Merge branch 'release/v0.3.0' into develop
* release/v0.3.0: (44 commits) Revert "fix(web): prompt editor" fix(web): prompt editor fix(prompt-optimizer): handle escaped quotes in JSON parsing fix(custom-tools): remove parameter coercion in custom tool base class fix(core): conditionally apply thinking parameters based on model support refactor(custom-tools): coerce query and request body parameters to schema types fix(prompt-optimizer): support list content type in prompt optimizer refactor(memory): unify user placeholder names and harden alias sync logic fix(rag): replace semicolon separators with newlines in Excel parser output fix(web): Compatible with Windows whitespace fix(memory): make PgSQL the single source of truth for user entity aliases refactor(rag): simplify Excel parsing logic and remove redundant chunk_token_num assignment fix(web): Hide error message when workflow node error message equals empty string ci(wechat-notify): add Sourcery summary extraction with Qwen fallback fix(http-request,embedding,naive): tighten form-data validation, reduce truncation length to 8000, and disable chunking for Excel fix(web): adjust the value of End User Name fix(http-request): support array and file variables in form-data files upload fix(web): change http body key name fix(web): header user name fix(web): calculate using the filtered breadcrumbs length ... # Conflicts: # web/src/views/UserMemoryDetail/Neo4j.tsx # web/src/views/UserMemoryDetail/components/EndUserProfile.tsx # web/src/views/UserMemoryDetail/types.ts
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Mark
@@ -14,6 +14,7 @@ from pydantic import BaseModel, Field
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from sqlalchemy.orm import Session
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from app.core.logging_config import get_logger
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from app.core.memory.storage_services.extraction_engine.deduplication.deduped_and_disamb import _USER_PLACEHOLDER_NAMES
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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.conversation_repository import ConversationRepository
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@@ -21,7 +22,7 @@ from app.repositories.end_user_repository import EndUserRepository
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from app.repositories.neo4j.cypher_queries import Graph_Node_query
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from app.repositories.neo4j.neo4j_connector import Neo4jConnector
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from app.schemas.memory_episodic_schema import EmotionSubject, EmotionType, 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, MIN_MEMORY_SUMMARY_COUNT
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from app.services.memory_config_service import MemoryConfigService
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from app.services.memory_perceptual_service import MemoryPerceptualService
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from app.services.memory_short_service import ShortService
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@@ -477,7 +478,7 @@ class UserMemoryService:
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allowed_fields = {'other_name', 'aliases', 'meta_data'}
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# 用户占位名称黑名单，不允许作为 other_name 或出现在 aliases 中
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_user_placeholder_names = {'用户', '我', 'User', 'I'}
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_user_placeholder_names = _USER_PLACEHOLDER_NAMES
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# 过滤 other_name：不允许设置为占位名称
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if 'other_name' in update_data and update_data['other_name'] and update_data['other_name'].strip() in _user_placeholder_names:
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@@ -1504,7 +1505,7 @@ async def analytics_memory_types(
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2. 工作记忆 (WORKING_MEMORY) = 会话数量（通过 ConversationRepository.get_conversation_by_user_id 获取）
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3. 短期记忆 (SHORT_TERM_MEMORY) = /short_term 接口返回的问答对数量
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4. 显性记忆 (EXPLICIT_MEMORY) = 情景记忆 + 语义记忆（通过 MemoryBaseService.get_explicit_memory_count 获取）
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5. 隐性记忆 (IMPLICIT_MEMORY) = Statement 节点数量的三分之一
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5. 隐性记忆 (IMPLICIT_MEMORY) = MemorySummary 节点数量（需 >= MIN_MEMORY_SUMMARY_COUNT 才显示，否则为 0）
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6. 情绪记忆 (EMOTIONAL_MEMORY) = 情绪标签统计总数（通过 MemoryBaseService.get_emotional_memory_count 获取）
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7. 情景记忆 (EPISODIC_MEMORY) = memory_summary（通过 MemoryBaseService.get_episodic_memory_count 获取）
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8. 遗忘记忆 (FORGET_MEMORY) = 激活值低于阈值的节点数（通过 MemoryBaseService.get_forget_memory_count 获取）
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@@ -1561,23 +1562,15 @@ async def analytics_memory_types(
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logger.warning(f"获取会话数量失败，工作记忆数量设为0: {str(e)}")
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work_count = 0
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# 获取隐性记忆数量（基于 Statement 节点数量的三分之一）
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# 获取隐性记忆数量（基于有关联关系的 MemorySummary 节点数量，需 >= MIN_MEMORY_SUMMARY_COUNT 才计入）
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implicit_count = 0
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if end_user_id:
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try:
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# 查询 Statement 节点数量
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query = """
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MATCH (n:Statement)
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WHERE n.end_user_id = $end_user_id
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RETURN count(n) as count
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"""
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result = await _neo4j_connector.execute_query(query, end_user_id=end_user_id)
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statement_count = result[0]["count"] if result and len(result) > 0 else 0
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# 取三分之一作为隐性记忆数量
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implicit_count = round(statement_count / 3)
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logger.debug(f"隐性记忆数量（Statement数量的1/3）: {implicit_count} (Statement总数={statement_count}, end_user_id={end_user_id})")
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memory_summary_count = await base_service.get_valid_memory_summary_count(end_user_id)
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implicit_count = memory_summary_count if memory_summary_count >= MIN_MEMORY_SUMMARY_COUNT else 0
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logger.debug(f"隐性记忆数量（有效MemorySummary节点数）: {implicit_count} (有效MemorySummary总数={memory_summary_count}, end_user_id={end_user_id})")
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except Exception as e:
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logger.warning(f"获取Statement数量失败，隐性记忆数量设为0: {str(e)}")
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logger.warning(f"获取MemorySummary数量失败，隐性记忆数量设为0: {str(e)}")
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implicit_count = 0
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# 原有的基于行为习惯的统计方式（已注释）
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@@ -1643,7 +1636,7 @@ async def analytics_memory_types(
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"WORKING_MEMORY": work_count, # 工作记忆（基于会话数量）
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"SHORT_TERM_MEMORY": short_term_count, # 短期记忆（基于问答对数量）
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"EXPLICIT_MEMORY": explicit_count, # 显性记忆（情景记忆 + 语义记忆）
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"IMPLICIT_MEMORY": implicit_count, # 隐性记忆（Statement数量的1/3）
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"IMPLICIT_MEMORY": implicit_count, # 隐性记忆（MemorySummary节点数，需>=MIN_MEMORY_SUMMARY_COUNT）
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"EMOTIONAL_MEMORY": emotion_count, # 情绪记忆（使用情绪标签统计）
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"EPISODIC_MEMORY": episodic_count, # 情景记忆
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"FORGET_MEMORY": forget_count # 遗忘记忆（激活值低于阈值）
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