fix: V1 测试版本端到端验证修复 — 6 CRITICAL + 3 HIGH 问题全量修复
修复项: - fix(db): 迁移 149 — 修复 Admin 角色权限绑定被迁移链破坏 (FE-C1) - fix(health): 4 个 handler 添加空名称验证 — Doctor/Article/AlertRule/Tag (API-C1~C4) - fix(health): Stats 仪表盘 new_this_week 查询修复 — SeaORM date_trunc bug (FE-C2) - fix(server): 添加安全响应头 — X-Frame-Options/CSP/XSS-Protection/Referrer-Policy (SEC-H1) - fix(mp): 预约创建契约修复 — notes/reason 字段映射 + 移除 schedule_id (MP-H1) - fix(mp): 咨询会话 subject/last_message 字段改为可选 (MP-H3) - fix(ai): AiConfig Default derive 替代手写 impl (clippy) 测试报告: - 8 维度端到端测试全部完成 (后端 87 用例 / 前端 30 页面 / 小程序 80+ API / 安全 20 项 / 性能 20 端点) - 多角色 7 角色 49 检查 100% 通过 - 综合测试报告 + 专家评估报告
This commit is contained in:
iven
415
crates/erp-ai/src/config_resolver.rs
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415
crates/erp-ai/src/config_resolver.rs
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@@ -0,0 +1,415 @@
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use sea_orm::ConnectionTrait;
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use sea_orm::DatabaseConnection;
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use serde::{Deserialize, Serialize};
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use uuid::Uuid;
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/// AI Agent 运行时配置，从 settings 表读取，带编译时默认值
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#[derive(Debug, Clone, Serialize, Deserialize, utoipa::ToSchema)]
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pub struct AiAgentConfig {
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pub model: String,
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pub temperature: f32,
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pub max_tokens: u32,
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pub max_iterations: usize,
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pub system_prompt: String,
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}
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impl Default for AiAgentConfig {
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fn default() -> Self {
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Self {
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model: "claude-sonnet-4-6".to_string(),
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temperature: 0.7,
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max_tokens: 2048,
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max_iterations: 5,
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system_prompt: default_system_prompt(),
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}
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}
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}
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/// AI 分析任务默认配置（当 prompt.model_config 未指定时的 fallback）
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#[derive(Debug, Clone, Serialize, Deserialize, utoipa::ToSchema)]
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pub struct AiAnalysisDefaults {
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pub model: String,
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pub temperature: f32,
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pub max_tokens: u32,
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}
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impl Default for AiAnalysisDefaults {
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fn default() -> Self {
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Self {
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model: "claude-sonnet-4-6".to_string(),
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temperature: 0.3,
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max_tokens: 2048,
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}
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}
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}
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/// 管理员可编辑的完整 AI 配置
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#[derive(Debug, Clone, Default, Serialize, Deserialize, utoipa::ToSchema)]
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pub struct AiConfig {
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pub agent: AiAgentConfig,
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pub analysis_defaults: AiAnalysisDefaults,
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}
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/// Setting key 常量
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const KEY_AGENT_MODEL: &str = "ai.agent.model";
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const KEY_AGENT_TEMPERATURE: &str = "ai.agent.temperature";
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const KEY_AGENT_MAX_TOKENS: &str = "ai.agent.max_tokens";
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const KEY_AGENT_MAX_ITERATIONS: &str = "ai.agent.max_iterations";
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const KEY_AGENT_SYSTEM_PROMPT: &str = "ai.agent.system_prompt";
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const KEY_ANALYSIS_MODEL: &str = "ai.analysis.default_model";
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const KEY_ANALYSIS_TEMPERATURE: &str = "ai.analysis.default_temperature";
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const KEY_ANALYSIS_MAX_TOKENS: &str = "ai.analysis.default_max_tokens";
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/// 从 settings 表批量读取 AI 配置
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pub async fn load_ai_config(tenant_id: Uuid, db: &DatabaseConnection) -> AiConfig {
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let defaults = AiConfig::default();
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let values = read_settings_batch(tenant_id, db).await;
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AiConfig {
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agent: AiAgentConfig {
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model: values
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.get(KEY_AGENT_MODEL)
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.and_then(|v| v.as_str())
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.unwrap_or(&defaults.agent.model)
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.to_string(),
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temperature: values
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.get(KEY_AGENT_TEMPERATURE)
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.and_then(|v| v.as_f64())
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.unwrap_or(defaults.agent.temperature as f64) as f32,
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max_tokens: values
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.get(KEY_AGENT_MAX_TOKENS)
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.and_then(|v| v.as_u64())
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.unwrap_or(defaults.agent.max_tokens as u64) as u32,
