from openai import OpenAI

from Config.Config import ALY_LLM_BASE_URL, ALY_LLM_API_KEY

# 初始化OpenAI客户端
client = OpenAI(
    api_key=ALY_LLM_API_KEY,
    base_url=ALY_LLM_BASE_URL
)

reasoning_content = ""  # 定义完整思考过程
answer_content = ""  # 定义完整回复
is_answering = False  # 判断是否结束思考过程并开始回复

prompt = """
你是一个严谨的数学助手，请将以下初中几何题进行描述，需包含：
【1】有哪些主体元素？比如 直角等腰三角形，等腰三角形，直角三角形，都有哪些，先列举大的，再列举小的。
【2】这些主体元素的位置关系是什么样的，比如AB是斜边，角C是90度角，AB是水平的，适合做坐标系的X轴。
【3】除主体元素外，其它的辅助元素有哪些？都应该如何描述清楚？
"""
# 创建聊天完成请求
completion = client.chat.completions.create(
    model="qvq-max",  # 此处以 qvq-max 为例，可按需更换模型名称
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://dsideal.obs.cn-north-1.myhuaweicloud.com/wb/math.jpg"
                    },
                },
                {"type": "text",
                 "text": prompt},
            ],
        },
    ],
    stream=True,
)

print("\n" + "=" * 20 + "思考过程" + "=" * 20 + "\n")

for chunk in completion:
    # 如果chunk.choices为空，则打印usage
    if not chunk.choices:
        print("\nUsage:")
        print(chunk.usage)
    else:
        delta = chunk.choices[0].delta
        # 打印思考过程
        if hasattr(delta, 'reasoning_content') and delta.reasoning_content != None:
            print(delta.reasoning_content, end='', flush=True)
            reasoning_content += delta.reasoning_content
        else:
            # 开始回复
            if delta.content != "" and is_answering is False:
                print("\n" + "=" * 20 + "完整回复" + "=" * 20 + "\n")
                is_answering = True
            # 打印回复过程
            print(delta.content, end='', flush=True)
            answer_content += delta.content

# print("=" * 20 + "完整思考过程" + "=" * 20 + "\n")
# print(reasoning_content)
# print("=" * 20 + "完整回复" + "=" * 20 + "\n")
# 保存成QvqResult.txt
with open("QvqResult.txt", "w", encoding='utf-8') as f:
    f.write(answer_content)
print("试题解析文本保存成功！")