feat(ai): Phase 2B 洞察→推送→反馈闭环 — 风险评分+通知+建议反馈
- 风险评分引擎 load_patient_data 实装（体征+化验异常）
- refresh_all_patients 高风险自动创建洞察+事件推送
- erp-message 订阅 copilot.insight.created 推送医护通知
- 每日 cron 增加洞察过期清理+建议过期清理
- POST /ai/suggestions/{id}/feedback 建议反馈端点
- SuggestionFeedbackService 反馈服务层
- 小程序健康页建议卡片增加采纳/忽略/咨询医生按钮
This commit is contained in:
iven
@@ -15,4 +15,5 @@ pub mod quota;
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pub mod reanalysis;
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pub mod risk_service;
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pub mod suggestion;
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pub mod suggestion_feedback;
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pub mod usage;
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@@ -167,22 +167,93 @@ impl RiskService {
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}
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/// 组装患者数据用于规则评估
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/// Phase 0: 基础实现，从 vital_signs_daily 和 lab_report_item 加载最新值
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/// Phase 1: 补充聚合字段（连续N次偏高等）
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/// 从 vital_signs_daily 和 lab_report 加载最新值
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async fn load_patient_data(
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db: &sea_orm::DatabaseConnection,
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_tenant_id: Uuid,
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_patient_id: Uuid,
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tenant_id: Uuid,
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patient_id: Uuid,
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) -> AppResult<serde_json::Value> {
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// Phase 0: 返回空数据结构，确保规则引擎不会因缺失数据崩溃
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// 真实数据加载将在 Phase 1 的 "每日批量刷新" 中实现
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let _ = db;
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Ok(serde_json::json!({}))
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use sea_orm::FromQueryResult;
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// 最新一条体征数据（最近 30 天）
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#[derive(FromQueryResult)]
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struct VitalRow {
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systolic_bp_morning: Option<i32>,
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diastolic_bp_morning: Option<i32>,
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heart_rate: Option<i32>,
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blood_sugar: Option<f64>,
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weight: Option<f64>,
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spo2: Option<i32>,
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body_temperature: Option<f64>,
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}
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let vital: Option<VitalRow> = VitalRow::find_by_statement(
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sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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"SELECT systolic_bp_morning, diastolic_bp_morning, heart_rate, blood_sugar, weight, spo2, body_temperature FROM vital_signs_daily WHERE tenant_id = $1 AND patient_id = $2 AND deleted_at IS NULL ORDER BY record_date DESC LIMIT 1",
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[tenant_id.into(), patient_id.into()],
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),
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)
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.one(db)
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.await?;
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// 最新化验报告异常计数（最近 90 天）
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#[derive(FromQueryResult)]
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struct LabAbnormal {
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report_type: String,
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abnormal_count: i64,
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}
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let lab_abnormals: Vec<LabAbnormal> = LabAbnormal::find_by_statement(
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sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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"SELECT report_type, COUNT(*) as abnormal_count FROM lab_reports WHERE tenant_id = $1 AND patient_id = $2 AND deleted_at IS NULL AND is_abnormal = true AND report_date >= NOW() - INTERVAL '90 days' GROUP BY report_type",
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[tenant_id.into(), patient_id.into()],
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),
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)
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.all(db)
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.await?;
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let mut data = serde_json::Map::new();
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if let Some(v) = vital {
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if let Some(bp_sys) = v.systolic_bp_morning {
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data.insert("systolic_bp_morning".into(), serde_json::json!(bp_sys));
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}
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if let Some(bp_dia) = v.diastolic_bp_morning {
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data.insert("diastolic_bp_morning".into(), serde_json::json!(bp_dia));
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}
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if let Some(hr) = v.heart_rate {
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data.insert("heart_rate".into(), serde_json::json!(hr));
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}
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if let Some(bs) = v.blood_sugar {
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data.insert("blood_sugar".into(), serde_json::json!(bs));
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}
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if let Some(w) = v.weight {
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data.insert("weight".into(), serde_json::json!(w));
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}
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if let Some(spo2) = v.spo2 {
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data.insert("spo2".into(), serde_json::json!(spo2));
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}
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if let Some(temp) = v.body_temperature {
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data.insert("body_temperature".into(), serde_json::json!(temp));
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}
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}
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for lab in lab_abnormals {
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data.insert(
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format!("lab_abnormal_{}", lab.report_type),
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serde_json::json!(lab.abnormal_count),
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);
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}
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Ok(serde_json::Value::Object(data))
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}
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/// 每日批量刷新所有在管患者的风险快照
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/// 通过 raw SQL 查询患者列表（因为 erp-ai 不依赖 erp-health entity）
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pub async fn refresh_all_patients(db: &sea_orm::DatabaseConnection) -> AppResult<u64> {
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pub async fn refresh_all_patients(
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db: &sea_orm::DatabaseConnection,
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event_bus: Option<&erp_core::events::EventBus>,
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) -> AppResult<u64> {
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#[derive(sea_orm::FromQueryResult)]
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struct PatientRow {
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id: Uuid,
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@@ -200,15 +271,103 @@ impl RiskService {
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let total = patients.len() as u64;
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for p in &patients {
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if let Err(e) = Self::compute_risk(db, p.tenant_id, p.id).await {
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tracing::warn!(
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patient_id = %p.id,
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tenant_id = %p.tenant_id,
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error = %e,
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"风险评分刷新失败"
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);
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match Self::compute_risk(db, p.tenant_id, p.id).await {
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Ok(risk) => {
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if risk.level == "high" || risk.level == "critical" {
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Self::create_risk_insight(db, event_bus, p.tenant_id, p.id, &risk).await;
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}
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}
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Err(e) => {
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tracing::warn!(
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patient_id = %p.id,
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tenant_id = %p.tenant_id,
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error = %e,
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"风险评分刷新失败"
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);
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}
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}
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}
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Ok(total)
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}
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/// 为高风险患者创建风险洞察
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async fn create_risk_insight(
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db: &sea_orm::DatabaseConnection,
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event_bus: Option<&erp_core::events::EventBus>,