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max_iterations: values
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.get(KEY_AGENT_MAX_ITERATIONS)
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.and_then(|v| v.as_u64())
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.unwrap_or(defaults.agent.max_iterations as u64)
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as usize,
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system_prompt: values
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.get(KEY_AGENT_SYSTEM_PROMPT)
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.and_then(|v| v.as_str())
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.unwrap_or(&defaults.agent.system_prompt)
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.to_string(),
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},
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analysis_defaults: AiAnalysisDefaults {
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model: values
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.get(KEY_ANALYSIS_MODEL)
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.and_then(|v| v.as_str())
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.unwrap_or(&defaults.analysis_defaults.model)
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.to_string(),
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temperature: values
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.get(KEY_ANALYSIS_TEMPERATURE)
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.and_then(|v| v.as_f64())
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.unwrap_or(defaults.analysis_defaults.temperature as f64)
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as f32,
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max_tokens: values
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.get(KEY_ANALYSIS_MAX_TOKENS)
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.and_then(|v| v.as_u64())
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.unwrap_or(defaults.analysis_defaults.max_tokens as u64)
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as u32,
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},
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}
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}
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/// 获取所有 AI 配置 key 列表（用于前端展示）
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pub fn all_config_keys() -> &'static [&'static str] {
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&[
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KEY_AGENT_MODEL,
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KEY_AGENT_TEMPERATURE,
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KEY_AGENT_MAX_TOKENS,
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KEY_AGENT_MAX_ITERATIONS,
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KEY_AGENT_SYSTEM_PROMPT,
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KEY_ANALYSIS_MODEL,
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KEY_ANALYSIS_TEMPERATURE,
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KEY_ANALYSIS_MAX_TOKENS,
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]
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}
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/// 批量写入 AI 配置到 settings 表
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pub async fn save_ai_config(
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config: &AiConfig,
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tenant_id: Uuid,
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operator_id: Uuid,
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db: &DatabaseConnection,
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event_bus: &erp_core::events::EventBus,
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) -> Result<(), erp_core::error::AppError> {
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let pairs: Vec<(&str, serde_json::Value)> = vec![
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(KEY_AGENT_MODEL, serde_json::json!(config.agent.model)),
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(
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KEY_AGENT_TEMPERATURE,
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serde_json::json!(config.agent.temperature),
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),
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(
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KEY_AGENT_MAX_TOKENS,
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serde_json::json!(config.agent.max_tokens),
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),
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(
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KEY_AGENT_MAX_ITERATIONS,
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serde_json::json!(config.agent.max_iterations),
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),
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(
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KEY_AGENT_SYSTEM_PROMPT,
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serde_json::json!(config.agent.system_prompt),
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),
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(
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KEY_ANALYSIS_MODEL,
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serde_json::json!(config.analysis_defaults.model),
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),
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(
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KEY_ANALYSIS_TEMPERATURE,
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serde_json::json!(config.analysis_defaults.temperature),
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),
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(
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KEY_ANALYSIS_MAX_TOKENS,
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serde_json::json!(config.analysis_defaults.max_tokens),
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),
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];
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for (key, value) in pairs {
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upsert_setting(key, &value, tenant_id, operator_id, db, event_bus).await?;
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}
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tracing::info!(
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tenant_id = %tenant_id,
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operator_id = %operator_id,
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"AI 配置已更新"
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);
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Ok(())
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}
