diff --git a/docs/changelog/update.md b/docs/changelog/update.md index 6422dc58..0705293a 100644 --- a/docs/changelog/update.md +++ b/docs/changelog/update.md @@ -19,7 +19,7 @@ - [ ] 知识图谱的上传和可视化，支持属性，标签的展示 - [ ] 集成智能体评估，首先使用命令行来实现，然后考虑放在 UI 里面展示 - [ ] 开发与生产环境隔离 -- [ ] 添加统计信息 +- [x] 添加统计信息 - [ ] 支持 MinerU 的解析方法 - [ ] Options 中添加网络搜索和绘制图片的选项，分别是用来调用工具 diff --git a/server/routers/auth_router.py b/server/routers/auth_router.py index 0944eee8..d6288982 100644 --- a/server/routers/auth_router.py +++ b/server/routers/auth_router.py @@ -272,9 +272,7 @@ async def update_profile( # 检查用户名是否已被其他用户使用 existing_user = ( - db.query(User) - .filter(User.username == profile_data.username, User.id != current_user.id) - .first() + db.query(User).filter(User.username == profile_data.username, User.id != current_user.id).first() ) if existing_user: raise HTTPException( diff --git a/server/routers/chat_router.py b/server/routers/chat_router.py index 3d158e0f..62aeb5c4 100644 --- a/server/routers/chat_router.py +++ b/server/routers/chat_router.py @@ -183,11 +183,11 @@ async def chat_agent( # 格式清洗 if finish_reason := msg_dict.get("response_metadata", {}).get("finish_reason"): - if "tool_call" in finish_reason and len(finish_reason) > len("tool_call") : + if "tool_call" in finish_reason and len(finish_reason) > len("tool_call"): model_name = msg_dict.get("response_metadata", {}).get("model_name", "") repeat_count = len(finish_reason) // len("tool_call") msg_dict["response_metadata"]["finish_reason"] = "tool_call" - msg_dict["response_metadata"]["model_name"] = model_name[:len(model_name)//repeat_count] + msg_dict["response_metadata"]["model_name"] = model_name[: len(model_name) // repeat_count] # 保存 AI 消息 ai_msg = conv_mgr.add_message( diff --git a/server/routers/dashboard_router.py b/server/routers/dashboard_router.py index 14ac46a6..393589cf 100644 --- a/server/routers/dashboard_router.py +++ b/server/routers/dashboard_router.py @@ -421,9 +421,7 @@ async def get_knowledge_stats( for _fid, finfo in files_meta.items(): file_ext = (finfo.get("file_type") or "").lower() # 统一映射显示名 - display_name = file_type_mapping.get( - file_ext, file_ext.upper() + "文件" if file_ext else "其他" - ) + display_name = file_type_mapping.get(file_ext, file_ext.upper() + "文件" if file_ext else "其他") files_by_type[display_name] = files_by_type.get(display_name, 0) + 1 # 估算大小（如果路径存在且是本地文件） @@ -721,33 +719,29 @@ async def get_call_timeseries_stats( ): """Get time series statistics for call analytics (Admin only)""" try: - from src.storage.db.models import Conversation, Message, ToolCall, ConversationStats + from src.storage.db.models import Conversation, Message, ToolCall # 计算时间范围（使用北京时间 UTC+8） now = datetime.utcnow() - beijing_time = now + timedelta(hours=8) # 转换为北京时间 if time_range == "7hours": intervals = 7 # 包含当前小时：从6小时前开始 - start_time = now - timedelta(hours=intervals-1) - time_format = "%Y-%m-%d %H:00" + start_time = now - timedelta(hours=intervals - 1) # SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间 - group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Message.created_at, '+8 hours')) + group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Message.created_at, "+8 hours")) elif time_range == "7weeks": intervals = 7 # 包含当前周：从6周前开始 - start_time = now - timedelta(weeks=intervals-1) - time_format = "%Y-W%U" + start_time = now - timedelta(weeks=intervals - 1) # SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间 - group_format = func.strftime("%Y-%W", func.datetime(Message.created_at, '+8 hours')) + group_format = func.strftime("%Y-%W", func.datetime(Message.created_at, "+8 hours")) else: # 7days (default) intervals = 7 # 包含当前天：从6天前开始 - start_time = now - timedelta(days=intervals-1) - time_format = "%Y-%m-%d" + start_time = now - timedelta(days=intervals - 1) # SQLite compatible approach: 使用datetime函数转换UTC时间为北京时间 - group_format = func.strftime("%Y-%m-%d", func.datetime(Message.created_at, '+8 hours')) + group_format = func.strftime("%Y-%m-%d", func.datetime(Message.created_at, "+8 hours")) # 根据类型查询数据 if type == "models": @@ -757,7 +751,7 @@ async def get_call_timeseries_stats( db.query( group_format.label("date"), func.count(Message.id).label("count"), - func.json_extract(Message.extra_metadata, "$.response_metadata.model_name").label("category") + func.json_extract(Message.extra_metadata, "$.response_metadata.model_name").label("category"), ) .filter(Message.role == "assistant", Message.created_at >= start_time) .filter(Message.extra_metadata.isnot(None)) @@ -768,17 +762,17 @@ async def get_call_timeseries_stats( # 智能体调用统计（基于对话数量，按智能体分组） # 为对话创建独立的时间格式化器 if time_range == "7hours": - conv_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Conversation.created_at, '+8 hours')) + conv_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(Conversation.created_at, "+8 hours")) elif time_range == "7weeks": - conv_group_format = func.strftime("%Y-%W", func.datetime(Conversation.created_at, '+8 hours')) + conv_group_format = func.strftime("%Y-%W", func.datetime(Conversation.created_at, "+8 hours")) else: # 7days - conv_group_format = func.strftime("%Y-%m-%d", func.datetime(Conversation.created_at, '+8 hours')) + conv_group_format = func.strftime("%Y-%m-%d", func.datetime(Conversation.created_at, "+8 hours")) query = ( db.query( conv_group_format.label("date"), func.count(Conversation.id).label("count"), - Conversation.agent_id.label("category") + Conversation.agent_id.label("category"), ) .filter(Conversation.created_at >= start_time) .group_by(conv_group_format, Conversation.agent_id) @@ -787,22 +781,20 @@ async def get_call_timeseries_stats( elif type == "tokens": # Token消耗统计（区分input/output tokens） # 先查询input tokens - from sqlalchemy import text, literal + from sqlalchemy import literal input_query = ( db.query( group_format.label("date"), func.sum( - func.coalesce( - func.json_extract(Message.extra_metadata, "$.usage_metadata.input_tokens"), 0 - ) + func.coalesce(func.json_extract(Message.extra_metadata, "$.usage_metadata.input_tokens"), 0) ).label("count"), - literal("input_tokens").label("category") + literal("input_tokens").label("category"), ) .filter( Message.created_at >= start_time, Message.extra_metadata.isnot(None), - func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None) + func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None), ) .group_by(group_format) .order_by(group_format) @@ -813,16 +805,14 @@ async def get_call_timeseries_stats( db.query( group_format.label("date"), func.sum( - func.coalesce( - func.json_extract(Message.extra_metadata, "$.usage_metadata.output_tokens"), 0 - ) + func.coalesce(func.json_extract(Message.extra_metadata, "$.usage_metadata.output_tokens"), 0) ).label("count"), - literal("output_tokens").label("category") + literal("output_tokens").label("category"), ) .filter( Message.created_at >= start_time, Message.extra_metadata.isnot(None), - func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None) + func.json_extract(Message.extra_metadata, "$.usage_metadata").isnot(None), ) .group_by(group_format) .order_by(group_format) @@ -836,17 +826,17 @@ async def get_call_timeseries_stats( # 工具调用统计（按工具名称分组） # 为工具调用创建独立的时间格式化器 if time_range == "7hours": - tool_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(ToolCall.created_at, '+8 hours')) + tool_group_format = func.strftime("%Y-%m-%d %H:00", func.datetime(ToolCall.created_at, "+8 hours")) elif time_range == "7weeks": - tool_group_format = func.strftime("%Y-%W", func.datetime(ToolCall.created_at, '+8 hours')) + tool_group_format = func.strftime("%Y-%W", func.datetime(ToolCall.created_at, "+8 hours")) else: # 7days - tool_group_format = func.strftime("%Y-%m-%d", func.datetime(ToolCall.created_at, '+8 hours')) + tool_group_format = func.strftime("%Y-%m-%d", func.datetime(ToolCall.created_at, "+8 hours")) query = ( db.query( tool_group_format.label("date"), func.count(ToolCall.id).label("count"), - ToolCall.tool_name.label("category") + ToolCall.tool_name.label("category"), ) .filter(ToolCall.created_at >= start_time) .group_by(tool_group_format, ToolCall.tool_name) @@ -862,7 +852,7 @@ async def get_call_timeseries_stats( # 首先收集所有类别 categories = set() for result in results: - if hasattr(result, 'category') and result.category: + if hasattr(result, "category") and result.category: categories.add(result.category) # 如果没有类别数据，提供默认类别 @@ -882,7 +872,7 @@ async def get_call_timeseries_stats( time_data = {} for result in results: date_key = result.date - category = getattr(result, 'category', 'unknown') + category = getattr(result, "category", "unknown") count = result.count if date_key not in time_data: @@ -921,17 +911,14 @@ async def get_call_timeseries_stats( if category not in day_data: day_data[category] = 0 - data.append({ - "date": date_key, - "data": day_data, - "total": day_total - }) + data.append({"date": date_key, "data": day_data, "total": day_total}) current_time += delta # 计算统计指标 if type == "tools": # 对于工具调用，显示所有时间的总数（与ToolStatsComponent保持一致） from src.storage.db.models import ToolCall + total_count = db.query(func.count(ToolCall.id)).scalar() or 0 else: # 其他类型使用时间序列数据的总和 diff --git a/src/agents/common/utils.py b/src/agents/common/utils.py index ebbcbfdb..50dfdccd 100644 --- a/src/agents/common/utils.py +++ b/src/agents/common/utils.py @@ -2,6 +2,7 @@ from datetime import UTC, datetime from langchain_core.messages import AIMessageChunk, ToolMessage from langchain_core.runnables import RunnableConfig + from src.agents.common.base import BaseAgent diff --git a/src/knowledge/implementations/chroma.py b/src/knowledge/implementations/chroma.py index 0a0e681d..c02ce91d 100644 --- a/src/knowledge/implementations/chroma.py +++ b/src/knowledge/implementations/chroma.py @@ -205,15 +205,11 @@ class ChromaKB(KnowledgeBase): total_batches = (len(chunks) + batch_size - 1) // batch_size for i in range(0, len(chunks), batch_size): - batch_documents = documents[i:i + batch_size] - batch_metadatas = metadatas[i:i + batch_size] - batch_ids = ids[i:i + batch_size] + batch_documents = documents[i : i + batch_size] + batch_metadatas = metadatas[i : i + batch_size] + batch_ids = ids[i : i + batch_size] - collection.add( - documents=batch_documents, - metadatas=batch_metadatas, - ids=batch_ids - ) + collection.add(documents=batch_documents, metadatas=batch_metadatas, ids=batch_ids) batch_num = i // batch_size + 1 logger.info(f"Processed batch {batch_num}/{total_batches} for {filename}")