From 8abd59b26e82214e61ad31c5dc3984a805c5cb76 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Thu, 2 Apr 2026 13:02:21 +0800 Subject: [PATCH] changes:(controllers & services) The method for calculating general data is extracted and presented as a shared function. --- .../memory_dashboard_controller.py | 117 +++--------------- api/app/services/memory_dashboard_service.py | 64 +++++++++- 2 files changed, 77 insertions(+), 104 deletions(-) diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index 32ab8f60..525fe1eb 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -591,7 +591,7 @@ async def dashboard_data( "total_api_call": None } - # 1. 获取记忆总量（total_memory） + # 1. 获取记忆总量（total_memory）—— neo4j 独有逻辑：查询 neo4j 存储节点 try: total_memory_data = await memory_dashboard_service.get_workspace_total_memory_count( db=db, @@ -600,60 +600,14 @@ async def dashboard_data( end_user_id=end_user_id ) neo4j_data["total_memory"] = total_memory_data.get("total_memory_count", 0) - # total_app: 统计当前空间下的所有app数量 - # 包含自有app + 被分享给本工作空间的app - from app.services import app_service as _app_svc - _, total_app = _app_svc.AppService(db).list_apps( - workspace_id=workspace_id, include_shared=True, pagesize=1 - ) - neo4j_data["total_app"] = total_app - api_logger.info(f"成功获取记忆总量: {neo4j_data['total_memory']}, 应用数量: {neo4j_data['total_app']}") + api_logger.info(f"成功获取记忆总量: {neo4j_data['total_memory']}") except Exception as e: api_logger.warning(f"获取记忆总量失败: {str(e)}") - # 2. 获取知识库数量（total_knowledge） - # 逻辑：统计 knowledges 表中 workspace_id = 当前工作空间 且 parent_id = workspace_id 的记录数 - # 即只统计顶层知识库（parent_id 指向所属工作空间） - try: - from sqlalchemy import func as _func - from app.models.knowledge_model import Knowledge as _Knowledge - total_knowledge = db.query(_func.count(_Knowledge.id)).filter( - _Knowledge.workspace_id == workspace_id, - _Knowledge.status == 1, - _Knowledge.parent_id == _Knowledge.workspace_id - ).scalar() or 0 - neo4j_data["total_knowledge"] = total_knowledge - api_logger.info(f"成功获取知识库数量: {neo4j_data['total_knowledge']}") - except Exception as e: - api_logger.warning(f"获取知识库数量失败: {str(e)}") - - # 3. 获取API调用统计（total_api_call）—— 仅统计当天api_key_log调用次数 - try: - from datetime import datetime - from sqlalchemy import func as _api_func - from app.models.api_key_model import ApiKey as _ApiKey, ApiKeyLog as _ApiKeyLog - - _now = datetime.now() - _today_start = _now.replace(hour=0, minute=0, second=0, microsecond=0) - - _api_key_ids = [ - row[0] for row in db.query(_ApiKey.id).filter( - _ApiKey.workspace_id == workspace_id - ).all() - ] - if _api_key_ids: - total_api_calls = db.query(_api_func.count(_ApiKeyLog.id)).filter( - _ApiKeyLog.api_key_id.in_(_api_key_ids), - _ApiKeyLog.created_at >= _today_start, - _ApiKeyLog.created_at < _now - ).scalar() or 0 - else: - total_api_calls = 0 - neo4j_data["total_api_call"] = total_api_calls - api_logger.info(f"成功获取API调用统计(当天): {neo4j_data['total_api_call']}") - except Exception as e: - api_logger.error(f"获取API调用统计失败: {str(e)}") - neo4j_data["total_api_call"] = 0 + # 2. 获取共享统计数据（total_app、total_knowledge、total_api_call） + common_stats = memory_dashboard_service.get_dashboard_common_stats(db, workspace_id) + neo4j_data.update(common_stats) + api_logger.info(f"成功获取共享统计: app={common_stats['total_app']}, knowledge={common_stats['total_knowledge']}, api_call={common_stats['total_api_call']}") # 计算昨日对比 try: @@ -685,61 +639,18 @@ async def dashboard_data( "total_api_call": None } - # 获取RAG相关数据 + # 1. 获取记忆总量（total_memory）—— rag 独有逻辑：查询 document 表的 chunk_num try: - # total_memory: 只统计用户知识库（permission_id='Memory'）的chunk数 total_chunk = memory_dashboard_service.get_rag_user_kb_total_chunk(db, current_user) rag_data["total_memory"] = total_chunk - - # total_app: 统计当前空间下的所有app数量 - # 包含自有app + 被分享给本工作空间的app - from app.services import app_service as _app_svc - _, total_app = _app_svc.AppService(db).list_apps( - workspace_id=workspace_id, include_shared=True, pagesize=1 - ) - rag_data["total_app"] = total_app - - # total_knowledge: 直接查knowledges表status=1的总数，排除用户知识库(permission_id='Memory') - from sqlalchemy import func as _func - from app.models.knowledge_model import Knowledge as _Knowledge - total_kb = db.query(_func.count(_Knowledge.id)).filter( - _Knowledge.workspace_id == workspace_id, - _Knowledge.status == 1, - _Knowledge.permission_id != "Memory" - ).scalar() or 0 - rag_data["total_knowledge"] = total_kb - - # total_api_call: 仅统计当天api_key_log调用次数 - try: - from datetime import datetime - from sqlalchemy import func as _api_func - from app.models.api_key_model import ApiKey as _ApiKey, ApiKeyLog as _ApiKeyLog - - _now = datetime.now() - _today_start = _now.replace(hour=0, minute=0, second=0, microsecond=0) - - _api_key_ids = [ - row[0] for row in db.query(_ApiKey.id).filter( - _ApiKey.workspace_id == workspace_id - ).all() - ] - if _api_key_ids: - total_api_calls = db.query(_api_func.count(_ApiKeyLog.id)).filter( - _ApiKeyLog.api_key_id.in_(_api_key_ids), - _ApiKeyLog.created_at >= _today_start, - _ApiKeyLog.created_at < _now - ).scalar() or 0 - else: - total_api_calls = 0 - rag_data["total_api_call"] = total_api_calls - api_logger.info(f"成功获取RAG模式API调用统计(当天): {rag_data['total_api_call']}") - except Exception as e: - api_logger.warning(f"获取RAG模式API调用统计失败，使用默认值: {str(e)}") - rag_data["total_api_call"] = 0 - - api_logger.info(f"成功获取RAG相关数据: memory={total_chunk}, app={total_app}, knowledge={total_kb}, api_calls={rag_data['total_api_call']}") + api_logger.info(f"成功获取RAG记忆总量: {total_chunk}") except Exception as e: - api_logger.warning(f"获取RAG相关数据失败: {str(e)}") + api_logger.warning(f"获取RAG记忆总量失败: {str(e)}") + + # 2. 获取共享统计数据（total_app、total_knowledge、total_api_call） + common_stats = memory_dashboard_service.get_dashboard_common_stats(db, workspace_id) + rag_data.update(common_stats) + api_logger.info(f"成功获取共享统计: app={common_stats['total_app']}, knowledge={common_stats['total_knowledge']}, api_call={common_stats['total_api_call']}") # 计算昨日对比 try: diff --git a/api/app/services/memory_dashboard_service.py b/api/app/services/memory_dashboard_service.py index 7e8aa807..b14a06af 100644 --- a/api/app/services/memory_dashboard_service.py +++ b/api/app/services/memory_dashboard_service.py @@ -1081,4 +1081,66 @@ async def generate_rag_profile( "tags_count": len(tags), "personas_count": len(personas), "insight_generated": bool(insight_sections.get("memory_insight")), - } \ No newline at end of file + } + + +def get_dashboard_common_stats(db: Session, workspace_id) -> dict: + """ + 获取 dashboard 中 neo4j/rag 分支共享的统计数据： + total_app、total_knowledge、total_api_call + + Returns: + dict: {"total_app": int, "total_knowledge": int, "total_api_call": int} + """ + result = {"total_app": 0, "total_knowledge": 0, "total_api_call": 0} + + # total_app: 统计当前空间下的所有app数量（包含自有 + 被分享给本工作空间的app） + try: + from app.services import app_service as _app_svc + _, total_app = _app_svc.AppService(db).list_apps( + workspace_id=workspace_id, include_shared=True, pagesize=1 + ) + result["total_app"] = total_app + except Exception as e: + business_logger.warning(f"获取应用数量失败: {e}") + + # total_knowledge: 统计顶层知识库（parent_id = workspace_id） + try: + from sqlalchemy import func as _func + from app.models.knowledge_model import Knowledge as _Knowledge + total_knowledge = db.query(_func.count(_Knowledge.id)).filter( + _Knowledge.workspace_id == workspace_id, + _Knowledge.status == 1, + _Knowledge.parent_id == _Knowledge.workspace_id + ).scalar() or 0 + result["total_knowledge"] = total_knowledge + except Exception as e: + business_logger.warning(f"获取知识库数量失败: {e}") + + # total_api_call: 仅统计当天 api_key_log 调用次数 + try: + from datetime import datetime + from sqlalchemy import func as _api_func + from app.models.api_key_model import ApiKey as _ApiKey, ApiKeyLog as _ApiKeyLog + + _now = datetime.now() + _today_start = _now.replace(hour=0, minute=0, second=0, microsecond=0) + + _api_key_ids = [ + row[0] for row in db.query(_ApiKey.id).filter( + _ApiKey.workspace_id == workspace_id + ).all() + ] + if _api_key_ids: + total_api_calls = db.query(_api_func.count(_ApiKeyLog.id)).filter( + _ApiKeyLog.api_key_id.in_(_api_key_ids), + _ApiKeyLog.created_at >= _today_start, + _ApiKeyLog.created_at < _now + ).scalar() or 0 + else: + total_api_calls = 0 + result["total_api_call"] = total_api_calls + except Exception as e: + business_logger.warning(f"获取API调用统计失败: {e}") + + return result