use axum::extract::{Extension, FromRef, Path, Query, State};
use axum::response::sse::{Event, KeepAlive, Sse};
use axum::Json;
use erp_core::health_provider::TimeRange;
use erp_core::rbac::require_permission;
use erp_core::types::{ApiResponse, TenantContext};
use futures::StreamExt;
use serde::Deserialize;
use std::convert::Infallible;

use crate::dto::{AnalysisSseEvent, AnalysisType};
use crate::service::suggestion::SuggestionService;
use crate::state::AiState;

pub mod suggestion_handler;

// === 分析请求 Body ===

#[derive(Debug, Deserialize)]
pub struct AnalyzeBody {
    pub report_id: Option<uuid::Uuid>,
    pub patient_id: Option<uuid::Uuid>,
    pub metrics: Option<Vec<String>>,
}

// === SSE 分析端点 ===

pub async fn stream_lab_report<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Json(body): Json<AnalyzeBody>,
) -> Result<Sse<impl futures::Stream<Item = Result<Event, Infallible>>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.manage")?;
    let report_id = body.report_id.ok_or_else(|| {
        erp_core::error::AppError::Validation("report_id 必填".into())
    })?;

    let lab_dto = state
        .health_provider
        .get_lab_report(ctx.tenant_id, report_id)
        .await?;
    let sanitized_data = state.analysis.sanitizer.sanitize_lab_report(&lab_dto)?;

    let prompt = state
        .prompt
        .get_active_prompt(ctx.tenant_id, "lab_report_interpretation")
        .await?;

    let model_config = &prompt.model_config;
    let model = model_config["model"].as_str().unwrap_or("claude-sonnet-4-6").to_string();
    let temperature = model_config["temperature"].as_f64().unwrap_or(0.3) as f32;
    let max_tokens = model_config["max_tokens"].as_u64().unwrap_or(2048) as u32;

    let (stream, analysis_id, _provider_name) = state
        .analysis
        .stream_analyze(
            ctx.tenant_id,
            ctx.user_id,
            uuid::Uuid::nil(),
            AnalysisType::LabReport,
            report_id.to_string(),
            prompt.system_prompt,
            prompt.user_prompt_template,
            sanitized_data,
            model,
            temperature,
            max_tokens,
        )
        .await?;

    let analysis_id_clone = analysis_id;
    let state_clone = state.clone();
    let patient_id_clone = uuid::Uuid::nil(); // lab report 场景 patient_id 从 report 关联
    let doctor_id_clone = ctx.user_id;

    let sse_stream = build_sse_stream(stream, analysis_id_clone, state_clone, "lab_report", ctx.tenant_id, patient_id_clone, doctor_id_clone);
    Ok(Sse::new(sse_stream).keep_alive(KeepAlive::default()))
}

pub async fn stream_trends<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Json(body): Json<AnalyzeBody>,
) -> Result<Sse<impl futures::Stream<Item = Result<Event, Infallible>>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.manage")?;
    let patient_id = body.patient_id.ok_or_else(|| {
        erp_core::error::AppError::Validation("patient_id 必填".into())
    })?;

    let metrics = body.metrics.unwrap_or_else(|| {
        vec![
            "systolic_bp_morning".into(),
            "diastolic_bp_morning".into(),
            "heart_rate".into(),
            "weight".into(),
            "blood_sugar".into(),
        ]
    });
    let range = TimeRange {
        start: chrono::Utc::now() - chrono::Duration::days(90),
        end: chrono::Utc::now(),
    };

    let trend_data = state
        .health_provider
        .get_trend_analysis_data(ctx.tenant_id, patient_id, &metrics, &range)
        .await?;
    let sanitized_data = state.analysis.sanitizer.sanitize_trend_analysis(&trend_data)?;

    let prompt = state
        .prompt
        .get_active_prompt(ctx.tenant_id, "health_trend_analysis")
        .await?;

    let model_config = &prompt.model_config;
    let model = model_config["model"].as_str().unwrap_or("claude-sonnet-4-6").to_string();
    let temperature = model_config["temperature"].as_f64().unwrap_or(0.3) as f32;
    let max_tokens = model_config["max_tokens"].as_u64().unwrap_or(2048) as u32;

