fix: 修复app.py中的缩进错误和logger配置问题

src/web/app.py

@@ -10,6 +10,9 @@ import os
 import json
 import logging
 import pandas as pd
+
+# 配置日志
+logger = logging.getLogger(__name__)
 from datetime import datetime, timedelta
 from openpyxl import Workbook
 from openpyxl.styles import Font
@@ -631,9 +634,9 @@ def get_workorders():
         priority_filter = request.args.get('priority')
         with db_manager.get_session() as session:
             q = session.query(WorkOrder)
-        if status_filter and status_filter != 'all':
+            if status_filter and status_filter != 'all':
                 q = q.filter(WorkOrder.status == status_filter)
-        if priority_filter and priority_filter != 'all':
+            if priority_filter and priority_filter != 'all':
                 q = q.filter(WorkOrder.priority == priority_filter)
             q = q.order_by(WorkOrder.created_at.desc())
             rows = q.all()
@@ -877,80 +880,80 @@ def generate_db_analytics(days: int, dimension: str) -> dict:
         } for d in day_keys]
     
     # 工单统计
-        total = len(workorders)
-        status_counts = Counter([wo.status for wo in workorders])
-        category_counts = Counter([wo.category for wo in workorders])
-        priority_counts = Counter([wo.priority for wo in workorders])
-        resolved_count = status_counts.get('resolved', 0)
+    total = len(workorders)
+    status_counts = Counter([wo.status for wo in workorders])
+    category_counts = Counter([wo.category for wo in workorders])
+    priority_counts = Counter([wo.priority for wo in workorders])
+    resolved_count = status_counts.get('resolved', 0)
     workorders_stats = {
-            'total': total,
-            'open': status_counts.get('open', 0),
-            'in_progress': status_counts.get('in_progress', 0),
-            'resolved': resolved_count,
-            'closed': status_counts.get('closed', 0),
-            'by_category': dict(category_counts),
-            'by_priority': dict(priority_counts)
-        }
-
-        # 满意度
-        scores = []
-        for wo in workorders:
-            if wo.satisfaction_score not in (None, ''):
-                try:
-                    score = float(wo.satisfaction_score)
-                    scores.append(score)
-                except (ValueError, TypeError):
-                    continue
-        avg_satisfaction = round(sum(scores)/len(scores), 1) if scores else 0
-        dist = Counter([str(int(round(s))) for s in scores]) if scores else {}
-    satisfaction_stats = {
-            'average': avg_satisfaction,
-            'distribution': {k: int(v) for k, v in dist.items()}
+        'total': total,
+        'open': status_counts.get('open', 0),
+        'in_progress': status_counts.get('in_progress', 0),
+        'resolved': resolved_count,
+        'closed': status_counts.get('closed', 0),
+        'by_category': dict(category_counts),
+        'by_priority': dict(priority_counts)
     }
-    
-    # 预警统计
-        level_counts = Counter([al.level for al in alerts])
-        active_alerts = len([al for al in alerts if al.is_active])
-        resolved_alerts = len([al for al in alerts if not al.is_active and al.resolved_at])
-    alerts_stats = {
-            'total': len(alerts),
-            'active': active_alerts,
-            'resolved': resolved_alerts,
-            'by_level': {k: int(v) for k, v in level_counts.items()}
-        }
 
-        # 性能指标（基于对话响应时间粗略估计）
-        resp_times = []
-        for c in conversations:
-            if c.response_time not in (None, ''):
-                try:
-                    resp_time = float(c.response_time)
-                    resp_times.append(resp_time)
-                except (ValueError, TypeError):
-                    continue
-        avg_resp = round(sum(resp_times)/len(resp_times), 2) if resp_times else 0
-        throughput = len(conversations)  # 期间内的对话数量
-        # 错误率：用严重预警比例粗估
-        critical = level_counts.get('critical', 0)
-        error_rate = round((critical / alerts_stats['total']) * 100, 2) if alerts_stats['total'] > 0 else 0
+    # 满意度
+    scores = []
+    for wo in workorders:
+        if wo.satisfaction_score not in (None, ''):
+            try:
+                score = float(wo.satisfaction_score)
+                scores.append(score)
+            except (ValueError, TypeError):
+                continue
+    avg_satisfaction = round(sum(scores)/len(scores), 1) if scores else 0
+    dist = Counter([str(int(round(s))) for s in scores]) if scores else {}
+    satisfaction_stats = {
+        'average': avg_satisfaction,
+        'distribution': {k: int(v) for k, v in dist.items()}
+    }
+
+    # 预警统计
+    level_counts = Counter([al.level for al in alerts])
+    active_alerts = len([al for al in alerts if al.is_active])
+    resolved_alerts = len([al for al in alerts if not al.is_active and al.resolved_at])
+    alerts_stats = {
+        'total': len(alerts),
+        'active': active_alerts,
+        'resolved': resolved_alerts,
+        'by_level': {k: int(v) for k, v in level_counts.items()}
+    }
+
+    # 性能指标（基于对话响应时间粗略估计）
+    resp_times = []
+    for c in conversations:
+        if c.response_time not in (None, ''):
+            try:
+                resp_time = float(c.response_time)
+                resp_times.append(resp_time)
+            except (ValueError, TypeError):
+                continue
+    avg_resp = round(sum(resp_times)/len(resp_times), 2) if resp_times else 0
+    throughput = len(conversations)  # 期间内的对话数量
+    # 错误率：用严重预警比例粗估
+    critical = level_counts.get('critical', 0)
+    error_rate = round((critical / alerts_stats['total']) * 100, 2) if alerts_stats['total'] > 0 else 0
     performance_stats = {
-            'response_time': avg_resp,
-            'uptime': 99.0,  # 可接入真实监控后更新
-            'error_rate': error_rate,
-            'throughput': throughput
+        'response_time': avg_resp,
+        'uptime': 99.0,  # 可接入真实监控后更新
+        'error_rate': error_rate,
+        'throughput': throughput
     }
     
     return {
-            'trend': trend,
+        'trend': trend,
         'workorders': workorders_stats,
         'satisfaction': satisfaction_stats,
         'alerts': alerts_stats,
         'performance': performance_stats,
         'summary': {
-                'total_workorders': total,
-                'resolution_rate': round((resolved_count/total)*100, 1) if total > 0 else 0,
-                'avg_satisfaction': avg_satisfaction,
-                'active_alerts': active_alerts
+            'total_workorders': total,
+            'resolution_rate': round((resolved_count/total)*100, 1) if total > 0 else 0,
+            'avg_satisfaction': avg_satisfaction,
+            'active_alerts': active_alerts
         }
     }
 
@@ -1144,11 +1147,11 @@ def get_settings():
                 settings['api_key'] = '******'
                 settings['api_key_masked'] = True
         else:
-        settings = {
-            "api_timeout": 30,
-            "max_history": 10,
-            "refresh_interval": 10,
-            "auto_monitoring": True,
+            settings = {
+                "api_timeout": 30,
+                "max_history": 10,
+                "refresh_interval": 10,
+                "auto_monitoring": True,
                 "agent_mode": True,
                 # LLM与API配置（仅持久化，不直接热更新LLM客户端）
                 "api_provider": "openai",