const [timeRange = "30d", maxResults = "500"] = process.argv.slice(2);
const maxResultsNum = parseInt(maxResults);
const BATCH_SIZE = 50; // Smaller batches to avoid timeouts

// Convert time range to Gmail query format
const timeRangeMap = {
  "30d": "newer_than:30d",
  "90d": "newer_than:90d",
  "1y": "newer_than:1y",
  "all": ""
};

const timeQuery = timeRangeMap[timeRange] || timeRangeMap["30d"];
const searchQuery = timeQuery ? `in:sent ${timeQuery}` : "in:sent";

console.log(`Fetching sent messages with query: ${searchQuery}`);
console.log(`Maximum results: ${maxResultsNum}`);

try {
  // Step 1: Fetch list of sent message IDs
  const listRes = await fetch(
    `https://gmail.googleapis.com/gmail/v1/users/me/messages?maxResults=${maxResultsNum}&q=${encodeURIComponent(searchQuery)}`,
    {
      headers: { Authorization: "Bearer PLACEHOLDER_TOKEN" }
    }
  );

  if (!listRes.ok) {
    console.error(`Gmail API list failed: ${listRes.status}`);
    console.error(await listRes.text());
    throw new Error(`Failed to list sent messages: ${listRes.status}`);
  }

  const listData = await listRes.json();

  if (!listData.messages || listData.messages.length === 0) {
    console.log("No sent messages found in specified time range");
    console.log(JSON.stringify({
      error: "No sent messages found",
      timeRange: timeRange
    }, null, 2));
    process.exit(0);
  }

  console.log(`Found ${listData.messages.length} message(s), fetching in batches of ${BATCH_SIZE}...`);

  const messages = [];
  const messageIds = listData.messages.map(m => m.id);

  // Step 2: Fetch messages in batches with parallel processing
  for (let i = 0; i < messageIds.length; i += BATCH_SIZE) {
    const batch = messageIds.slice(i, i + BATCH_SIZE);
    console.log(`Fetching batch ${Math.floor(i / BATCH_SIZE) + 1} (${batch.length} messages)...`);

    const batchResults = await Promise.all(
      batch.map(async (msgId) => {
        try {
          const detailRes = await fetch(
            `https://gmail.googleapis.com/gmail/v1/users/me/messages/${msgId}?format=metadata&metadataHeaders=Subject&metadataHeaders=To&metadataHeaders=Cc&metadataHeaders=Date`,
            {
              headers: { Authorization: "Bearer PLACEHOLDER_TOKEN" }
            }
          );

          if (!detailRes.ok) {
            console.error(`Failed to fetch message ${msgId}: ${detailRes.status}`);
            return null;
          }

          const detail = await detailRes.json();

          const getHeader = (name) => {
            const header = detail.payload.headers.find(h => h.name.toLowerCase() === name.toLowerCase());
            return header ? header.value : "";
          };

          return {
            id: detail.id,
            threadId: detail.threadId,
            subject: getHeader("Subject"),
            to: getHeader("To"),
            cc: getHeader("Cc"),
            snippet: detail.snippet,
            date: getHeader("Date"),
            internalDate: detail.internalDate,
            labelIds: detail.labelIds || []
          };
        } catch (error) {
          console.error(`Error fetching message ${msgId}:`, error.message);
          return null;
        }
      })
    );

    const validMessages = batchResults.filter(m => m !== null);
    messages.push(...validMessages);

    console.log(`✓ Batch complete: ${validMessages.length}/${batch.length} messages fetched (total: ${messages.length}/${messageIds.length})`);

    // Early stop if we have enough data for pattern analysis (300+ messages)
    if (messages.length >= 300 && i + BATCH_SIZE < messageIds.length) {
      console.log(`✓ Collected ${messages.length} messages - sufficient for pattern analysis, stopping early`);
      break;
    }
  }

  console.log(`✓ Fetched ${messages.length} sent messages successfully`);