    let (stream, analysis_id, _) = state
        .analysis
        .stream_analyze(
            ctx.tenant_id,
            ctx.user_id,
            patient_id,
            AnalysisType::Trends,
            patient_id.to_string(),
            prompt.system_prompt,
            prompt.user_prompt_template,
            sanitized_data,
            model,
            temperature,
            max_tokens,
        )
        .await?;

    let analysis_id_clone = analysis_id;
    let state_clone = state.clone();

    let sse_stream = build_sse_stream(stream, analysis_id_clone, state_clone, "trend", ctx.tenant_id, uuid::Uuid::nil(), ctx.user_id);
    Ok(Sse::new(sse_stream).keep_alive(KeepAlive::default()))
}

pub async fn stream_checkup_plan<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Json(body): Json<AnalyzeBody>,
) -> Result<Sse<impl futures::Stream<Item = Result<Event, Infallible>>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.manage")?;
    let patient_id = body.patient_id.ok_or_else(|| {
        erp_core::error::AppError::Validation("patient_id 必填".into())
    })?;

    let summary_dto = state
        .health_provider
        .get_patient_summary(ctx.tenant_id, patient_id)
        .await?;
    let sanitized_data = state
        .analysis
        .sanitizer
        .sanitize_patient_summary(&summary_dto)?;

    let prompt = state
        .prompt
        .get_active_prompt(ctx.tenant_id, "personalized_checkup_plan")
        .await?;

    let model_config = &prompt.model_config;
    let model = model_config["model"].as_str().unwrap_or("claude-sonnet-4-6").to_string();
    let temperature = model_config["temperature"].as_f64().unwrap_or(0.3) as f32;
    let max_tokens = model_config["max_tokens"].as_u64().unwrap_or(2048) as u32;

    let (stream, analysis_id, _) = state
        .analysis
        .stream_analyze(
            ctx.tenant_id,
            ctx.user_id,
            patient_id,
            AnalysisType::CheckupPlan,
            patient_id.to_string(),
            prompt.system_prompt,
            prompt.user_prompt_template,
            sanitized_data,
            model,
            temperature,
            max_tokens,
        )
        .await?;

    let analysis_id_clone = analysis_id;
    let state_clone = state.clone();

    let sse_stream = build_sse_stream(stream, analysis_id_clone, state_clone, "checkup_plan", ctx.tenant_id, uuid::Uuid::nil(), ctx.user_id);
    Ok(Sse::new(sse_stream).keep_alive(KeepAlive::default()))
}

pub async fn stream_report_summary<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Json(body): Json<AnalyzeBody>,
) -> Result<Sse<impl futures::Stream<Item = Result<Event, Infallible>>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.manage")?;
    let report_id = body.report_id.ok_or_else(|| {
        erp_core::error::AppError::Validation("report_id 必填".into())
    })?;

    let report_dto = state
        .health_provider
        .get_full_report(ctx.tenant_id, report_id)
        .await?;
    let sanitized_data = state
        .analysis
        .sanitizer
        .sanitize_health_report(&report_dto)?;

    let prompt = state
        .prompt
        .get_active_prompt(ctx.tenant_id, "report_summary_generation")
        .await?;

    let model_config = &prompt.model_config;
    let model = model_config["model"].as_str().unwrap_or("claude-sonnet-4-6").to_string();
    let temperature = model_config["temperature"].as_f64().unwrap_or(0.3) as f32;
    let max_tokens = model_config["max_tokens"].as_u64().unwrap_or(2048) as u32;

    let (stream, analysis_id, _) = state
        .analysis
        .stream_analyze(
            ctx.tenant_id,
            ctx.user_id,
            uuid::Uuid::nil(),
            AnalysisType::ReportSummary,
            report_id.to_string(),
            prompt.system_prompt,
            prompt.user_prompt_template,
            sanitized_data,
            model,
            temperature,
            max_tokens,
        )
        .await?;

    let analysis_id_clone = analysis_id;
    let state_clone = state.clone();

    let sse_stream = build_sse_stream(stream, analysis_id_clone, state_clone, "report_summary", ctx.tenant_id, uuid::Uuid::nil(), ctx.user_id);
    Ok(Sse::new(sse_stream).keep_alive(KeepAlive::default()))
}

