services/llm.js

import OpenAI from "openai";
import fs from "node:fs";
import path from "node:path";

// ── CONFIG LOADING ────────────────────────────────────────────
const DATA_DIR = process.env.DATA_DIR || "/data";
const CONFIG_PATH = path.join(DATA_DIR, "config.json");

function loadConfig() {
  try {
    if (!fs.existsSync(CONFIG_PATH)) {
      console.error(`Config file not found at ${CONFIG_PATH}`);
      process.exit(1);
    }
    const config = JSON.parse(fs.readFileSync(CONFIG_PATH, "utf8"));
    return config;
  } catch (error) {
    console.error(`Failed to load config from ${CONFIG_PATH}:`, error.message);
    process.exit(1);
  }
}

const config = loadConfig();

// ── OPENAI CONFIG ────────────────────────────────────────────
const openai = new OpenAI({
  apiKey: process.env.NVIDIA_API_KEY,
  baseURL: "https://integrate.api.nvidia.com/v1",
});

const OPENAI_MODEL = config.OPENAI_MODEL || "stepfun-ai/step-3.5-flash";

// ── STEP 1: Ask OpenAI to extract structured knowledge ────────
async function askOpenAI(rawText, prompt) {
  const completion = await openai.chat.completions.create({
    model: OPENAI_MODEL,
    messages: [
      {
        role: "system",
        content:
          "You are a JSON extraction engine. Return ONLY a valid JSON object. No markdown, no code fences, no text before or after. Your entire response must be parseable JSON.",
      },
      {
        role: "user",
        content: prompt,
      },
    ],
    temperature: 0.05,
    max_tokens: 4096,
  });

  return completion.choices[0]?.message?.content || "";
}

export { openai, OPENAI_MODEL, askOpenAI };