pn-new-crm/src/lib/queue/workers/ai.ts

import { Worker, type Job } from 'bullmq';

import type { ConnectionOptions } from 'bullmq';
import { logger } from '@/lib/logger';
import { QUEUE_CONFIGS } from '@/lib/queue';

// ─── Email draft generation ───────────────────────────────────────────────────

const MAX_OUTPUT_BYTES = 10 * 1024; // 10 KB
const OPENAI_TIMEOUT_MS = 30_000; // 30 s

interface GenerateEmailDraftPayload {
  interestId: string;
  clientId: string;
  portId: string;
  context: 'follow_up' | 'introduction' | 'stage_update' | 'general';
  additionalInstructions?: string;
  requestedBy: string;
}

interface DraftResult {
  subject: string;
  body: string;
  generatedAt: string;
}

async function generateEmailDraft(payload: GenerateEmailDraftPayload): Promise<DraftResult> {
  const { interestId, clientId, portId, context, additionalInstructions } = payload;

  // Fetch data by IDs in the worker — never trust PII from the queue payload
  const { db } = await import('@/lib/db');
  const { interests } = await import('@/lib/db/schema/interests');
  const { clients } = await import('@/lib/db/schema/clients');
  const { berths } = await import('@/lib/db/schema/berths');
  const { interestNotes } = await import('@/lib/db/schema/interests');
  const { emailThreads } = await import('@/lib/db/schema/email');
  const { and, eq, desc } = await import('drizzle-orm');

  // Fetch interest, client, berth
  const [interest, client] = await Promise.all([
    db.query.interests.findFirst({
      where: and(eq(interests.id, interestId), eq(interests.portId, portId)),
    }),
    db.query.clients.findFirst({ where: eq(clients.id, clientId) }),
  ]);

  if (!interest || !client) {
    throw new Error('Interest or client not found');
  }

  let berthMooring: string | null = null;
  if (interest.berthId) {
    const berth = await db.query.berths.findFirst({
      where: eq(berths.id, interest.berthId),
    });
    berthMooring = berth?.mooringNumber ?? null;
  }

  // Fetch last 5 notes
  const recentNotes = await db
    .select({ content: interestNotes.content, createdAt: interestNotes.createdAt })
    .from(interestNotes)
    .where(eq(interestNotes.interestId, interestId))
    .orderBy(desc(interestNotes.createdAt))
    .limit(5);

  // Fetch last 5 email subjects (via threads linked to client)
  const recentThreads = await db
    .select({ subject: emailThreads.subject, lastMessageAt: emailThreads.lastMessageAt })
    .from(emailThreads)
    .where(and(eq(emailThreads.clientId, clientId), eq(emailThreads.portId, portId)))
    .orderBy(desc(emailThreads.lastMessageAt))
    .limit(5);

  const apiKey = process.env.OPENAI_API_KEY;

  if (!apiKey) {
    // Fallback: template-based draft
    return buildTemplateDraft({
      clientName: client.fullName,
      context,
      berthMooring,
      pipelineStage: interest.pipelineStage,
    });
  }

  // Build prompt
  const contextDescriptions: Record<string, string> = {
    follow_up: 'a friendly follow-up email',
    introduction: 'an initial introduction email',
    stage_update: `an email informing the client about their pipeline progression to stage "${interest.pipelineStage}"`,
    general: 'a general communication email',
  };

  const prompt = [
    `Write ${contextDescriptions[context] ?? 'an email'} to a marina berth client.`,
    '',
    `Client name: ${client.fullName}`,
    berthMooring ? `Berth: ${berthMooring}` : 'Berth: not yet assigned',
    `Pipeline stage: ${interest.pipelineStage}`,
    '',
    recentNotes.length > 0
      ? `Recent notes:\n${recentNotes.map((n) => `- ${n.content.slice(0, 200)}`).join('\n')}`
      : null,
    recentThreads.length > 0
      ? `Recent email subjects:\n${recentThreads.map((t) => `- ${t.subject ?? '(no subject)'}`).join('\n')}`
      : null,
    additionalInstructions ? `Additional instructions: ${additionalInstructions}` : null,
    '',
    'Return JSON with keys: subject (string) and body (string, plain text).',
  ]
    .filter(Boolean)
    .join('\n');