// === 分析历史 ===

#[derive(Debug, Deserialize)]
pub struct ListAnalysisQuery {
    pub patient_id: Option<uuid::Uuid>,
    pub analysis_type: Option<String>,
    pub page: Option<u64>,
    pub page_size: Option<u64>,
}

pub async fn list_analysis<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Query(params): Query<ListAnalysisQuery>,
) -> Result<Json<ApiResponse<serde_json::Value>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.list")?;
    let pagination = erp_core::types::Pagination {
        page: params.page,
        page_size: params.page_size,
    };
    let (items, total) = state
        .analysis
        .list_analysis(ctx.tenant_id, params.patient_id, params.analysis_type, &pagination)
        .await?;
    Ok(Json(ApiResponse::ok(serde_json::json!({
        "data": items,
        "total": total,
        "page": pagination.page.unwrap_or(1),
        "page_size": pagination.limit(),
    }))))
}

pub async fn get_analysis<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Path(id): Path<uuid::Uuid>,
) -> Result<Json<ApiResponse<crate::entity::ai_analysis::Model>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.analysis.list")?;
    let analysis = state.analysis.get_analysis(id, ctx.tenant_id).await?;
    Ok(Json(ApiResponse::ok(analysis)))
}

// === Prompt 管理 ===

#[derive(Debug, Deserialize)]
pub struct ListPromptsQuery {
    pub category: Option<String>,
    pub page: Option<u64>,
    pub page_size: Option<u64>,
}

pub async fn list_prompts<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Query(params): Query<ListPromptsQuery>,
) -> Result<Json<ApiResponse<serde_json::Value>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.prompt.list")?;
    let pagination = erp_core::types::Pagination {
        page: params.page,
        page_size: params.page_size,
    };
    let (items, total) = state
        .prompt
        .list_prompts(ctx.tenant_id, params.category, &pagination)
        .await?;
    Ok(Json(ApiResponse::ok(serde_json::json!({
        "data": items,
        "total": total,
        "page": pagination.page.unwrap_or(1),
        "page_size": pagination.limit(),
    }))))
}

#[derive(Debug, Deserialize)]
pub struct CreatePromptBody {
    pub name: String,
    pub description: Option<String>,
    pub system_prompt: String,
    pub user_prompt_template: String,
    pub model_config: serde_json::Value,
    pub category: String,
}

pub async fn create_prompt<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Json(body): Json<CreatePromptBody>,
) -> Result<Json<ApiResponse<crate::entity::ai_prompt::Model>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.prompt.manage")?;
    let prompt = state
        .prompt
        .create_prompt(
            ctx.tenant_id,
            ctx.user_id,
            body.name,
            body.system_prompt,
            body.user_prompt_template,
            body.model_config,
            body.category,
        )
        .await?;
    Ok(Json(ApiResponse::ok(prompt)))
}

pub async fn activate_prompt<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Path(id): Path<uuid::Uuid>,
) -> Result<Json<ApiResponse<crate::entity::ai_prompt::Model>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.prompt.manage")?;
    let prompt = state.prompt.activate_prompt(id, ctx.tenant_id).await?;
    Ok(Json(ApiResponse::ok(prompt)))
}

pub async fn rollback_prompt<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
    Path(id): Path<uuid::Uuid>,
) -> Result<Json<ApiResponse<crate::entity::ai_prompt::Model>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.prompt.manage")?;
    let prompt = state.prompt.rollback_prompt(id, ctx.tenant_id).await?;
    Ok(Json(ApiResponse::ok(prompt)))
}