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/// 直接从 settings 表读取所有 ai.* 配置项（tenant → platform fallback）
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async fn read_settings_batch(
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tenant_id: Uuid,
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db: &DatabaseConnection,
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) -> std::collections::HashMap<String, serde_json::Value> {
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use sea_orm::FromQueryResult;
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#[derive(FromQueryResult)]
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struct SettingRow {
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setting_key: String,
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setting_value: serde_json::Value,
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}
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let sql = r#"
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SELECT setting_key, setting_value
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FROM settings
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WHERE setting_key LIKE 'ai.%'
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AND deleted_at IS NULL
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AND (scope = 'platform' OR (scope = 'tenant' AND tenant_id = $1))
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ORDER BY scope ASC
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"#;
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let rows: Vec<SettingRow> =
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SettingRow::find_by_statement(sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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sql,
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[tenant_id.into()],
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))
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.all(db)
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.await
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.unwrap_or_default();
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let mut result = std::collections::HashMap::new();
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// 先放 platform（低优先级），再放 tenant（高优先级覆盖）
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for row in rows {
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result.insert(row.setting_key, row.setting_value);
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}
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result
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}
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/// Upsert 单个 setting（简化版，不用 erp-config 的 SettingService 避免跨 crate）
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async fn upsert_setting(
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key: &str,
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value: &serde_json::Value,
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tenant_id: Uuid,
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operator_id: Uuid,
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db: &DatabaseConnection,
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event_bus: &erp_core::events::EventBus,
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) -> Result<(), erp_core::error::AppError> {
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use sea_orm::FromQueryResult;
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#[derive(FromQueryResult)]
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struct IdRow {
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id: Uuid,
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}
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let existing: Option<IdRow> =
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IdRow::find_by_statement(sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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r#"
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SELECT id, version FROM settings
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WHERE setting_key = $1 AND scope = 'tenant' AND tenant_id = $2
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AND scope_id IS NULL AND deleted_at IS NULL
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"#,
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[key.into(), tenant_id.into()],
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))
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.one(db)
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.await
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.map_err(|e| erp_core::error::AppError::Internal(e.to_string()))?;
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if let Some(row) = existing {
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let stmt = sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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r#"
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UPDATE settings
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SET setting_value = $1, updated_at = NOW(), updated_by = $2, version = version + 1
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WHERE id = $3
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"#,
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[value.clone().into(), operator_id.into(), row.id.into()],
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);
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db.execute(stmt)
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.await
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.map_err(|e| erp_core::error::AppError::Internal(e.to_string()))?;
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} else {
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let id = Uuid::now_v7();
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let stmt = sea_orm::Statement::from_sql_and_values(
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sea_orm::DatabaseBackend::Postgres,
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r#"
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INSERT INTO settings (id, tenant_id, scope, scope_id, setting_key, setting_value,
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created_at, updated_at, created_by, updated_by, deleted_at, version)
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VALUES ($1, $2, 'tenant', NULL, $3, $4, NOW(), NOW(), $5, $5, NULL, 1)
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"#,
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[
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id.into(),
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tenant_id.into(),
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key.into(),
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value.clone().into(),
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operator_id.into(),
