import "@supabase/functions-js/edge-runtime.d.ts";
import { createClient } from "https://esm.sh/@supabase/supabase-js@2";
import { normalizeInstagramHandle } from "../_shared/normalizeHandles.ts";

const corsHeaders = {
  "Access-Control-Allow-Origin": "*",
  "Access-Control-Allow-Headers":
    "authorization, x-client-info, apikey, content-type",
};

interface ReportRequest {
  url: string;
  clinicName?: string;
}

Deno.serve(async (req) => {
  if (req.method === "OPTIONS") {
    return new Response("ok", { headers: corsHeaders });
  }

  try {
    const { url, clinicName } = (await req.json()) as ReportRequest;

    if (!url) {
      return new Response(
        JSON.stringify({ error: "URL is required" }),
        { status: 400, headers: { ...corsHeaders, "Content-Type": "application/json" } }
      );
    }

    const PERPLEXITY_API_KEY = Deno.env.get("PERPLEXITY_API_KEY");
    if (!PERPLEXITY_API_KEY) {
      throw new Error("PERPLEXITY_API_KEY not configured");
    }

    const supabaseUrl = Deno.env.get("SUPABASE_URL")!;
    const supabaseKey = Deno.env.get("SUPABASE_SERVICE_ROLE_KEY")!;

    // Step 1: Call scrape-website function
    const scrapeRes = await fetch(`${supabaseUrl}/functions/v1/scrape-website`, {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${supabaseKey}`,
      },
      body: JSON.stringify({ url, clinicName }),
    });
    const scrapeResult = await scrapeRes.json();

    if (!scrapeResult.success) {
      throw new Error(`Scraping failed: ${scrapeResult.error}`);
    }

    const clinic = scrapeResult.data.clinic;
    const resolvedName = clinicName || clinic.clinicName || url;
    const services = clinic.services || [];
    const address = clinic.address || "";

    // Step 2: Call analyze-market function
    const analyzeRes = await fetch(`${supabaseUrl}/functions/v1/analyze-market`, {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${supabaseKey}`,
      },
      body: JSON.stringify({
        clinicName: resolvedName,
        services,
        address,
        scrapeData: scrapeResult.data,
      }),
    });
    const analyzeResult = await analyzeRes.json();

    // Step 3: Generate final report with Gemini
    const reportPrompt = `
당신은 프리미엄 의료 마케팅 전문 분석가입니다. 아래 데이터를 기반으로 종합 마케팅 인텔리전스 리포트를 생성해주세요.

## 수집된 데이터

### 병원 정보
${JSON.stringify(scrapeResult.data, null, 2)}

### 시장 분석
${JSON.stringify(analyzeResult.data?.analysis || {}, null, 2)}

## 리포트 형식 (반드시 아래 JSON 구조로 응답)

{
  "clinicInfo": {
    "name": "병원명",
    "address": "주소",
    "phone": "전화번호",
    "services": ["시술1", "시술2"],
    "doctors": [{"name": "의사명", "specialty": "전문분야"}]
  },
  "executiveSummary": "경영진 요약 (3-5문장)",
  "overallScore": 0-100,
  "channelAnalysis": {
    "naverBlog": { "score": 0-100, "status": "active|inactive|weak", "posts": 0, "recommendation": "추천사항" },
    "instagram": { "score": 0-100, "status": "active|inactive|weak", "followers": 0, "recommendation": "추천사항" },
    "youtube": { "score": 0-100, "status": "active|inactive|weak", "subscribers": 0, "recommendation": "추천사항" },
    "naverPlace": { "score": 0-100, "rating": 0, "reviews": 0, "recommendation": "추천사항" },
    "gangnamUnni": { "score": 0-100, "rating": 0, "reviews": 0, "recommendation": "추천사항" },
    "website": { "score": 0-100, "issues": [], "recommendation": "추천사항" }
  },
  "competitors": [
    { "name": "경쟁병원명", "strengths": ["강점1"], "weaknesses": ["약점1"], "marketingChannels": ["채널1"] }
  ],
  "keywords": {
    "primary": [{"keyword": "키워드", "monthlySearches": 0, "competition": "high|medium|low"}],
    "longTail": [{"keyword": "롱테일 키워드", "monthlySearches": 0}]
  },
  "targetAudience": {
    "primary": { "ageRange": "25-35", "gender": "female", "interests": ["관심사1"], "channels": ["채널1"] },
    "secondary": { "ageRange": "35-45", "gender": "female", "interests": ["관심사1"], "channels": ["채널1"] }
  },
  "recommendations": [
    { "priority": "high|medium|low", "category": "카테고리", "title": "제목", "description": "설명", "expectedImpact": "기대 효과" }
  ],
  "marketTrends": ["트렌드1", "트렌드2"]
}
`;

    const aiRes = await fetch("https://api.perplexity.ai/chat/completions", {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${PERPLEXITY_API_KEY}`,
      },
      body: JSON.stringify({
        model: "sonar",
        messages: [
          {
            role: "system",
            content: "You are a Korean medical marketing analyst. Respond ONLY with valid JSON, no markdown code blocks. Always respond in Korean for text fields.",
          },
          { role: "user", content: reportPrompt },
        ],
        temperature: 0.3,
      }),
    });

    const aiData = await aiRes.json();
    let reportText = aiData.choices?.[0]?.message?.content || "";
    // Strip markdown code blocks if present
    const jsonMatch = reportText.match(/```(?:json)?\n?([\s\S]*?)```/);
    if (jsonMatch) reportText = jsonMatch[1];

    let report;
    try {
      report = JSON.parse(reportText);
    } catch {
      report = { raw: reportText, parseError: true };
    }

    // Normalize social handles from scrape data
    const socialMedia = clinic.socialMedia || {};
    const normalizedHandles = {
      instagram: normalizeInstagramHandle(socialMedia.instagram),
      youtube: socialMedia.youtube || null,
      facebook: socialMedia.facebook || null,
      blog: socialMedia.blog || null,
    };

    // Embed normalized handles in report for DB persistence
    report.socialHandles = normalizedHandles;

    // Save to Supabase
    const supabase = createClient(supabaseUrl, supabaseKey);
    const { data: saved, error: saveError } = await supabase
      .from("marketing_reports")
      .insert({
        url,
        clinic_name: resolvedName,
        report,
        scrape_data: scrapeResult.data,
        analysis_data: analyzeResult.data,
      })
      .select("id")
      .single();

    return new Response(
      JSON.stringify({
        success: true,
        reportId: saved?.id || null,
        report,
        metadata: {
          url,
          clinicName: resolvedName,
          generatedAt: new Date().toISOString(),
          dataSources: {
            scraping: scrapeResult.success,
            marketAnalysis: analyzeResult.success,
            aiGeneration: !report.parseError,
          },
          socialHandles: normalizedHandles,
          address,
          services,
        },
      }),
      { headers: { ...corsHeaders, "Content-Type": "application/json" } }
    );
  } catch (error) {
    return new Response(
      JSON.stringify({ success: false, error: error.message }),
      { status: 500, headers: { ...corsHeaders, "Content-Type": "application/json" } }
    );
  }
});