import OpenAI from "openai";
import storage from 'node-persist'
import { sendMsg } from "../lib/qq";
import prompt from './prompt.txt'

await storage.init();
storage.clear();

const client = new OpenAI({
    baseURL: process.env.OPENAI_BASE_URL,
    apiKey: process.env.OPENAI_API_KEY,
    // logLevel: "debug"
})

const tools = [{
    type: "function" as const,
    name: "send_msg",
    description: "Send a message to the user. Always use this to respond to the user.",
    parameters: {
        type: "object",
        properties: {
            text: { type: "string", description: "The message content sent to the user through QQ." }
        },
        required: ["text"],
        additionalProperties: false
    },
    strict: true
}]

/**
 * 
 * @param input 提问
 * @param target_id 用户 QQ 号
 */
export async function chat(input: string, target_id: string) {
    const chatHistoryKey = `chat_history_${target_id}`;
    let chatHistory: OpenAI.Responses.ResponseInput = await storage.getItem(chatHistoryKey) || [];

    // 添加新输入到对话历史
    chatHistory.push({ role: "user", content: input });

    // 保存更新后的对话历史
    console.log(`[LLM] 使用对话, 历史：`, chatHistory);

    await storage.setItem(chatHistoryKey, chatHistory);

    const response = await client.responses.create({
        model: process.env.CHAT_MODEL || "gpt-5-nano",
        instructions: prompt,
        reasoning: { effort: 'minimal' },
        input: chatHistory,
        tools
    });

    await storage.setItem(chatHistoryKey, chatHistory);

    // 继续调用工具，直到没有工具调用为止

    await toolUseCycle(response.output);

    async function toolUseCycle(outputArr: OpenAI.Responses.ResponseOutputItem[]) {
        chatHistory.push(...outputArr);
        const functionCalls = (outputArr ?? []).filter(item => item.type === 'function_call');
        console.log("进入 toolUseCycle, with functionCalls", functionCalls.length, "个");
        console.log(JSON.stringify(chatHistory, null, 2));

        if (functionCalls.length == 0) {
            let lastMessage = outputArr.at(-1);
            if (!lastMessage) return
            if (lastMessage.type != 'message') return
            if (lastMessage.role != 'assistant') return

            const msg = lastMessage.content.map(c => c.type == 'output_text' ? c.text : '').join('');
            if (msg.trim().length > 0) {
                // 结束，发送最后的消息
                sendMsg(msg, target_id);
            }
            return
        }
        for (const item of functionCalls ?? []) {
            if (item.name === "send_msg") {
                console.log(item.arguments);

                const { text } = JSON.parse(item.arguments);
                sendMsg(text, target_id);

                chatHistory.push({ type: "function_call_output", call_id: item.call_id, output: "OK" });
            }
        }
        await storage.setItem(chatHistoryKey, chatHistory);

        const response = await client.responses.create({
            model: process.env.CHAT_MODEL || "gpt-5-nano",
            instructions: prompt,
            reasoning: { effort: 'minimal' },
            input: chatHistory,
            tools
        });

        toolUseCycle(response.output);
    }
}

export async function resetChat(target_id: string) {
    const chatHistoryKey = `chat_history_${target_id}`;
    await storage.removeItem(chatHistoryKey);
    sendMsg("已为你重置对话历史。", target_id);
}