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],
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);
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db.execute(stmt)
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.await
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.map_err(|e| erp_core::error::AppError::Internal(e.to_string()))?;
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}
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event_bus
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.publish(
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erp_core::events::DomainEvent::new(
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"setting.updated",
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tenant_id,
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serde_json::json!({ "key": key, "scope": "tenant" }),
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),
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db,
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)
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.await;
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Ok(())
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}
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fn default_system_prompt() -> String {
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r#"你是 HMS 健康管理平台的 AI 健康顾问"小华"。
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## 核心策略
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根据用户表达的内容和情绪，自然地采用以下策略方向：
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1. 【情绪安抚】当用户表达焦虑、恐惧、沮丧时：
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- 先共情认可感受，不急于给建议
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- 用通俗语言解释，避免医学术语
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- 分享积极案例，降低恐惧感
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2. 【医疗科普】当用户询问指标含义、疾病知识时：
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- 调用 search_medical_knowledge 获取准确信息（如可用）
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- 用比喻和类比让老年患者也能理解
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- 强调"具体请以医生诊断为准"
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3. 【服务推荐】当用户表达就医需求或身体不适时：
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- 调用 query_appointments 查看已有预约（如可用）
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- 主动提出帮用户预约
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4. 【风险预警】当用户描述的症状或数据异常时：
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- 调用 query_patient_vitals 查看体征数据
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- 明确告知风险等级和需要注意的事项
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- 高风险时建议尽快就医
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5. 【引导到院】当用户有明确就诊意向或高风险预警时：
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- 提供科室位置、出诊医生信息
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- 建议用户联系前台预约
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## 策略不是互斥的，你可以在一轮对话中自然切换。
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## 永远不要：推荐具体药物、给出明确诊断、替代医生建议。
|
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## 如果没有可用的工具数据，就基于常识回答，并建议用户咨询医生。"#
|
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.to_string()
|
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}
|
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|
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#[cfg(test)]
|
||||
mod tests {
|
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use super::*;
|
||||
|
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#[test]
|
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fn default_config_has_reasonable_values() {
|
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let config = AiAgentConfig::default();
|
||||
assert_eq!(config.model, "claude-sonnet-4-6");
|
||||
assert!((config.temperature - 0.7).abs() < f32::EPSILON);
|
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assert_eq!(config.max_tokens, 2048);
|
||||
assert_eq!(config.max_iterations, 5);
|
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assert!(config.system_prompt.contains("小华"));
|
||||
}
|
||||
|
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#[test]
|
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fn default_analysis_config_has_reasonable_values() {
|
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let config = AiAnalysisDefaults::default();
|
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assert_eq!(config.model, "claude-sonnet-4-6");
|
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assert!((config.temperature - 0.3).abs() < f32::EPSILON);
|
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assert_eq!(config.max_tokens, 2048);
|
||||
}
|
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|
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#[test]
|
||||
fn all_config_keys_count() {
|
||||
assert_eq!(all_config_keys().len(), 8);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn config_serialization_roundtrip() {
|
||||
let config = AiConfig::default();
|
||||
let json = serde_json::to_string(&config).unwrap();
|
||||
let back: AiConfig = serde_json::from_str(&json).unwrap();
|
||||
assert_eq!(back.agent.model, config.agent.model);
|
||||
assert_eq!(back.agent.max_iterations, config.agent.max_iterations);
|
||||
assert_eq!(back.analysis_defaults.model, config.analysis_defaults.model);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn load_config_from_json_values() {
|
||||
let mut values = std::collections::HashMap::new();
|
||||
values.insert("ai.agent.model".to_string(), serde_json::json!("gpt-4o"));
|
||||
values.insert("ai.agent.temperature".to_string(), serde_json::json!(0.5));
|
||||
values.insert("ai.agent.max_tokens".to_string(), serde_json::json!(4096));
|
||||
values.insert("ai.agent.max_iterations".to_string(), serde_json::json!(3));
|
||||
|
||||
let defaults = AiConfig::default();
|
||||
|
||||
let config = AiConfig {
|
||||
agent: AiAgentConfig {
|
||||
model: values
|
||||
.get("ai.agent.model")
|
||||
.and_then(|v| v.as_str())
|
||||
.unwrap_or(&defaults.agent.model)
|
||||
.to_string(),
|
||||
temperature: values
|
||||
.get("ai.agent.temperature")
|
||||
.and_then(|v| v.as_f64())
|
||||
.unwrap_or(defaults.agent.temperature as f64)
|
||||
as f32,
|
||||
max_tokens: values
|
||||
.get("ai.agent.max_tokens")
|
||||
.and_then(|v| v.as_u64())
|
||||
.unwrap_or(defaults.agent.max_tokens as u64) as u32,
|
||||
max_iterations: values
|
||||
.get("ai.agent.max_iterations")
|
||||
.and_then(|v| v.as_u64())
|
||||
.unwrap_or(defaults.agent.max_iterations as u64)
|
||||
as usize,
|
||||
system_prompt: defaults.agent.system_prompt,
|
||||
},
|
||||
analysis_defaults: defaults.analysis_defaults,
|
||||
};
|
||||
|
||||
assert_eq!(config.agent.model, "gpt-4o");
|
||||
assert!((config.agent.temperature - 0.5).abs() < f32::EPSILON);
|
||||
assert_eq!(config.agent.max_tokens, 4096);
|
||||
assert_eq!(config.agent.max_iterations, 3);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user