db: Session,
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db: Session,
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end_user_id: str,
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end_user_id: str,
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node_types: Optional[List[str]] = None,
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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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depth: int = 1,
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center_node_id: Optional[str] = None
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center_node_id: Optional[str] = None
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) -> Dict[str, Any]:
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) -> Dict[str, Any]:
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@@ -1576,10 +1577,11 @@ 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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for field in allowed_fields:
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if field in properties:
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if field in properties:
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value = properties[field]
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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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# 清理 Neo4j 特殊类型
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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[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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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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return filtered_props
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