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[add] Add cache to RAG storage

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This commit is contained in:
lanceyq
2026-03-10 11:41:09 +08:00
parent e4aaa18f61
commit e2f5fa87b1
3 changed files with 159 additions and 63 deletions
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6
api/app/models/end_user_model.py
View File

@@ -51,6 +51,12 @@ class EndUser(Base):
growth_trajectory = Column(Text, nullable=True, comment="成长轨迹")
memory_insight_updated_at = Column(DateTime, nullable=True, comment="洞察报告最后更新时间")
# RAG存储模式专用字段 - RAG Storage Mode Fields
storage_type = Column(String, nullable=True, default="neo4j", comment="存储模式类型: neo4j / rag")
rag_tags = Column(Text, nullable=True, comment="RAG模式下提取的标签列表（JSON格式）")
rag_personas = Column(Text, nullable=True, comment="RAG模式下提取的人物形象列表（JSON格式）")
rag_summary_updated_at = Column(DateTime, nullable=True, comment="RAG摘要/标签/人物形象最后更新时间")
# 与 App 的反向关系
app = relationship(
"App",

84
api/app/repositories/end_user_repository.py
View File

@@ -220,6 +220,90 @@ class EndUserRepository:
db_logger.error(f"更新终端用户 {end_user_id} 的用户摘要缓存时出错: {str(e)}")
raise
def update_rag_summary_tags(
self,
end_user_id: uuid.UUID,
user_summary: str,
rag_tags: str,
rag_personas: str,
) -> bool:
"""更新RAG模式下的用户摘要、标签和人物形象缓存
Args:
end_user_id: 终端用户ID
user_summary: 用户摘要文本
rag_tags: 标签列表（JSON字符串）
rag_personas: 人物形象列表（JSON字符串）
Returns:
bool: 更新成功返回True，否则返回False
"""
try:
updated_count = (
self.db.query(EndUser)
.filter(EndUser.id == end_user_id)
.update(
{
EndUser.user_summary: user_summary,
EndUser.rag_tags: rag_tags,
EndUser.rag_personas: rag_personas,
EndUser.storage_type: "rag",
EndUser.rag_summary_updated_at: datetime.datetime.now(),
},
synchronize_session=False
)
)
self.db.commit()
if updated_count > 0:
db_logger.info(f"成功更新终端用户 {end_user_id} 的RAG摘要/标签/人物形象缓存")
return True
else:
db_logger.warning(f"未找到终端用户 {end_user_id}，无法更新RAG摘要缓存")
return False
except Exception as e:
self.db.rollback()
db_logger.error(f"更新终端用户 {end_user_id} 的RAG摘要缓存时出错: {str(e)}")
raise
def update_rag_insight(
self,
end_user_id: uuid.UUID,
memory_insight: str,
) -> bool:
"""更新RAG模式下的记忆洞察缓存
Args:
end_user_id: 终端用户ID
memory_insight: 洞察文本
Returns:
bool: 更新成功返回True，否则返回False
"""
try:
updated_count = (
self.db.query(EndUser)
.filter(EndUser.id == end_user_id)
.update(
{
EndUser.memory_insight: memory_insight,
EndUser.storage_type: "rag",
EndUser.memory_insight_updated_at: datetime.datetime.now(),
},
synchronize_session=False
)
)
self.db.commit()
if updated_count > 0:
db_logger.info(f"成功更新终端用户 {end_user_id} 的RAG洞察缓存")
return True
else:
db_logger.warning(f"未找到终端用户 {end_user_id}，无法更新RAG洞察缓存")
return False
except Exception as e:
self.db.rollback()
db_logger.error(f"更新终端用户 {end_user_id} 的RAG洞察缓存时出错: {str(e)}")
raise
def get_all_by_workspace(self, workspace_id: uuid.UUID) -> List[EndUser]:
"""获取工作空间的所有终端用户