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tenant_id: Uuid,
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patient_id: Uuid,
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risk: &RiskScore,
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) {
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let matched_with_severity: Vec<_> = risk
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.matched_rules
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.iter()
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.map(|r| {
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(
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r.rule_id,
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r.name.clone(),
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r.score,
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r.severity.clone(),
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r.suggestion.clone(),
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)
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})
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.collect();
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let insights = crate::copilot::engine::generate_anomaly_insights(
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&patient_id.to_string(),
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&matched_with_severity,
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);
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for insight_data in insights {
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let severity = insight_data["severity"]
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.as_str()
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.unwrap_or("warning")
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.to_string();
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let title = insight_data["title"]
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.as_str()
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.unwrap_or("风险告警")
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.to_string();
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let content = insight_data
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.get("content")
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.cloned()
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.unwrap_or(insight_data.clone());
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match crate::service::insight_service::InsightService::create_insight(
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db,
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tenant_id,
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patient_id,
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"daily_scan".into(),
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"risk_refresh".into(),
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Some(severity.clone()),
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title.clone(),
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content,
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None,
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168,
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None,
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)
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.await
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{
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Ok(_insight_id) => {
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if let Some(bus) = event_bus {
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let event = erp_core::events::DomainEvent::new(
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"copilot.insight.created",
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tenant_id,
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erp_core::events::build_event_payload(serde_json::json!({
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"patient_id": patient_id.to_string(),
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"insight_type": "daily_scan",
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"severity": severity,
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"title": title,
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})),
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);
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bus.publish(event, db).await;
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}
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}
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Err(e) => {
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tracing::warn!(
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patient_id = %patient_id,
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error = %e,
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"每日扫描洞察创建失败"
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);
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}
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}
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}
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}
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}
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@@ -169,6 +169,28 @@ impl SuggestionService {
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Ok(res.rows_affected())
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}
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/// 批量清理所有租户的过期建议
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pub async fn expire_stale_all_tenants(
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db: &sea_orm::DatabaseConnection,
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max_age_days: i64,
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) -> AppResult<u64> {
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let cutoff = chrono::Utc::now() - chrono::Duration::days(max_age_days);
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let sql = r#"
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UPDATE ai_suggestion
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SET status = 'expired', updated_at = NOW(), version_lock = version_lock + 1
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WHERE deleted_at IS NULL
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AND status IN ('pending', 'approved')
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AND created_at < $1
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"#;
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let result = sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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sql,
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[cutoff.into()],
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);
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let res = sea_orm::ConnectionTrait::execute(db, result).await?;
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Ok(res.rows_affected())
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}
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/// 标记为解析失败（仅记录日志，不创建建议记录）
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pub async fn mark_parse_failed(
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_db: &sea_orm::DatabaseConnection,
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44
crates/erp-ai/src/service/suggestion_feedback.rs
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44
crates/erp-ai/src/service/suggestion_feedback.rs
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@@ -0,0 +1,44 @@
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use crate::entity::ai_suggestion_feedback;
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use erp_core::error::AppResult;
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use sea_orm::{ActiveModelTrait, ColumnTrait, EntityTrait, QueryFilter, Set};
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use uuid::Uuid;
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pub struct SuggestionFeedbackService;
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impl SuggestionFeedbackService {
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pub async fn submit_feedback(
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db: &sea_orm::DatabaseConnection,
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tenant_id: Uuid,
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suggestion_id: Uuid,
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user_id: Uuid,
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action: String,
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feedback_text: Option<String>,
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) -> AppResult<Uuid> {
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let id = Uuid::now_v7();
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let now = chrono::Utc::now();
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let model = ai_suggestion_feedback::ActiveModel {
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id: Set(id),
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tenant_id: Set(tenant_id),
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suggestion_id: Set(suggestion_id),
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user_id: Set(user_id),
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action: Set(action),
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feedback_text: Set(feedback_text),
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created_at: Set(now),
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};
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model.insert(db).await?;
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Ok(id)
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}
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pub async fn list_feedback(
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db: &sea_orm::DatabaseConnection,
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tenant_id: Uuid,
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suggestion_id: Uuid,
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) -> AppResult<Vec<ai_suggestion_feedback::Model>> {
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let items = ai_suggestion_feedback::Entity::find()
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.filter(ai_suggestion_feedback::Column::TenantId.eq(tenant_id))
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.filter(ai_suggestion_feedback::Column::SuggestionId.eq(suggestion_id))
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.all(db)
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.await?;
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Ok(items)
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}
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}
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