feat: KPI通用化数据层改造

- 新增entities表（企业实体）+ 种子数据（酣客/博海）
- kpi_definitions新增entity_id字段（DEFAULT 1，向后兼容）
- 后端API list_kpis支持可选的entity_id过滤参数
- 新增 GET /api/cma/entities API返回企业列表
- 43个现有KPI自动获得entity_id=1（酣客）
- 前端重新构建并部署

backend/app/api/bot_bridge.py

@@ -3,7 +3,7 @@ CMA BOT API桥接层 — 供财务BOT/店研学BOT调用
 无需用户登录，使用 BOT API Key 认证
 """
 import os, json, logging
-from fastapi import APIRouter, Depends, HTTPException, Query, Header
+from fastapi import APIRouter, Depends, HTTPException, Query, Header, UploadFile, File
 from sqlalchemy.orm import Session
 from sqlalchemy import func, desc
 from datetime import datetime
@@ -30,10 +30,9 @@ def _load_bot_keys():
     raw = os.getenv("CMA_BOT_API_KEYS", "")
     if not raw:
         _BOT_API_KEYS = {
-            "cma-bot-finance-2026": {"role": "finance", "name": "财务分析Bot", "dimension": "finance"},
-            "cma-bot-customer-2026": {"role": "business", "name": "客户分析Bot", "dimension": "customer"},
-            "cma-bot-process-2026": {"role": "it", "name": "流程分析Bot", "dimension": "process"},
-            "cma-bot-learning-2026": {"role": "ceo", "name": "战略分析Bot", "dimension": "learning"},
+            "cma-bot-finance-2026": {"role": "finance", "name": "财务BOT"},
+            "cma-bot-shop-2026": {"role": "business", "name": "店研学BOT"},
+            "cma-bot-admin-2026": {"role": "ceo", "name": "管理BOT"},
         }
     else:
         try:
@@ -463,6 +462,68 @@ def bot_query(
     return result
 
 
+@router.post("/import")
+def bot_import_excel(
+    file: UploadFile = File(...),
+    bot: dict = Depends(verify_bot_key),
+    db: Session = Depends(get_db),
+):
+    """Bot上传Excel导入KPI数据到CMA"""
+    import pandas as pd, io, hashlib
+    from app.models import KPIValue
+    try:
+        content = file.file.read()
+        df = pd.read_excel(io.BytesIO(content))
+    except Exception as e:
+        raise HTTPException(400, f"Excel解析失败: {e}")
+    finally:
+        file.file.close()
+
+    # 智能识别列名
+    col_map = {"kpi_code": ["kpi_code", "KPI编码", "指标编码", "code"],
+               "period": ["period", "期间", "月份", "month", "日期"],
+               "actual_value": ["actual_value", "实际值", "值", "金额", "value", "amount"]}
+    
+    mapped = {}
+    for field, aliases in col_map.items():
+        for col in df.columns:
+            if str(col).strip() in aliases or str(col).strip().lower() in aliases:
+                mapped[field] = str(col).strip()
+                break
+    
+    if "actual_value" not in mapped:
+        raise HTTPException(400, f"无法识别数值列，支持的列名: {col_map['actual_value']}")
+    if "kpi_code" not in mapped:
+        raise HTTPException(400, f"无法识别KPI编码列，支持的列名: {col_map['kpi_code']}")
+    
+    kpi_col = mapped["kpi_code"]
+    val_col = mapped["actual_value"]
+    period_col = mapped.get("period")
+    
+    count = 0
+    errors = []
+    for idx, row in df.iterrows():
+        try:
+            kpi_code = str(row[kpi_col]).strip()
+            val = float(row[val_col])
+            period = str(row[period_col]).strip() if period_col else datetime.now().strftime("%Y-%m")
+            
+            kpi = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == kpi_code).first()
+            if not kpi:
+                errors.append(f"第{idx+2}行: KPI编码 '{kpi_code}' 不存在，跳过")
+                continue
+            
+            kv = KPIValue(kpi_id=kpi.id, period=period, actual_value=val,
+                          batch_id=hashlib.md5(f"{datetime.now()}".encode()).hexdigest()[:12])
+            db.add(kv)
+            count += 1
+        except Exception as e:
+            errors.append(f"第{idx+2}行: {e}")
+    
+    db.commit()
+    return {"ok": True, "imported": count, "errors": len(errors), "detail": errors[:5]}
+
+
 # ── 自然语言查询 ──
 
 @router.get("/nlp")