v1.4.2 — 自动归类取代手动选择板块

- 后端关键词自动归类立志/责善/勤学到六板块
- 移除DOM板块选择器，简化UI
- 蓝图面板展示各板块立志·责善·勤学统计+详情列表
- 旧数据自动兼容、新数据无需手动选分类

app.py

@@ -77,7 +77,30 @@ def compute_stats():
     total_evening = 0
     total_study = 0
     calendar = {}
-    all_morning_items = []  # 收集所有立志项用于蓝图统计
+    all_morning_items = []
+    all_evening_items = []
+    all_study_items = []
+
+    # 关键词 → 板块 自动归类规则
+    PILLAR_KEYWORDS = {
+        '医药营销': ['科普','科研','学术会议','学术','会议','患者管理','临床推广','临床','药企','处方','KOL','代表','拜访','荣昌','恒瑞','信达','鲁银','OPC','项目','标杆','客户'],
+        '医疗服务': ['诊疗','治疗','医生','医院','科室','手术','门诊','患者','病','护理','诊断','影像','检验'],
+        '医疗支付': ['医保','商保','理赔','支付','保险','费用','报销','商业保险','保单'],
+        'AI 智能': ['AI','数字人','智能','算法','自动化','平台','系统','网站','开发','代码','程序','模型'],
+        '公司治理': ['团队','组织','管理','招聘','HR','制度','流程','财务','考核','KPI','规划','人才','架构','预算'],
+        '个人修养': ['早起','睡觉','俯卧撑','运动','冥想','阅读','复盘','写作','习惯','修身','立志','责善','改过','勤学'],
+    }
+
+    def classify_auto(text):
+        """根据文本内容自动归类"""
+        if not text or not text.strip():
+            return ''
+        text_lower = text.strip()
+        for pillar, keywords in PILLAR_KEYWORDS.items():
+            for kw in keywords:
+                if kw in text_lower:
+                    return pillar
+        return ''  # 未匹配
 
     for row in rows:
         d = row['date']
@@ -86,12 +109,36 @@ def compute_stats():
         evening = data.get('evening', [])
         study = data.get('study', [])
 
-        # 收集 morning items
+        # 收集并自动归类
         for mi in morning:
-            if isinstance(mi, dict) and (mi.get('text', '') or '').strip():
-                all_morning_items.append(mi)
-            elif isinstance(mi, str) and mi.strip():
-                all_morning_items.append({'text': mi, 'pillar': ''})
+            text = mi if isinstance(mi, str) else mi.get('text', '')
+            if isinstance(text, str) and text.strip():
+                auto_pillar = mi.get('pillar', '') if isinstance(mi, dict) else ''
+                if not auto_pillar:
+                    auto_pillar = classify_auto(text)
+                all_morning_items.append({'text': text.strip(), 'pillar': auto_pillar})
+
+        for ei in evening:
+            if isinstance(ei, dict):
+                m = (ei.get('mistake') or '').strip()
+                imp = (ei.get('improvement') or '').strip()
+                if m or imp:
+                    pillar = ei.get('pillar', '') or classify_auto(m + ' ' + imp)
+                    all_evening_items.append({'mistake': m, 'improvement': imp, 'pillar': pillar})
+            elif isinstance(ei, str) and ei.strip():
+                all_evening_items.append({'mistake': ei.strip(), 'improvement': '', 'pillar': classify_auto(ei)})
+
+        for si in study:
+            name = si.get('name', '') if isinstance(si, dict) else str(si)
+            if name.strip():
+                pillar = si.get('pillar', '') if isinstance(si, dict) else ''
+                if not pillar:
+                    pillar = classify_auto(name)
+                all_study_items.append({
+                    'name': name.strip(),
+                    'done': si.get('done', False) if isinstance(si, dict) else False,
+                    'pillar': pillar
+                })
 
         morning_count = sum(1 for x in morning if (
             isinstance(x, str) and x.strip() or
@@ -114,11 +161,38 @@ def compute_stats():
             # day_score = 60 + extra * 5  (不在此处使用，仅用于日历状态)
         calendar[d] = 'pass' if all_three else 'fail'
 
+    # 构建板块统计
+    pillars = ['医疗服务','医药营销','医疗支付','AI 智能','公司治理','个人修养']
+    pillar_breakdown = {}
+    for p in pillars:
+        pillar_breakdown[p] = {
+            'morning': 0, 'evening': 0, 'study': 0,
+            'morning_items': [], 'evening_items': [], 'study_items': []
+        }
+    for mi in all_morning_items:
+        p = mi['pillar']
+        if p in pillar_breakdown:
+            pillar_breakdown[p]['morning'] += 1
+            pillar_breakdown[p]['morning_items'].append(mi)
+    for ei in all_evening_items:
+        p = ei['pillar']
+        if p in pillar_breakdown:
+            pillar_breakdown[p]['evening'] += 1
+            pillar_breakdown[p]['evening_items'].append(ei)
+    for si in all_study_items:
+        p = si['pillar']
+        if p in pillar_breakdown:
+            pillar_breakdown[p]['study'] += 1
+            pillar_breakdown[p]['study_items'].append(si)
+
     return dict(
         total_days=total_days, total_morning=total_morning,
         total_evening=total_evening, total_study=total_study,
         calendar=calendar,
-        morning_items=all_morning_items
+        morning_items=all_morning_items,
+        evening_items=all_evening_items,
+        study_items=all_study_items,
+        pillar_breakdown=pillar_breakdown
     )