  // Step 3: Filter cold/marketing emails for personality analysis
  const coldEmailPatterns = [
    /unsubscribe/i,
    /opt.out/i,
    /click here/i,
    /view in browser/i,
    /follow us on/i,
    /\[BULK\]/i,
    /\[MARKETING\]/i,
    /newsletter/i,
    /promotional/i
  ];

  const isColdEmail = (email) => {
    const text = `${email.subject || ''} ${email.snippet || ''}`.toLowerCase();
    return coldEmailPatterns.some(pattern => pattern.test(text));
  };

  const personalEmails = messages.filter(e => !isColdEmail(e));
  const coldEmailCount = messages.length - personalEmails.length;

  if (coldEmailCount > 0) {
    console.log(`Filtered out ${coldEmailCount} cold/marketing emails (${(coldEmailCount / messages.length * 100).toFixed(1)}%), analyzing ${personalEmails.length} personal emails`);
  }

  const analysisEmails = personalEmails.length > 0 ? personalEmails : messages;

  console.log(`Aggregating ${analysisEmails.length} emails...`);

  // Step 4: Aggregate patterns

  // Time range analysis
  const dates = analysisEmails.map(e => parseInt(e.internalDate)).filter(d => !isNaN(d));
  const timeRange = {
    start: dates.length > 0 ? new Date(Math.min(...dates)).toISOString() : null,
    end: dates.length > 0 ? new Date(Math.max(...dates)).toISOString() : null,
    totalCount: messages.length,
    personalCount: analysisEmails.length,
    coldEmailsFiltered: coldEmailCount
  };

  // Recipient analysis
  const recipientCounts = {};
  const domainCounts = {};
  let internalCount = 0;
  let externalCount = 0;

  analysisEmails.forEach(email => {
    const recipients = [];
    if (email.to) recipients.push(...email.to.split(',').map(r => r.trim()));
    if (email.cc) recipients.push(...email.cc.split(',').map(r => r.trim()));

    recipients.forEach(recipient => {
      const emailMatch = recipient.match(/<([^>]+)>/) || [null, recipient];
      const emailAddr = emailMatch[1] || recipient;

      recipientCounts[emailAddr] = (recipientCounts[emailAddr] || 0) + 1;

      const domain = emailAddr.split('@')[1] || 'unknown';
      domainCounts[domain] = (domainCounts[domain] || 0) + 1;

      if (domain.includes('company') || domain.includes('corp') || domain.includes('.internal')) {
        internalCount++;
      } else {
        externalCount++;
      }
    });
  });

  const topRecipients = Object.entries(recipientCounts)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([email, count]) => ({ email, count }));

  const topDomains = Object.entries(domainCounts)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([domain, count]) => ({ domain, count }));

  const recipientStats = {
    topRecipients,
    topDomains,
    uniqueRecipients: Object.keys(recipientCounts).length,
    internalVsExternal: {
      internal: internalCount,
      external: externalCount,
      ratio: internalCount > 0 ? (externalCount / internalCount).toFixed(2) : 'N/A'
    }
  };

  // Topic clustering
  const subjectWords = {};
  const threadCounts = {};

  analysisEmails.forEach(email => {
    threadCounts[email.threadId] = (threadCounts[email.threadId] || 0) + 1;

    const subject = email.subject || '';
    const words = subject.toLowerCase()
      .replace(/re:|fwd:|fw:/gi, '')
      .split(/\s+/)
      .filter(w => w.length > 3 && !['the', 'and', 'for', 'with', 'from'].includes(w));

    words.forEach(word => {
      subjectWords[word] = (subjectWords[word] || 0) + 1;
    });
  });

  const topTopics = Object.entries(subjectWords)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 15)
    .map(([word, count]) => ({ keyword: word, count }));

