adai/MemoryBear
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fix/memory increment (#139)

Browse Source 
* [fix]Correct the display sequence of memory increments

* [fix]Correct the display sequence of memory increments

* [changes]Modify the code based on the AI review
This commit is contained in:
乐力齐
2026-01-19 10:46:53 +08:00
committed by GitHub
parent 2aca4ed67e
commit 825f257cf4
2 changed files with 42 additions and 32 deletions
Download Patch File Download Diff File Expand all files Collapse all files

56
api/app/controllers/emotion_controller.py
View File

@@ -59,7 +59,7 @@ async def get_emotion_tags(
"limit": request.limit
}
)
# 调用服务层
data = await emotion_service.get_emotion_tags(
end_user_id=request.group_id,
@@ -68,7 +68,7 @@ async def get_emotion_tags(
end_date=request.end_date,
limit=request.limit
)
api_logger.info(
"情绪标签统计获取成功",
extra={
@@ -77,9 +77,9 @@ async def get_emotion_tags(
"tags_count": len(data.get("tags", []))
}
)
return success(data=data, msg="情绪标签获取成功")
except Exception as e:
api_logger.error(
f"获取情绪标签统计失败: {str(e)}",
@@ -108,14 +108,14 @@ async def get_emotion_wordcloud(
"limit": request.limit
}
)
# 调用服务层
data = await emotion_service.get_emotion_wordcloud(
end_user_id=request.group_id,
emotion_type=request.emotion_type,
limit=request.limit
)
api_logger.info(
"情绪词云数据获取成功",
extra={
@@ -123,9 +123,9 @@ async def get_emotion_wordcloud(
"total_keywords": data.get("total_keywords", 0)
}
)
return success(data=data, msg="情绪词云获取成功")
except Exception as e:
api_logger.error(
f"获取情绪词云数据失败: {str(e)}",
@@ -152,7 +152,7 @@ async def get_emotion_health(
status_code=status.HTTP_400_BAD_REQUEST,
detail="时间范围参数无效，必须是 7d、30d 或 90d"
)
api_logger.info(
f"用户 {current_user.username} 请求获取情绪健康指数",
extra={
@@ -160,13 +160,13 @@ async def get_emotion_health(
"time_range": request.time_range
}
)
# 调用服务层
data = await emotion_service.calculate_emotion_health_index(
end_user_id=request.group_id,
time_range=request.time_range
)
api_logger.info(
"情绪健康指数获取成功",
extra={
@@ -175,9 +175,9 @@ async def get_emotion_health(
"level": data.get("level", "未知")
}
)
return success(data=data, msg="情绪健康指数获取成功")
except HTTPException:
raise
except Exception as e:
@@ -200,12 +200,12 @@ async def get_emotion_suggestions(
current_user: User = Depends(get_current_user),
):
"""获取个性化情绪建议（从缓存读取）
Args:
request: 包含 group_id 和可选的 config_id
db: 数据库会话
current_user: 当前用户
Returns:
缓存的个性化情绪建议响应
"""
@@ -217,13 +217,13 @@ async def get_emotion_suggestions(
"config_id": request.config_id
}
)
# 从缓存获取建议
data = await emotion_service.get_cached_suggestions(
end_user_id=request.group_id,
db=db
)
if data is None:
# 缓存不存在或已过期
api_logger.info(
@@ -235,7 +235,7 @@ async def get_emotion_suggestions(
"建议缓存不存在或已过期，请调用 /generate_suggestions 接口生成新建议",
None
)
api_logger.info(
"个性化建议获取成功（缓存）",
extra={
@@ -243,9 +243,9 @@ async def get_emotion_suggestions(
"suggestions_count": len(data.get("suggestions", []))
}
)
return success(data=data, msg="个性化建议获取成功（缓存）")
except Exception as e:
api_logger.error(
f"获取个性化建议失败: {str(e)}",
@@ -265,12 +265,12 @@ async def generate_emotion_suggestions(
current_user: User = Depends(get_current_user),
):
"""生成个性化情绪建议（调用LLM并缓存）
Args:
request: 包含 group_id、可选的 config_id 和 force_refresh
db: 数据库会话
current_user: 当前用户
Returns:
新生成的个性化情绪建议响应
"""
@@ -298,7 +298,7 @@ async def generate_emotion_suggestions(
return fail(BizCode.INVALID_PARAMETER, "配置ID无效", f"配置 {config_id} 不存在")
except Exception as e:
return fail(BizCode.INVALID_PARAMETER, "配置ID验证失败", str(e))
api_logger.info(
f"用户 {current_user.username} 请求生成个性化情绪建议",
extra={
@@ -306,13 +306,13 @@ async def generate_emotion_suggestions(
"config_id": config_id
}
)
# 调用服务层生成建议
data = await emotion_service.generate_emotion_suggestions(
end_user_id=request.group_id,
db=db
)
# 保存到缓存
await emotion_service.save_suggestions_cache(
end_user_id=request.group_id,
@@ -320,7 +320,7 @@ async def generate_emotion_suggestions(
db=db,
expires_hours=24
)
api_logger.info(
"个性化建议生成成功",
extra={
@@ -328,9 +328,9 @@ async def generate_emotion_suggestions(
"suggestions_count": len(data.get("suggestions", []))
}
)
return success(data=data, msg="个性化建议生成成功")
except Exception as e:
api_logger.error(
f"生成个性化建议失败: {str(e)}",