from flask import Flask, jsonify
from flask import request
import time
import concurrent.futures
import requests
import socket


def get_host_ip():
    """
    查询本机ip地址
    :return: ip
    """
    try:
        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
        s.connect(('8.8.8.8', 80))
        ip = s.getsockname()[0]
    finally:
        s.close()

    return ip

chatgpt_url_predict = "http://{}:12000/predict".format(str(get_host_ip()))
chatgpt_url_search = "http://{}:12000/search".format(str(get_host_ip()))
# prompt = "<|role|>user<|says|>{}<|end|>\n<|role|>assistant<|says|>"
prompt = "<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n"

app = Flask(__name__)
app.config["JSON_AS_ASCII"] = False

def dialog_line_parse(url, text):
    """
    将数据输入模型进行分析并输出结果
    :param url: 模型url
    :param text: 进入模型的数据
    :return: 模型返回结果
    """

    response = requests.post(
        url,
        json=text,
        timeout=1000
    )
    if response.status_code == 200:
        return response.json()
    else:
        # logger.error(
        #     "【{}】 Failed to get a proper response from remote "
        #     "server. Status Code: {}. Response: {}"
        #     "".format(url, response.status_code, response.text)
        # )
        print("【{}】 Failed to get a proper response from remote "
            "server. Status Code: {}. Response: {}"
            "".format(url, response.status_code, response.text))
        print(text)
        return []


def request_api_chatgpt(prompt):
    '''
    {
        "content": "<|role|>user<|says|>任务：生成目录\n为论文题目“基于“六经”伏邪理论治疗过敏性紫癜性肾炎初探”生成中文目录，要求只有一级标题，二级标题，一级标题使用中文数字 例如一、xxx；二级标题使用阿拉伯数字 例如1.1 xxx一级标题生成5个；每个一级标题包含4-7个二级标题<|end|>\n<|role|>assistant<|says|>",
        "model": "openbuddy-qwen2.5llamaify-7b_train_11_prompt_mistral_gpt_xiaobiaot_real_paper_2",
        "top_p": 1,
        "temperature": 0
    }
    :param prompt:
    :return:
    '''
    data = {
        "content": prompt,
        "model": "gpt-4-turbo",
        "top_p": 0.95,
        "temperature": 0.7
    }
    response = requests.post(
        chatgpt_url_predict,
        json=data,
        timeout=100000
    )
    if response.status_code == 200:
        return response.json()
    else:
        # logger.error(
        #     "【{}】 Failed to get a proper response from remote "
        #     "server. Status Code: {}. Response: {}"
        #     "".format(url, response.status_code, response.text)
        # )
        print("Failed to get a proper response from remote "
              "server. Status Code: {}. Response: {}"
              "".format(response.status_code, response.text))
        return {}


def uuid_search(uuid):
    data = {
        "id": uuid
    }
    response = requests.post(
        chatgpt_url_search,
        json=data,
        timeout=100000
    )
    if response.status_code == 200:
        return response.json()
    else:
        # logger.error(
        #     "【{}】 Failed to get a proper response from remote "
        #     "server. Status Code: {}. Response: {}"
        #     "".format(url, response.status_code, response.text)
        # )
        print("Failed to get a proper response from remote "
              "server. Status Code: {}. Response: {}"
              "".format(response.status_code, response.text))
        return {}


def uuid_search_mp(results):
    results_list = [""] * len(results)
    while True:
        tiaochu_bool = True

        for i in results_list:
            if i == "":
                tiaochu_bool = False
                break

        if tiaochu_bool == True:
            break

        for i in range(len(results)):
            uuid = results[i]["texts"]["id"]

            result = uuid_search(uuid)
            if result["code"] == 200:
                results_list[i] = result["text"]
        time.sleep(3)
    return results_list


def get_multiple_urls(urls):
    input_values = []

    for i in urls:
        input_values.append(i[1])
    with concurrent.futures.ThreadPoolExecutor() as executor:
        # 使用map方法并发地调用worker_function
        results = list(executor.map(request_api_chatgpt, input_values))

    with concurrent.futures.ThreadPoolExecutor() as executor:
        # 使用map方法并发地调用worker_function
        results = list(executor.map(uuid_search_mp, [results]))

    return_list = []
    for i in results[0]:
        data = {
            "code": 200,
            "data": i
        }
        return_list.append(data)
    return return_list


@app.route("/articles_directory", methods=["POST"])
def articles_directory():
    text = request.json["texts"]  # 获取用户query中的文本 例如"I love you"
    nums = request.json["nums"]
    text = prompt.format(text)
    nums = int(nums)

    input_data = []
    for i in range(nums):
        # input_data.append([i, chatgpt_url, {"texts": text_sentence[i]}])
        input_data.append([i, text])

    results = get_multiple_urls(input_data)

    return jsonify(results)  # 返回结果

if __name__ == "__main__":
    app.run(debug=False, host='0.0.0.0', port=18000)