wulf-pulse/app/api/veeam/ticket-analysis/route.ts

import { NextRequest, NextResponse } from 'next/server';
import postgresClient from '@/lib/services/postgres-client';

export async function GET(req: NextRequest) {
  const { searchParams } = new URL(req.url);
  const page     = Math.max(1, parseInt(searchParams.get('page')  ?? '1'));
  const limit    = 50;
  const offset   = (page - 1) * limit;
  const category = searchParams.get('category');
  const company  = searchParams.get('company');

  // Build filter for ticket list only (aggregations always show all data)
  const filterWhere: string[] = [];
  const filterParams: any[]   = [];

  if (category) {
    filterParams.push(category);
    filterWhere.push(`problem_category = $${filterParams.length}`);
  }
  if (company) {
    filterParams.push(`%${company}%`);
    filterWhere.push(`company_name ILIKE $${filterParams.length}`);
  }

  const baseWhere = filterWhere.length
    ? `WHERE ticket_created_at >= DATE_TRUNC('year', NOW()) AND ${filterWhere.join(' AND ')}`
    : `WHERE ticket_created_at >= DATE_TRUNC('year', NOW())`;

  const [statsRes, categoryRes, resolutionRes, skillsRes, complexityRes, ticketsRes, totalRes, ytdRes] =
    await Promise.all([
      // Overall stats (unfiltered)
      postgresClient.query(`
        SELECT
          COUNT(*)                                                                           AS total_analyzed,
          ROUND(AVG(hours_worked)::numeric, 2)                                              AS avg_hours,
          ROUND(100.0 * COUNT(*) FILTER (WHERE same_day_close)
            / NULLIF(COUNT(*), 0), 1)                                                       AS same_day_pct,
          ROUND(100.0 * COUNT(*) FILTER (WHERE preventable = true)
            / NULLIF(COUNT(*) FILTER (WHERE preventable IS NOT NULL), 0), 1)                AS preventable_pct,
          ROUND(100.0 * COUNT(*) FILTER (WHERE device_was_offline = true)
            / NULLIF(COUNT(*) FILTER (WHERE device_was_offline IS NOT NULL), 0), 1)         AS offline_pct,
          ROUND(100.0 * COUNT(*) FILTER (WHERE backup_completed_before_tech = true)
            / NULLIF(COUNT(*) FILTER (WHERE backup_completed_before_tech IS NOT NULL), 0), 1) AS auto_resolved_pct
        FROM veeam_ticket_analysis
        WHERE ticket_created_at >= DATE_TRUNC('year', NOW())
      `),

      // By problem category (unfiltered)
      postgresClient.query(`
        SELECT problem_category,
               COUNT(*)                                                           AS count,
               ROUND(AVG(hours_worked)::numeric, 2)                              AS avg_hours,
               ROUND(100.0 * COUNT(*) FILTER (WHERE same_day_close)
                 / NULLIF(COUNT(*), 0), 1)                                        AS same_day_pct
        FROM veeam_ticket_analysis
        WHERE ticket_created_at >= DATE_TRUNC('year', NOW())
        GROUP BY problem_category
        ORDER BY count DESC
      `),

      // By resolution type (unfiltered)
      postgresClient.query(`
        SELECT resolution_type, COUNT(*) AS count
        FROM veeam_ticket_analysis
        WHERE ticket_created_at >= DATE_TRUNC('year', NOW())
        GROUP BY resolution_type
        ORDER BY count DESC
      `),

      // Skills frequency (unfiltered)
      postgresClient.query(`
        SELECT skill, COUNT(*) AS count
        FROM veeam_ticket_analysis, unnest(skills_required) AS skill
        WHERE ticket_created_at >= DATE_TRUNC('year', NOW())
        GROUP BY skill
        ORDER BY count DESC
        LIMIT 15
      `),

      // Complexity breakdown (unfiltered)
      postgresClient.query(`
        SELECT complexity, COUNT(*) AS count
        FROM veeam_ticket_analysis
        WHERE ticket_created_at >= DATE_TRUNC('year', NOW())
        GROUP BY complexity
        ORDER BY CASE complexity
          WHEN 'trivial' THEN 1 WHEN 'low' THEN 2 WHEN 'medium' THEN 3 WHEN 'high' THEN 4 ELSE 5
        END
      `),

      // Filtered ticket list
      postgresClient.query(`
        SELECT ticket_number, company_name, device_hostname,
               ticket_created_at, ticket_closed_at, same_day_close,
               hours_worked, problem_category, resolution_type, complexity,
               device_was_offline, backup_completed_before_tech, preventable,
               work_summary, recommended_procedure
        FROM veeam_ticket_analysis
        ${baseWhere}
        ORDER BY ticket_created_at DESC
        LIMIT $${filterParams.length + 1} OFFSET $${filterParams.length + 2}
      `, [...filterParams, limit, offset]),

      // Filtered total
      postgresClient.query(
        `SELECT COUNT(*) FROM veeam_ticket_analysis ${baseWhere}`,
        filterParams
      ),

      // YTD total all backup tickets
      postgresClient.query(`
        SELECT COUNT(*) AS total FROM tickets
        WHERE title ILIKE 'Veeam:%'
          AND title NOT ILIKE '[Veeam RPO]%'
          AND create_date >= DATE_TRUNC('year', NOW())
      `),
    ]);

  return NextResponse.json({
    stats: {
      ...statsRes.rows[0],
      total_ytd: parseInt(ytdRes.rows[0]?.total ?? 0),
    },
    by_category:  categoryRes.rows,
    by_resolution: resolutionRes.rows,
    skills:       skillsRes.rows,
    by_complexity: complexityRes.rows,
    tickets:      ticketsRes.rows,
    total:        parseInt(totalRes.rows[0]?.count ?? 0),
    page,
    limit,
  });
}