132
api/app/services/memory_dashboard_service.py
View File

@@ -647,55 +647,63 @@ async def get_chunk_summary_and_tags(
) -> dict:
"""
获取chunk的总结、标签和人物形象
Args:
end_user_id: 宿主ID
limit: 返回的chunk数量限制
max_tags: 最大标签数量
db: 数据库会话
current_user: 当前用户
Returns:
包含summary、tags和personas的字典
优先返回end_user表中的缓存，若无缓存则实时生成并写库
"""
import json
from app.repositories.end_user_repository import EndUserRepository
business_logger.info(f"获取chunk摘要、标签和人物形象: end_user_id={end_user_id}, limit={limit}, 操作者: {current_user.username}")
try:
# 1. 获取chunk内容
repo = EndUserRepository(db)
end_user = repo.get_by_id(uuid.UUID(end_user_id))
# 读缓存：user_summary / rag_tags / rag_personas 均有值时直接返回
if (
end_user
and end_user.user_summary
and end_user.rag_tags
and end_user.rag_personas
):
business_logger.info(f"命中缓存，直接返回end_user {end_user_id} 的摘要/标签/人物形象")
return {
"summary": end_user.user_summary,
"tags": json.loads(end_user.rag_tags),
"personas": json.loads(end_user.rag_personas),
}
# 无缓存：实时生成
rag_content = get_rag_content(end_user_id, limit, db, current_user)
chunks = rag_content.get("contents", [])
if not chunks:
business_logger.warning(f"未找到chunk内容: end_user_id={end_user_id}")
return {
"summary": "暂无内容",
"tags": [],
"personas": []
}
# 2. 导入RAG工具函数
return {"summary": "暂无内容", "tags": [], "personas": []}
from app.core.rag_utils import generate_chunk_summary, extract_chunk_tags, extract_chunk_persona
# 3. 并发生成摘要、提取标签和人物形象
import asyncio
summary_task = generate_chunk_summary(chunks, max_chunks=limit, end_user_id=end_user_id)
tags_task = extract_chunk_tags(chunks, max_tags=max_tags, max_chunks=limit, end_user_id=end_user_id)
personas_task = extract_chunk_persona(chunks, max_personas=5, max_chunks=limit, end_user_id=end_user_id)
summary, tags_with_freq, personas = await asyncio.gather(summary_task, tags_task, personas_task)
# 4. 格式化标签数据
summary, tags_with_freq, personas = await asyncio.gather(
generate_chunk_summary(chunks, max_chunks=limit, end_user_id=end_user_id),
extract_chunk_tags(chunks, max_tags=max_tags, max_chunks=limit, end_user_id=end_user_id),
extract_chunk_persona(chunks, max_personas=5, max_chunks=limit, end_user_id=end_user_id),
)
tags = [{"tag": tag, "frequency": freq} for tag, freq in tags_with_freq]
result = {
"summary": summary,
"tags": tags,
"personas": personas
}
# 写库缓存
if end_user:
repo.update_rag_summary_tags(
end_user_id=end_user.id,
user_summary=summary,
rag_tags=json.dumps(tags, ensure_ascii=False),
rag_personas=json.dumps(personas, ensure_ascii=False),
)
result = {"summary": summary, "tags": tags, "personas": personas}
business_logger.info(f"成功获取chunk摘要、{len(tags)} 个标签和 {len(personas)} 个人物形象")
return result
except Exception as e:
business_logger.error(f"获取chunk摘要、标签和人物形象失败: end_user_id={end_user_id} - {str(e)}")
raise
@@ -709,42 +717,40 @@ async def get_chunk_insight(
) -> dict:
"""
获取chunk的洞察分析
Args:
end_user_id: 宿主ID
limit: 返回的chunk数量限制
db: 数据库会话
current_user: 当前用户
Returns:
包含insight的字典
优先返回end_user表中的缓存，若无缓存则实时生成并写库
"""
from app.repositories.end_user_repository import EndUserRepository
business_logger.info(f"获取chunk洞察: end_user_id={end_user_id}, limit={limit}, 操作者: {current_user.username}")
try:
# 1. 获取chunk内容
repo = EndUserRepository(db)
end_user = repo.get_by_id(uuid.UUID(end_user_id))
# 读缓存
if end_user and end_user.memory_insight:
business_logger.info(f"命中缓存，直接返回end_user {end_user_id} 的洞察")
return {"insight": end_user.memory_insight}
# 无缓存：实时生成
rag_content = get_rag_content(end_user_id, limit, db, current_user)
chunks = rag_content.get("contents", [])
if not chunks:
business_logger.warning(f"未找到chunk内容: end_user_id={end_user_id}")
return {
"insight": "暂无足够数据生成洞察报告"
}
# 2. 导入RAG工具函数
return {"insight": "暂无足够数据生成洞察报告"}
from app.core.rag_utils import generate_chunk_insight
# 3. 生成洞察
insight = await generate_chunk_insight(chunks, max_chunks=limit, end_user_id=end_user_id)
result = {
"insight": insight
}
# 写库缓存
if end_user:
repo.update_rag_insight(end_user_id=end_user.id, memory_insight=insight)
business_logger.info("成功获取chunk洞察")
return result
return {"insight": insight}
except Exception as e:
business_logger.error(f"获取chunk洞察失败: end_user_id={end_user_id} - {str(e)}")
raise