import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: process.env.OPENAI_API_KEY,
    organization: process.env.OPENAI_ORGANIZATION,
});

export default openai;

import openai from "./openai";
import { ChatCompletionMessage } from "openai/resources/index.mjs";

const systemRoleContent = "You are capable of seeing the color of someone's aura based on how they answer questions. Your job is to look at a user's answers to specific questions and determine the color of their aura. Each question is numbered in order. The question and it's answer are separated by a |. Each question is separated by |||. Respond with a color.";

const model = 'gpt-3.5-turbo';

const query = async (prompt: string) => {

    if (prompt.length < 1) return false;

    const list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];

    function sleep(milliseconds: number): Promise<any> {
        return new Promise((resolve) => setTimeout(resolve, milliseconds));
    }

    for (const item in list) {
        const res: string | ChatCompletionMessage = await openai.chat.completions.create({
            model: model,
            messages: [
                { 'role': 'system', 'content': systemRoleContent }, // Tells the AI it's job
                { 'role': 'user', 'content': prompt },
            ],
            temperature: 0.86, // Values accepted: 0 - 2. The higher the value, the more random. The lower, the more deterministic. Recommended value: 0.5 - 1.
        }).then((res) => res.choices[Number(item)].message)
            .catch((err) => `Celebrity couldn't be determined! (Error: ${err.message})`);

            await sleep(500);

            if (typeof res === 'object') {
                return res.content; // Ensure you get a string back
            }

            return res;
    }
}

export default query;