78 lines
2.7 KiB
Python
78 lines
2.7 KiB
Python
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from openai import OpenAI
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from utils.image_utils import encode_image
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# 初始化OpenAI客户端
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client = OpenAI(
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api_key="sk-f6da0c787eff4b0389e4ad03a35a911f",
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
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)
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base64_image = encode_image(r"D:\ocr\QQ截图20250814093022.jpg")
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reasoning_content = "" # 定义完整思考过程
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answer_content = "" # 定义完整回复
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is_answering = False # 判断是否结束思考过程并开始回复
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prompt = """
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你是一个初中数学图片的描述专家，请将图片中的内容转换为文本。
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1、注意数学公式需要用latex格式输出。注意只输出文本内容，不要输出任何解释。
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2、如果图片中有图形，请根据题干对图形进行描述，只要描述不需要任何解释。
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3、如果图片中是坐标系，一定要说明抛物线的开口和抛物线经过了几个象限。
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4、要以markdown格式输出，注意latex格式两边要加$
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输出格式为
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【题干】
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【图形描述】
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"""
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# 创建聊天完成请求
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completion = client.chat.completions.create(
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model="qvq-max-latest", # 此处以 qvq-max 为例，可按需更换模型名称
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "image_url",
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"image_url": {
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# "url": "https://dsideal.obs.cn-north-1.myhuaweicloud.com/wb/img10.jpg"
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'url': f'data:image/jpeg;base64,{base64_image}'
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},
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},
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{"type": "text",
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"text": prompt},
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],
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},
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],
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stream=True,
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)
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print("\n" + "=" * 20 + "思考过程" + "=" * 20 + "\n")
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for chunk in completion:
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# 如果chunk.choices为空，则打印usage
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if not chunk.choices:
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print("\nUsage:")
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print(chunk.usage)
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else:
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delta = chunk.choices[0].delta
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# 打印思考过程
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if hasattr(delta, 'reasoning_content') and delta.reasoning_content != None:
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print(delta.reasoning_content, end='', flush=True)
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reasoning_content += delta.reasoning_content
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else:
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# 开始回复
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if delta.content != "" and is_answering is False:
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print("\n" + "=" * 20 + "完整回复" + "=" * 20 + "\n")
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is_answering = True
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# 打印回复过程
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print(delta.content, end='', flush=True)
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answer_content += delta.content
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# print("=" * 20 + "完整思考过程" + "=" * 20 + "\n")
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# print(reasoning_content)
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# print("=" * 20 + "完整回复" + "=" * 20 + "\n")
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# 保存成QvqResult.txt
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with open("QvqResult.txt", "w", encoding='utf-8') as f:
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f.write(answer_content)
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print("试题解析文本保存成功！")
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