hms/crates/erp-ai/src/copilot/scoring.rs

use crate::copilot::rules::MatchedRuleData;

/// 风险评分结果
#[derive(Debug, Clone, serde::Serialize)]
pub struct RiskScore {
    pub score: i16,
    pub level: String,
    pub matched_rules: Vec<MatchedRule>,
}

#[derive(Debug, Clone, serde::Serialize)]
pub struct MatchedRule {
    pub rule_id: uuid::Uuid,
    pub name: String,
    pub score: i16,
    pub severity: String,
    pub suggestion: Option<String>,
}

/// 根据匹配规则计算风险评分
pub fn calculate_risk(matched: Vec<MatchedRuleData>) -> RiskScore {
    let total: i16 = matched.iter().map(|(_, _, s, _, _)| *s).sum();
    let clamped = total.clamp(0, 10);
    let level = match clamped {
        0..=2 => "low".to_string(),
        3..=5 => "medium".to_string(),
        6..=8 => "high".to_string(),
        _ => "critical".to_string(),
    };
    let matched_rules = matched
        .into_iter()
        .map(|(id, name, score, severity, suggestion)| MatchedRule {
            rule_id: id,
            name,
            score,
            severity,
            suggestion,
        })
        .collect();
    RiskScore {
        score: clamped,
        level,
        matched_rules,
    }
}

/// LLM 补充分析：基于规则评分结果和患者数据，生成自然语言的补充洞察
/// 失败时返回 None（降级为纯规则模式）
pub async fn llm_supplement(
    provider_registry: &crate::provider::registry::ProviderRegistry,
    preferred_provider: &str,
    risk_score: &RiskScore,
    patient_data: &serde_json::Value,
) -> Option<String> {
    let prompt = format!(
        "基于以下患者风险评分和匹配规则，是否存在规则未覆盖的风险因素？\
         风险评分：{}/10，等级：{}\n\
         匹配规则：{}\n\
         患者近期数据摘要：{}\n\
         请给出简洁的补充分析（100字以内），如无补充请回复\"无补充\"。",
        risk_score.score,
        risk_score.level,
        risk_score
            .matched_rules
            .iter()
            .map(|r| format!("- {}（+{}分）", r.name, r.score))
            .collect::<Vec<_>>()
            .join("\n"),
        serde_json::to_string(&serde_json::json!({
            "latest_bp": patient_data.get("vital_signs"),
            "latest_lab": patient_data.get("lab_reports"),
        }))
        .unwrap_or_default(),
    );
    let resolved: crate::error::AiResult<_> = provider_registry.resolve(preferred_provider).await;
    let resolved = resolved.ok()?;
    let req = crate::dto::GenerateRequest {
        system_prompt: "你是健康管理AI助手，负责对患者的风险评分进行补充分析。".into(),
        user_prompt: prompt,
        model: String::new(),
        temperature: 0.3,
        max_tokens: 256,
    };
    let resp: crate::error::AiResult<_> = resolved.provider().generate(req).await;
    Some(resp.ok()?.content)
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_calculate_risk_low() {
        let matched = vec![];
        let result = calculate_risk(matched);
        assert_eq!(result.score, 0);
        assert_eq!(result.level, "low");
    }

    #[test]
    fn test_calculate_risk_high() {
        let matched = vec![
            (
                uuid::Uuid::now_v7(),
                "eGFR下降".into(),
                3,
                "warning".into(),
                Some("建议调整".into()),
            ),
            (
                uuid::Uuid::now_v7(),
                "血压偏高".into(),
                2,
                "warning".into(),
                None,
            ),
            (uuid::Uuid::now_v7(), "失约".into(), 1, "info".into(), None),
        ];
        let result = calculate_risk(matched);
        assert_eq!(result.score, 6);
        assert_eq!(result.level, "high");
        assert_eq!(result.matched_rules.len(), 3);
    }

    #[test]
    fn test_calculate_risk_clamp_at_10() {
        let matched = vec![
            (
                uuid::Uuid::now_v7(),
                "危急".into(),
                5,
                "critical".into(),
                None,
            ),
            (
                uuid::Uuid::now_v7(),
                "严重".into(),
                4,
                "critical".into(),
                None,
            ),
            (
                uuid::Uuid::now_v7(),
                "异常".into(),
                3,
                "warning".into(),
                None,
            ),
        ];
        let result = calculate_risk(matched);
        assert_eq!(result.score, 10);
        assert_eq!(result.level, "critical");
    }
}