import SparkApi
from prompt import *
from tqdm import tqdm

# 以下密钥信息从控制台获取
appid = "f0f73de5"  # 填写控制台中获取的 APPID 信息
api_secret = "YzkyYjQwMTU0MGZjMmUzMGE1Y2ZjYzBk"  # 填写控制台中获取的 APISecret 信息
api_key = "5773f6f95563708de994d17b7ea5d414"  # 填写控制台中获取的 APIKey 信息

# 用于配置大模型版本，默认“general/generalv2”
domain = "4.0Ultra"  # v1.5版本
# domain = "generalv2"    # v2.0版本
# 云端环境的服务地址
Spark_url = "wss://spark-api.xf-yun.com/v4.0/chat"  # v1.5环境的地址
# Spark_url = "ws://spark-api.xf-yun.com/v2.1/chat"  # v2.0环境的地址


text = []


# length = 0

def getText(role, content):
    jsoncon = {}
    jsoncon["role"] = role
    jsoncon["content"] = content
    text.append(jsoncon)
    return text


def getlength(text):
    length = 0
    for content in text:
        temp = content["content"]
        leng = len(temp)
        length += leng
    return length


def checklen(text):
    while (getlength(text) > 8000):
        del text[0]
    return text


if __name__ == '__main__':
    text.clear()
    file_name = 'train3.jsonl'
    conversations = []
    for i in tqdm(range(200)):
        Input = prompt(random.randint(0, 16))
        question = checklen(getText("user", Input))
        SparkApi.answer = ""
        SparkApi.main(appid, api_key, api_secret, Spark_url, domain, question)
        getText("assistant", SparkApi.answer)
        conversations.append(ChatGLM3_6B(SparkApi.answer))
        for item in conversations:
            save_jsonl(item, file_name)
        conversations.clear()