feat: Bot KPI管理体系 — bot_source字段 + 11个财务Bot KPI + Bot KPI看板

- 新增 bot_source 字段到 kpi_definitions 表（DB迁移 + 模型字段） - 创建 bot_kpis.py API（GET /api/cma/bot-kpis + POST .../value） - 种子脚本 seed_finance_bot_kpis.py 插入11个财务Bot KPI - BotKpiDashboard.vue 看板组件（三区：核心产出5/质量3/用户反馈3） - 路由 /bot-kpis + 侧边栏菜单入口 - 复用五档评分引擎
2026-07-25 07:44:41 +08:00
parent c7ec8b2c99
commit abedf8cb8d
8 changed files with 660 additions and 1 deletions
@@ -0,0 +1,180 @@
+"""
+种子数据：财务Bot KPI（11个）
+插入到 kpi_definitions 表，bot_source='finance-bot'
+"""
+import pymysql
+import os
+import sys
+from datetime import datetime
+
+DB_USER = os.getenv("CMA_DB_USER", "cma_user")
+DB_PASS = os.getenv("CMA_DB_PASS", "cma_pass_2026")
+DB_HOST = os.getenv("CMA_DB_HOST", "127.0.0.1")
+DB_PORT = int(os.getenv("CMA_DB_PORT", "3306"))
+DB_NAME = os.getenv("CMA_DB_NAME", "cma")
+
+FINANCE_BOT_KPIS = [
+    # ── 核心产出（5个 · 月度考核）──
+    {
+        "kpi_code": "FB_ANALYSIS_COUNT",
+        "kpi_name": "分析报告产出数",
+        "formula": "月度生成的结构化分析报告数量",
+        "unit": "份",
+        "target_value": 20,
+        "frequency": "monthly",
+        "category": "core_output",
+        "weight": 15,
+    },
+    {
+        "kpi_code": "FB_ACCURACY_RATE",
+        "kpi_name": "数据提取准确率",
+        "formula": "1−(数据错误次数/总分析次数)",
+        "unit": "%",
+        "target_value": 98,
+        "frequency": "monthly",
+        "category": "core_output",
+        "weight": 25,
+    },
+    {
+        "kpi_code": "FB_ISSUE_FOUND",
+        "kpi_name": "问题发现数",
+        "formula": "月度发现的影响经营的问题数量",
+        "unit": "个",
+        "target_value": 5,
+        "frequency": "monthly",
+        "category": "core_output",
+        "weight": 20,
+    },
+    {
+        "kpi_code": "FB_ACTION_RATE",
+        "kpi_name": "行动采纳率",
+        "formula": "被用户采纳的行动建议数/总建议数",
+        "unit": "%",
+        "target_value": 60,
+        "frequency": "monthly",
+        "category": "core_output",
+        "weight": 25,
+    },
+    {
+        "kpi_code": "FB_RESPONSE_TIME",
+        "kpi_name": "响应时效",
+        "formula": "用户发文件到出分析结果的平均时间",
+        "unit": "分钟",
+        "target_value": 10,
+        "frequency": "monthly",
+        "category": "core_output",
+        "weight": 15,
+    },
+    # ── 质量监控（3个 · 月度考核）──
+    {
+        "kpi_code": "FB_DATA_GAP",
+        "kpi_name": "数据间隙发现率",
+        "formula": "发现的数据异常/缺失数 / 应发现数",
+        "unit": "%",
+        "target_value": 90,
+        "frequency": "monthly",
+        "category": "quality",
+        "weight": 30,
+    },
+    {
+        "kpi_code": "FB_CONSISTENCY",
+        "kpi_name": "跨期一致性",
+        "formula": "同期指标口径是否一致",
+        "unit": "%",
+        "target_value": 100,
+        "frequency": "monthly",
+        "category": "quality",
+        "weight": 30,
+    },
+    {
+        "kpi_code": "FB_CITATION",
+        "kpi_name": "结论可追溯率",
+        "formula": "每个结论有对应的数据来源",
+        "unit": "%",
+        "target_value": 100,
+        "frequency": "monthly",
+        "category": "quality",
+        "weight": 40,
+    },
+    # ── 用户反馈（3个 · 季度考核）──
+    {
+        "kpi_code": "FB_SATISFACTION",
+        "kpi_name": "用户满意度",
+        "formula": "用户对分析报告的评分（1-5分）",
+        "unit": "分",
+        "target_value": 4.0,
+        "frequency": "quarterly",
+        "category": "user_feedback",
+        "weight": 40,
+    },
+    {
+        "kpi_code": "FB_REUSE_RATE",
+        "kpi_name": "复用率",
+        "formula": "用户连续使用天数/月总天数",
+        "unit": "%",
+        "target_value": 80,
+        "frequency": "quarterly",
+        "category": "user_feedback",
+        "weight": 30,
+    },
+    {
+        "kpi_code": "FB_REFERRAL",
+        "kpi_name": "推荐率",
+        "formula": "用户主动向他人推荐次数",
+        "unit": "次",
+        "target_value": 1,
+        "frequency": "quarterly",
+        "category": "user_feedback",
+        "weight": 30,
+    },
+]
+
+
+def run():
+    conn = pymysql.connect(
+        host=DB_HOST, user=DB_USER, password=DB_PASS,
+        database=DB_NAME, charset="utf8mb4",
+    )
+    cursor = conn.cursor()
+
+    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    inserted = 0
+    skipped = 0
+
+    for kpi in FINANCE_BOT_KPIS:
+        code = kpi["kpi_code"]
+        # 检查是否已存在
+        cursor.execute("SELECT id FROM kpi_definitions WHERE kpi_code = %s", (code,))
+        existing = cursor.fetchone()
+        if existing:
+            print(f"  ⏭  {code} 已存在 (id={existing[0]})")
+            skipped += 1
+            continue
+
+        sql = """
+            INSERT INTO kpi_definitions
+                (entity_id, kpi_code, kpi_name, dimension, formula, unit,
+                 target_value, frequency, category, status, bot_source, data_source,
+                 data_owner, created_at, updated_at)
+            VALUES
+                (%s, %s, %s, %s, %s, %s,
+                 %s, %s, %s, 'active', 'finance-bot', 'Bot自计数',
+                 'FinanceBot', %s, %s)
+        """
+        cursor.execute(sql, (
+            1, code, kpi["kpi_name"], "process", kpi["formula"], kpi["unit"],
+            kpi["target_value"], kpi["frequency"], kpi["category"],
+            now, now,
+        ))
+        new_id = cursor.lastrowid
+        print(f"  ✅ {code} -> id={new_id}")
+        inserted += 1
+
+    conn.commit()
+    cursor.close()
+    conn.close()
+    print(f"\n完成：新增 {inserted} 条，跳过 {skipped} 条（共 {len(FINANCE_BOT_KPIS)} 个KPI）")
+
+
+if __name__ == "__main__":
+    run()