feat(memory): add episodic memory pagination and semantic memory list API

Split explicit memory overview into two independent endpoints:
- GET /memory/explicit-memory/episodics: episodic memory paginated query
  with date range filter (millisecond timestamp) and episodic type filter
  using Neo4j datetime() for precise time comparison
- GET /memory/explicit-memory/semantics: semantic memory full list query
  returns data as array directly

Modified files:
- api/app/controllers/memory_explicit_controller.py
- api/app/services/memory_explicit_service.py
This commit is contained in:
miao
2026-04-23 12:05:31 +08:00
parent fc7d9df3cb
commit 5c836c90c9
2 changed files with 342 additions and 3 deletions

View File

@@ -4,7 +4,10 @@
处理显性记忆相关的API接口包括情景记忆和语义记忆的查询。
"""
from fastapi import APIRouter, Depends
from datetime import date
from typing import Optional
from fastapi import APIRouter, Depends, Query
from app.core.logging_config import get_api_logger
from app.core.response_utils import success, fail
@@ -69,6 +72,140 @@ async def get_explicit_memory_overview_api(
return fail(BizCode.INTERNAL_ERROR, "显性记忆总览查询失败", str(e))
@router.get("/episodics", response_model=ApiResponse)
async def get_episodic_memory_list_api(
end_user_id: str = Query(..., description="end user ID"),
page: int = Query(1, gt=0, description="page number, starting from 1"),
pagesize: int = Query(10, gt=0, le=100, description="number of items per page, max 100"),
start_date: Optional[int] = Query(None, description="start timestamp (ms)"),
end_date: Optional[int] = Query(None, description="end timestamp (ms)"),
episodic_type: str = Query("all", description="episodic type all/conversation/project_work/learning/decision/important_event"),
current_user: User = Depends(get_current_user),
) -> dict:
"""
获取情景记忆分页列表
返回指定用户的情景记忆列表,支持分页、时间范围筛选和情景类型筛选。
Args:
end_user_id: 终端用户ID必填
page: 页码从1开始默认1
pagesize: 每页数量默认10最大100
start_date: 开始时间戳(可选,毫秒),自动扩展到当天 00:00:00
end_date: 结束时间戳(可选,毫秒),自动扩展到当天 23:59:59
episodic_type: 情景类型筛选可选默认all
current_user: 当前用户
Returns:
ApiResponse: 包含情景记忆分页列表
Examples:
- 基础分页查询GET /episodic-list?end_user_id=xxx&page=1&pagesize=5
返回第1页每页5条数据
- 按时间范围筛选GET /episodic-list?end_user_id=xxx&page=1&pagesize=5&start_date=1738684800000&end_date=1738771199000
返回指定时间范围内的数据
- 按情景类型筛选GET /episodic-list?end_user_id=xxx&page=1&pagesize=5&episodic_type=important_event
返回类型为"重要事件"的数据
Notes:
- start_date 和 end_date 必须同时提供或同时不提供
- start_date 不能大于 end_date
- episodic_type 可选值all, conversation, project_work, learning, decision, important_event
- total 为该用户情景记忆总数(不受筛选条件影响)
- page.total 为筛选后的总条数
"""
workspace_id = current_user.current_workspace_id
# 检查用户是否已选择工作空间
if workspace_id is None:
api_logger.warning(f"用户 {current_user.username} 尝试查询情景记忆列表但未选择工作空间")
return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None")
api_logger.info(
f"情景记忆分页查询: end_user_id={end_user_id}, "
f"start_date={start_date}, end_date={end_date}, episodic_type={episodic_type}, "
f"page={page}, pagesize={pagesize}, username={current_user.username}"
)
# 1. 参数校验
if page < 1 or pagesize < 1:
api_logger.warning(f"分页参数错误: page={page}, pagesize={pagesize}")
return fail(BizCode.INVALID_PARAMETER, "分页参数必须大于0")
valid_episodic_types = ["all", "conversation", "project_work", "learning", "decision", "important_event"]
if episodic_type not in valid_episodic_types:
api_logger.warning(f"无效的情景类型参数: {episodic_type}")
return fail(BizCode.INVALID_PARAMETER, f"无效的情景类型参数,可选值:{', '.join(valid_episodic_types)}")
# 时间戳参数校验
if (start_date is not None and end_date is None) or (end_date is not None and start_date is None):
return fail(BizCode.INVALID_PARAMETER, "start_date和end_date必须同时提供")
if start_date is not None and end_date is not None and start_date > end_date:
return fail(BizCode.INVALID_PARAMETER, "start_date不能大于end_date")
# 2. 执行查询
try:
result = await memory_explicit_service.get_episodic_memory_list(
end_user_id=end_user_id,
page=page,
pagesize=pagesize,
start_date=start_date,
end_date=end_date,
episodic_type=episodic_type,
)
api_logger.info(
f"情景记忆分页查询成功: end_user_id={end_user_id}, "
f"total={result['total']}, 返回={len(result['items'])}"
)
except Exception as e:
api_logger.error(f"情景记忆分页查询失败: end_user_id={end_user_id}, error={str(e)}")
return fail(BizCode.INTERNAL_ERROR, "情景记忆分页查询失败", str(e))
# 3. 返回结构化响应
return success(data=result, msg="查询成功")
@router.get("/semantics", response_model=ApiResponse)
async def get_semantic_memory_list_api(
end_user_id: str = Query(..., description="终端用户ID"),
current_user: User = Depends(get_current_user),
) -> dict:
"""
获取语义记忆列表
返回指定用户的全量语义记忆列表。
Args:
end_user_id: 终端用户ID必填
current_user: 当前用户
Returns:
ApiResponse: 包含语义记忆全量列表
"""
workspace_id = current_user.current_workspace_id
if workspace_id is None:
api_logger.warning(f"用户 {current_user.username} 尝试查询语义记忆列表但未选择工作空间")
return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None")
api_logger.info(
f"语义记忆列表查询: end_user_id={end_user_id}, username={current_user.username}"
)
try:
result = await memory_explicit_service.get_semantic_memory_list(
end_user_id=end_user_id
)
api_logger.info(
f"语义记忆列表查询成功: end_user_id={end_user_id}, total={len(result)}"
)
except Exception as e:
api_logger.error(f"语义记忆列表查询失败: end_user_id={end_user_id}, error={str(e)}")
return fail(BizCode.INTERNAL_ERROR, "语义记忆列表查询失败", str(e))
return success(data=result, msg="查询成功")
@router.post("/details", response_model=ApiResponse)
async def get_explicit_memory_details_api(
request: ExplicitMemoryDetailsRequest,