import express from 'express';

import { genAI, getMcpTool } from './llm/gemini';

import { systemPrompt } from './systemPrompt'; // Import the repository info from a separate file
import { iniciarProcesoCognitivo } from './cognition/index'; // Import the MCP function to start cognitive processes
import type { Conversation, Msg, Participant } from './types'; // Import the Conversation type
import dotenv from 'dotenv';

dotenv.config();



const PORT = Number(process.env.PORT) || 8001;
const API_KEY = process.env.GEMINI_API_KEY || '';
console.log(`Using Gemini API key: ${API_KEY}`);





/**
 * Descripción de alto nivel para que cualquier agente (humano o LLM) entienda y
 * trabaje con el repositorio sin perder tiempo buscando contexto.
 */



const app = express();
app.use(express.json());

app.post('/', async (req, res) => {
  const conversation = req.body?.conversation as Conversation | undefined;
  if (!conversation) return res.status(400).json({ error: 'Missing conversation' });
  const lastMsg = conversation.messages[conversation.messages.length - 1];
  const message = lastMsg?.text || '';

  const context = conversation.messages
    .slice(-10)
    .map((m) => {
      const sender =
        conversation.participants.find((p) => p.id === m.from)?.name || m.from;
      const content = m.text || `[${m.type}]`;
      return `${sender}: ${content}`;
    })
    .join('\n');

  if (!genAI) {
    return res.json({ reply: systemPrompt });
  }

  try {
    const contents = `${systemPrompt}\nConversation:\n${context}\n`;
    const result = await iniciarProcesoCognitivo({})
    const reply = (result.text || '').trim();
    res.json({ reply });
  } catch (err: any) {
    console.error('Gemini error', err.message);
    res.status(500).json({ error: 'Failed to generate reply' });
  }
});

app.get('/', (req, res) => {
  res.send(`
    <h1>Conversation Layer Agent</h1>
    <p>This service answers questions about the repository.</p>
    <p>Send a POST request to / with a JSON body containing {"conversation": {...}}</p>
    <p>Example: {"conversation": {"chatId": "123@c.us", "title": "Chat", "isGroup": false, "unreadCount": 0, "participants": [{"id": "123@c.us", "name": "Alice", "isMe": false}], "messages": [{"id": "m1", "from": "123@c.us", "to": "me@c.us", "ts": 0, "type": "chat", "text": "hello", "meta": {"ack":0,"hasReaction":false,"isQuoted":false}}]}}</p>
    <p>It will respond with a JSON object containing {"reply": "the answer"}</p>

    <p>Repository info: ${systemPrompt}</p>
  `);
}
);

app.listen(PORT, () => {
  console.log(`conversation-layer-agent listening on ${PORT}`);
});