  // Time pattern analysis
  let morningCount = 0;
  let afternoonCount = 0;
  let eveningCount = 0;
  let nightCount = 0;
  let weekendCount = 0;

  analysisEmails.forEach(email => {
    const date = new Date(parseInt(email.internalDate));
    const hour = date.getHours();
    const day = date.getDay();

    if (day === 0 || day === 6) weekendCount++;

    if (hour >= 6 && hour < 12) morningCount++;
    else if (hour >= 12 && hour < 18) afternoonCount++;
    else if (hour >= 18 && hour < 22) eveningCount++;
    else nightCount++;
  });

  const timePatterns = {
    timeBuckets: {
      morning: morningCount,
      afternoon: afternoonCount,
      evening: eveningCount,
      night: nightCount
    },
    weekendRatio: (weekendCount / analysisEmails.length * 100).toFixed(1) + '%'
  };

  // Length patterns
  const lengths = analysisEmails.map(e => (e.snippet || '').length);
  const avgLength = lengths.reduce((a, b) => a + b, 0) / lengths.length;

  const lengthBuckets = {
    brief: lengths.filter(l => l < 100).length,
    standard: lengths.filter(l => l >= 100 && l < 200).length,
    detailed: lengths.filter(l => l >= 200 && l < 300).length,
    long: lengths.filter(l => l >= 300).length
  };

  const lengthPatterns = {
    avgSnippetLength: Math.round(avgLength),
    distribution: lengthBuckets
  };

  // Phrase analysis
  const openers = {};
  const commonWords = {};

  analysisEmails.forEach(email => {
    const snippet = email.snippet || '';
    const words = snippet.toLowerCase().split(/\s+/);

    if (words.length >= 2) {
      const opener = words.slice(0, 2).join(' ');
      openers[opener] = (openers[opener] || 0) + 1;
    }

    words.forEach(word => {
      if (word.length > 3) {
        commonWords[word] = (commonWords[word] || 0) + 1;
      }
    });
  });

  const topOpeners = Object.entries(openers)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 10)
    .map(([phrase, count]) => ({ phrase, count }));

  const topWords = Object.entries(commonWords)
    .sort((a, b) => b[1] - a[1])
    .slice(0, 20)
    .map(([word, count]) => ({ word, count }));

  const phraseAnalysis = {
    topOpeners,
    topWords
  };

  // Communication stats
  const threadDepths = Object.values(threadCounts);
  const avgThreadDepth = threadDepths.reduce((a, b) => a + b, 0) / threadDepths.length;

  const communicationStats = {
    totalThreads: Object.keys(threadCounts).length,
    avgThreadDepth: avgThreadDepth.toFixed(1),
    singleEmailThreads: threadDepths.filter(d => d === 1).length,
    multiEmailThreads: threadDepths.filter(d => d > 1).length
  };

  // Project signals
  const projectKeywords = ['project', 'meeting', 'deadline', 'review', 'deliverable', 'presentation', 'report'];
  const projectEmails = analysisEmails.filter(e =>
    projectKeywords.some(kw => (e.subject || '').toLowerCase().includes(kw) || (e.snippet || '').toLowerCase().includes(kw))
  );

  const projectSignals = {
    projectRelatedCount: projectEmails.length,
    projectRatio: (projectEmails.length / analysisEmails.length * 100).toFixed(1) + '%',
    keywordMatches: projectKeywords.map(kw => ({
      keyword: kw,
      count: analysisEmails.filter(e => (e.subject || '').toLowerCase().includes(kw) || (e.snippet || '').toLowerCase().includes(kw)).length
    })).filter(m => m.count > 0)
  };

  // Step 5: Output aggregated data
  const aggregates = {
    timeRange,
    recipientStats,
    topics: topTopics,
    timePatterns,
    lengthPatterns,
    phraseAnalysis,
    communicationStats,
    projectSignals
  };

  console.log(`✓ Aggregation complete`);
  console.log(JSON.stringify(aggregates, null, 2));

} catch (error) {
  console.error("Error in fetch and aggregate:", error.message);
  throw error;
}