80 lines
2.8 KiB
Python
80 lines
2.8 KiB
Python
from zhipuai import ZhipuAI
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client = ZhipuAI(api_key="78dc1dfe37e04f29bd4ca9a49858a969.gn7TIZTfzpY35nx9") # 填写您自己的APIKey
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from utils.image_utils import encode_image
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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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base64_image = encode_image(r"D:\ocr\QQ截图20250814093022.jpg")
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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，请结合题干内容对图形进行描述，只要描述不需要任何解释。
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3、如果图片中有几何图形，识别图片中的几何图形，如三角形、圆形、矩形等。请结合题干内容对图形进行详细描述，包括形状、大小、位置关系等。
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3、如果图片中是坐标系，分析抛物线的开口方向和经过的象限，并详细描述。识别图片中的坐标系类型，如直角坐标系、极坐标系等。
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4、要以markdown格式输出
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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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completion = client.chat.completions.create(
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model="glm-4.1v-thinking-flash", # 填写需要调用的模型名称
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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": "text",
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"text": prompt
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},
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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/math.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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]
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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(response.choices[0].message) |