import OpenAI from 'openai';

const OPENAI_API_KEY = process.env.OPENAI_API_KEY || 'test';
const LM_BASE_URL = process.env.LM_BASE_URL || 'http://localhost:1234/v1';

export const openai = new OpenAI({
  baseURL: LM_BASE_URL,
  apiKey: OPENAI_API_KEY,
});


import {buildRouterPrompt} from '../utils/llmUtils.js'
/**
 * Маршрутизация через LLM: возвращает { bot, reason }
 * @param {string} userText
 * @param {Array} bots - [{ name, description }]
 * @returns {Promise<{bot: string, reason: string}>}
 */
export async function routeByLLM(userText, bots) {
  const prompt = buildRouterPrompt(bots);

  console.log('prompt',prompt);

  const messages = [
    { role: 'system', content: prompt },
    { role: 'user', content: userText }
  ]

  console.log('messages',messages[1]);
  const data = {
    model: process.env.LM_MODEL || 'vikhrmodels-vikhr-nemo-12b-instruct-r-21-09-24',
    messages
  }
  const response = await openai.chat.completions.create(data)
  const content = response.choices[0]?.message?.content || '{}'

  console.log('content',content);
  let jsonString = content
  .replace(/```(?:json)?\s*/g, '')  // убираем ``` или ```json и любые пробелы/переводы строки после
  .replace(/```/g, '')              // убираем оставшиеся ```
  .trim();
  
  try {
    const result = JSON.parse(jsonString)
    // result: { bot, reason }
    return result
  } catch (e) {
    return { bot: 'unknown', reason: 'Ошибка парсинга ответа' }
  }
}