// === 用量统计 ===

pub async fn usage_overview<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
) -> Result<Json<ApiResponse<serde_json::Value>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.usage.list")?;
    let overview = state.usage.get_overview(ctx.tenant_id).await?;
    Ok(Json(ApiResponse::ok(serde_json::json!({
        "total_count": overview.total_count,
    }))))
}

pub async fn usage_by_type<S>(
    State(state): State<AiState>,
    Extension(ctx): Extension<TenantContext>,
) -> Result<Json<ApiResponse<Vec<serde_json::Value>>>, erp_core::error::AppError>
where
    AiState: FromRef<S>,
    S: Clone + Send + Sync + 'static,
{
    require_permission(&ctx, "ai.usage.list")?;
    let types = state.usage.get_by_type(ctx.tenant_id).await?;
    let result: Vec<serde_json::Value> = types
        .into_iter()
        .map(|t| {
            serde_json::json!({
                "analysis_type": t.analysis_type,
                "count": t.count,
            })
        })
        .collect();
    Ok(Json(ApiResponse::ok(result)))
}

// === SSE 流构建辅助 ===

fn build_sse_stream(
    stream: std::pin::Pin<Box<dyn futures::Stream<Item = crate::error::AiResult<String>> + Send>>,
    analysis_id: uuid::Uuid,
    state: AiState,
    analysis_type: &'static str,
    tenant_id: uuid::Uuid,
    patient_id: uuid::Uuid,
    doctor_id: uuid::Uuid,
) -> impl futures::Stream<Item = Result<Event, Infallible>> {
    async_stream::stream! {
        let mut full_content = String::new();
        let mut index: u32 = 0;

        let mut stream = std::pin::pin!(stream);
        while let Some(result) = stream.next().await {
            match result {
                Ok(chunk) => {
                    full_content.push_str(&chunk);
                    index += 1;
                    let event = AnalysisSseEvent::Chunk { content: chunk, index };
                    let data = serde_json::to_string(&event).unwrap_or_default();
                    yield Ok(Event::default().event("chunk").data(data));
                }
                Err(e) => {
                    let event = AnalysisSseEvent::Error { message: e.to_string() };
                    let data = serde_json::to_string(&event).unwrap_or_default();
                    yield Ok(Event::default().event("error").data(data));
                    let _ = state.analysis.fail_analysis(analysis_id, e.to_string()).await;
                    // 发布 AI 分析失败事件
                    let fail_event = erp_core::events::DomainEvent::new(
                        "ai.analysis.failed",
                        tenant_id,
                        erp_core::events::build_event_payload(serde_json::json!({
                            "analysis_id": analysis_id,
                            "error": e.to_string(),
                        })),
                    );
                    state.event_bus.publish(fail_event, &state.db).await;
                    return;
                }
            }
        }

        let metadata = serde_json::json!({"analysis_type": analysis_type});
        let _ = state.analysis.complete_analysis(analysis_id, full_content.clone(), metadata).await;

        // 解析双通道输出并创建建议记录
        let parsed = crate::service::output_parser::parse_dual_channel(&full_content).unwrap_or(
            crate::dto::suggestion::ParsedOutput {
                text_content: full_content.clone(),
                structured: None,
            },
        );

        let mut event_payload = serde_json::json!({
            "analysis_id": analysis_id,
            "analysis_type": analysis_type,
            "patient_id": patient_id,
            "doctor_id": doctor_id,
        });

        if let Some(ref structured) = parsed.structured {
            event_payload["risk_level"] = serde_json::json!(structured.risk_level.as_str());
            event_payload["suggestion_count"] = serde_json::json!(structured.suggestions.len());

            if !structured.suggestions.is_empty() {
                let _ = SuggestionService::create_suggestions(
                    &state.db,
                    tenant_id,
                    analysis_id,
                    &structured.suggestions,
                    structured.risk_level,
                    &structured.baseline_summary,
                    Some(doctor_id),
                ).await;
            }
        } else {
            let _ = SuggestionService::mark_parse_failed(&state.db, analysis_id).await;
        }

        // 发布 AI 分析完成事件
        let event = erp_core::events::DomainEvent::new(
            "ai.analysis.completed",
            tenant_id,
            erp_core::events::build_event_payload(event_payload),
        );
        state.event_bus.publish(event, &state.db).await;

        let done_event = AnalysisSseEvent::Done {
            analysis_id,
            status: "completed".into(),
        };
        let data = serde_json::to_string(&done_event).unwrap_or_default();
        yield Ok(Event::default().event("done").data(data));
    }
}