  // Call OpenAI with timeout
  const controller = new AbortController();
  const timeoutId = setTimeout(() => controller.abort(), OPENAI_TIMEOUT_MS);

  let subject: string;
  let body: string;

  try {
    const response = await fetch('https://api.openai.com/v1/chat/completions', {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        Authorization: `Bearer ${apiKey}`,
      },
      body: JSON.stringify({
        model: 'gpt-4o-mini',
        messages: [
          {
            role: 'system',
            content:
              'You are an expert marina sales and relationship manager. Generate professional, concise emails. Always return valid JSON with "subject" and "body" keys only.',
          },
          { role: 'user', content: prompt },
        ],
        max_tokens: 800,
        temperature: 0.7,
        response_format: { type: 'json_object' },
      }),
      signal: controller.signal,
    });

    clearTimeout(timeoutId);

    if (!response.ok) {
      const errorText = await response.text().catch(() => '');
      throw new Error(`OpenAI API error ${response.status}: ${errorText}`);
    }

    const data = (await response.json()) as {
      choices: Array<{ message: { content: string } }>;
    };

    const content = data.choices[0]?.message?.content ?? '{}';

    // Enforce output size cap
    if (content.length > MAX_OUTPUT_BYTES) {
      throw new Error('AI output exceeded 10 KB cap');
    }

    const parsed = JSON.parse(content) as { subject?: string; body?: string };
    subject = parsed.subject ?? `Follow-up: ${client.fullName}`;
    body = parsed.body ?? '';
  } catch (err) {
    clearTimeout(timeoutId);
    logger.warn({ err, interestId }, 'OpenAI call failed, falling back to template draft');
    return buildTemplateDraft({
      clientName: client.fullName,
      context,
      berthMooring,
      pipelineStage: interest.pipelineStage,
    });
  }

  return { subject, body, generatedAt: new Date().toISOString() };
}

// ─── Template fallback ────────────────────────────────────────────────────────

function buildTemplateDraft(opts: {
  clientName: string;
  context: string;
  berthMooring: string | null;
  pipelineStage: string;
}): DraftResult {
  const { clientName, context, berthMooring, pipelineStage } = opts;
  const berthText = berthMooring ? `berth ${berthMooring}` : 'your requested berth';

  const templates: Record<string, { subject: string; body: string }> = {
    introduction: {
      subject: `Welcome to Port Nimara – ${clientName}`,
      body: `Dear ${clientName},\n\nThank you for your interest in Port Nimara. We are delighted to introduce our marina facilities and look forward to discussing how we can accommodate your needs for ${berthText}.\n\nPlease feel free to reach out at any time.\n\nKind regards,\nPort Nimara Team`,
    },
    follow_up: {
      subject: `Following up – ${clientName}`,
      body: `Dear ${clientName},\n\nI wanted to follow up regarding your interest in ${berthText}. Please let us know if you have any questions or if there is anything we can assist you with.\n\nWe look forward to hearing from you.\n\nKind regards,\nPort Nimara Team`,
    },
    stage_update: {
      subject: `Update on your application – ${clientName}`,
      body: `Dear ${clientName},\n\nWe are pleased to inform you that your application for ${berthText} has progressed to the "${pipelineStage.replace(/_/g, ' ')}" stage.\n\nWe will be in touch shortly with the next steps.\n\nKind regards,\nPort Nimara Team`,
    },
    general: {
      subject: `Message from Port Nimara – ${clientName}`,
      body: `Dear ${clientName},\n\nThank you for your continued interest in Port Nimara. We appreciate your patience and look forward to assisting you with ${berthText}.\n\nKind regards,\nPort Nimara Team`,
    },
  };

  const template = templates[context] ?? templates['general']!;
  return { ...template, generatedAt: new Date().toISOString() };
}

// ─── Worker ───────────────────────────────────────────────────────────────────

export const aiWorker = new Worker(
  'ai',
  async (job: Job) => {
    logger.info({ jobId: job.id, jobName: job.name }, 'Processing AI job');

    switch (job.name) {
      case 'generate-email-draft': {
        const payload = job.data as GenerateEmailDraftPayload;
        const result = await generateEmailDraft(payload);
        return result;
      }

      default:
        logger.warn({ jobName: job.name }, 'Unknown AI job');
        return undefined;
    }
  },
  {
    connection: { url: process.env.REDIS_URL! } as ConnectionOptions,
    concurrency: QUEUE_CONFIGS.ai.concurrency,
  },
);

aiWorker.on('failed', (job, err) => {
  logger.error({ jobId: job?.id, jobName: job?.name, err }, 'AI job failed');
});