import { ClientOptions, OpenAI } from 'openai';
import { ChatCompletionMessageParam } from 'openai/resources';

enum GPTCallType {
    SUMMARY = 'summary',
    COMPLETION = 'completion',
    EDIT = 'edit',
    SORT = 'sort',
    DESCRIBE = 'describe',
    MERMAID = 'mermaid',
    DATA = 'data',
}

type GPTCallOpts = {
    model: string;
    maxTokens: number;
    temp: number;
    prompt: string;
};

const callTypeMap: { [type: string]: GPTCallOpts } = {
    // newest model: gpt-4
    summary: { model: 'gpt-3.5-turbo', maxTokens: 256, temp: 0.5, prompt: 'Summarize the text given in simpler terms.' },
    edit: { model: 'gpt-3.5-turbo', maxTokens: 256, temp: 0.5, prompt: 'Reword the text.' },
    completion: { model: 'gpt-3.5-turbo', maxTokens: 256, temp: 0.5, prompt: "You are a helpful assistant. Answer the user's prompt." },
    mermaid: {
        model: 'gpt-4-turbo',
        maxTokens: 2048,
        temp: 0,
        prompt: "(Heres an example of changing color of a pie chart to help you pie title Example \"Red\": 20 \"Blue\": 50 \"Green\": 30 %%{init: {'theme': 'base', 'themeVariables': {'pie1': '#0000FF', 'pie2': '#00FF00', 'pie3': '#FF0000'}}}%% keep in mind that pie1 is the highest since its sorted in descending order. Heres an example of a mindmap: mindmap  root((mindmap))    Origins      Long history      ::icon(fa fa-book)      Popularisation        British popular psychology author Tony Buzan    Research      On effectivness<br/>and features      On Automatic creation       Uses            Creative techniques            Strategic planning            Argument mapping    Tools      Pen and paper     Mermaid.  ",
    },
    data: {
        model: 'gpt-3.5-turbo',
        maxTokens: 256,
        temp: 0.5,
        prompt: "You are a helpful resarch assistant. Analyze the user's data to find meaningful patterns and/or correlation. Please only return a JSON with a correlation column 1 propert, a correlation column 2 property, and an analysis property. ",
    },
    sort: {
        model: 'gpt-4o',
        maxTokens: 2048,
        temp: 0.5,
        prompt: "I'm going to give you a list of descriptions. Each one is seperated by ====== on either side. They will vary in length, so make sure to only seperate when you see ======. Sort them into lists by shared content. MAKE SURE EACH DESCRIPTOR IS IN ONLY ONE LIST. Generate only the list with each list seperated by ====== with the elements seperated by ~~~~~~. Try to do around 4 groups, but a little more or less is ok.",
    },
    describe: { model: 'gpt-4-vision-preview', maxTokens: 2048, temp: 0, prompt: 'Describe these images in 3-5 words' },
};

let lastCall = '';
let lastResp = '';
/**
 * Calls the OpenAI API.
 *
 * @param inputText Text to process
 * @returns AI Output
 */
const gptAPICall = async (inputTextIn: string, callType: GPTCallType, prompt?: any) => {
    const inputText = callType === GPTCallType.SUMMARY ? inputTextIn + '.' : inputTextIn;
    const opts: GPTCallOpts = callTypeMap[callType];
    if (lastCall === inputText) return lastResp;
    try {
        const configuration: ClientOptions = {
            apiKey: process.env.OPENAI_KEY,
            dangerouslyAllowBrowser: true,
        };
        lastCall = inputText;
        const openai = new OpenAI(configuration);

        const usePrompt = prompt ? opts.prompt + prompt : opts.prompt;
        const messages: ChatCompletionMessageParam[] = [
            { role: 'system', content: usePrompt },
            { role: 'user', content: inputText },
        ];

        const response = await openai.chat.completions.create({
            model: opts.model,
            messages: messages,
            temperature: opts.temp,
            max_tokens: opts.maxTokens,
        });
        lastResp = response.choices[0].message.content ?? '';
        return lastResp;
    } catch (err) {
        console.log(err);
        return 'Error connecting with API.';
    }
};

const gptImageLabel = async (imgUrl: string): Promise<string> => {
    try {
        const configuration: ClientOptions = {
            apiKey: process.env.OPENAI_KEY,
            dangerouslyAllowBrowser: true,
        };

        const openai = new OpenAI(configuration);
        const response = await openai.chat.completions.create({
            model: 'gpt-4o',
            messages: [
                {
                    role: 'user',
                    content: [
                        { type: 'text', text: 'Describe this image in 3-5 words' },
                        {
                            type: 'image_url',
                            image_url: {
                                url: `${imgUrl}`,
                            },
                        },
                    ],
                },
            ],
        });
        if (response.choices[0].message.content) {
            return response.choices[0].message.content;
        } else {
            return ':(';
        }
    } catch (err) {
        console.log(err);
        return 'Error connecting with API';
    }
};

const gptImageCall = async (prompt: string, n?: number) => {
    try {
        const configuration: ClientOptions = {
            apiKey: process.env.OPENAI_KEY,
            dangerouslyAllowBrowser: true,
        };

        const openai = new OpenAI(configuration);
        const response = await openai.images.generate({
            prompt: prompt,
            n: n ?? 1,
            size: '1024x1024',
        });
        return response.data.map((data: any) => data.url);
        // return response.data.data[0].url;
    } catch (err) {
        console.error(err);
    }
    return undefined;
};

export { gptAPICall, gptImageCall, gptImageLabel, GPTCallType };