pub mod structured_source;

use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use uuid::Uuid;

use crate::error::AiResult;

/// 知识源 trait — 统一结构化和未来向量检索的知识获取接口
#[async_trait]
pub trait KnowledgeSource: Send + Sync {
    /// 根据查询获取知识上下文
    async fn get_context(&self, query: &KnowledgeQuery) -> AiResult<KnowledgeContext>;

    /// 知识源类型标识
    fn source_type(&self) -> &str;

    /// 健康检查
    async fn health_check(&self) -> AiResult<bool>;
}

/// 知识查询参数
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KnowledgeQuery {
    pub tenant_id: Uuid,
    pub analysis_type: String,
    pub patient_context: Option<PatientSummary>,
    pub query_text: Option<String>,
}

/// 脱敏患者摘要（不含 PII）
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PatientSummary {
    pub age: Option<i32>,
    pub gender: Option<String>,
    pub tags: Vec<String>,
}

/// 知识上下文（返回给 Prompt 注入）
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KnowledgeContext {
    pub source: String,
    pub context_text: String,
    pub references: Vec<Reference>,
    pub confidence: f32,
}

/// 参考引用
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Reference {
    pub title: String,
    pub source: String,
    pub relevance_score: f32,
}

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

    #[test]
    fn knowledge_query_construction() {
        let query = KnowledgeQuery {
            tenant_id: Uuid::now_v7(),
            analysis_type: "lab_report".into(),
            patient_context: Some(PatientSummary {
                age: Some(65),
                gender: Some("male".into()),
                tags: vec!["高血压".into(), "糖尿病".into()],
            }),
            query_text: Some("血红蛋白偏低".into()),
        };
        assert_eq!(query.analysis_type, "lab_report");
        assert_eq!(query.patient_context.as_ref().unwrap().tags.len(), 2);
    }

    #[test]
    fn knowledge_context_serde_roundtrip() {
        let ctx = KnowledgeContext {
            source: "structured".into(),
            context_text: "【规则】血压 >140 需关注".into(),
            references: vec![Reference {
                title: "高血压指南".into(),
                source: "system".into(),
                relevance_score: 0.95,
            }],
            confidence: 0.9,
        };
        let json = serde_json::to_string(&ctx).unwrap();
        let back: KnowledgeContext = serde_json::from_str(&json).unwrap();
        assert_eq!(back.source, "structured");
        assert_eq!(back.references.len(), 1);
        assert!((back.confidence - 0.9).abs() < 0.01);
    }

    #[test]
    fn patient_summary_serde() {
        let summary = PatientSummary {
            age: Some(70),
            gender: Some("female".into()),
            tags: vec![],
        };
        let json = serde_json::to_string(&summary).unwrap();
        let back: PatientSummary = serde_json::from_str(&json).unwrap();
        assert_eq!(back.age, Some(70));
    }

    #[test]
    fn truncate_context_text() {
        let long_text: String = "x".repeat(10000);
        let max_chars = 8000;
        let truncated = if long_text.len() > max_chars {
            long_text[..max_chars].to_string()
        } else {
            long_text
        };
        assert_eq!(truncated.len(), max_chars);
    }
}