chore: 干净 ERP 基座 — 删除 health/ai/wechat 业务代码

删除内容:
- 前端: health/(67文件), ai/(2文件), Copilot, MediaPicker, 相关API/Store/Hook
- 后端: wechat_handler, wechat_service, wechat_user entity, analytics handler, ai_workflow_seed
- 配置: WechatConfig, AppConfig.wechat, AuthState wechat 字段
- 启动: 微信凭据检查块, ensure_ai_workflows() 调用
- 迁移: 新增 m20260613_000170_drop_wechat_users.rs
- 脚本: api_test_health_alert.py, api_test_mp.py, mpsync.sh/ps1
- E2E: health-data page, flows/ 目录

保留: erp-core/auth/workflow/message/config/plugin + 基座前端 + 通用组件

docker/prometheus/alerts.yml

@@ -0,0 +1,103 @@
+groups:
+  # ── 系统级告警 ──
+  - name: system
+    rules:
+      - alert: HMSHighMemoryUsage
+        expr: process_resident_memory_bytes > 800000000
+        for: 5m
+        labels:
+          severity: warning
+        annotations:
+          summary: "HMS 内存使用超过 800MB"
+          description: "当前值: {{ $value | humanize }}B"
+
+      - alert: HMSHighMemoryCritical
+        expr: process_resident_memory_bytes > 1000000000
+        for: 2m
+        labels:
+          severity: critical
+        annotations:
+          summary: "HMS 内存使用超过 1GB（危险）"
+          description: "当前值: {{ $value | humanize }}B"
+
+      - alert: HMSHighCPU
+        expr: rate(process_cpu_seconds_total[5m]) > 0.8
+        for: 10m
+        labels:
+          severity: warning
+        annotations:
+          summary: "HMS CPU 使用率超过 80%"
+
+  # ── 应用级告警 ──
+  - name: application
+    rules:
+      - alert: HMSHighErrorRate
+        expr: rate(http_requests_total{status=~"5.."}[5m]) / rate(http_requests_total[5m]) > 0.05
+        for: 5m
+        labels:
+          severity: critical
+        annotations:
+          summary: "API 5xx 错误率超过 5%"
+          description: "当前错误率: {{ $value | humanizePercentage }}"
+
+      - alert: HMSSlowResponses
+        expr: histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m])) > 2
+        for: 10m
+        labels:
+          severity: warning
+        annotations:
+          summary: "95% 请求响应时间超过 2 秒"
+
+      - alert: HMSInstanceDown
+        expr: up{job="hms"} == 0
+        for: 2m
+        labels:
+          severity: critical
+        annotations:
+          summary: "HMS 服务不可达"
+
+  # ── 数据库告警 ──
+  - name: database
+    rules:
+      - alert: HMSPostgresConnectionsHigh
+        expr: pg_stat_activity_count > 80
+        for: 5m
+        labels:
+          severity: warning
+        annotations:
+          summary: "PostgreSQL 活跃连接数超过 80"
+
+      - alert: HMSPostgresReplicationLag
+        expr: pg_replication_lag > 30
+        for: 5m
+        labels:
+          severity: critical
+        annotations:
+          summary: "PostgreSQL 复制延迟超过 30 秒"
+
+      - alert: HMSBackupMissing
+        expr: time() - hms_last_backup_timestamp > 86400 * 2
+        for: 1h
+        labels:
+          severity: critical
+        annotations:
+          summary: "数据库备份超过 48 小时未执行"
+
+  # ── Redis 告警 ──
+  - name: redis
+    rules:
+      - alert: HMSRedisMemoryHigh
+        expr: redis_memory_used_bytes / redis_memory_max_bytes > 0.9
+        for: 5m
+        labels:
+          severity: warning
+        annotations:
+          summary: "Redis 内存使用超过 90%"
+
+      - alert: HMSRedisDown
+        expr: redis_up == 0
+        for: 2m
+        labels:
+          severity: critical
+        annotations:
+          summary: "Redis 服务不可达"

docker/prometheus/prometheus.yml

@@ -0,0 +1,32 @@
+global:
+  scrape_interval: 15s
+  evaluation_interval: 15s
+
+rule_files:
+  - "alerts.yml"
+
+scrape_configs:
+  - job_name: "hms"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["app:9090"]
+        labels:
+          service: "hms-server"
+
+  - job_name: "postgres"
+    static_configs:
+      - targets: ["postgres-exporter:9187"]
+        labels:
+          service: "postgresql"
+
+  - job_name: "redis"
+    static_configs:
+      - targets: ["redis-exporter:9121"]
+        labels:
+          service: "redis"
+
+  - job_name: "nginx"
+    static_configs:
+      - targets: ["nginx-exporter:9113"]
+        labels:
+          service: "nginx"