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from openai import OpenAI
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# 一、调用OCR整理出试题
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client = OpenAI(
api_key='sk-f6da0c787eff4b0389e4ad03a35a911f',
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
prompt = "请提取图片中的试题"
completion = client.chat.completions.create(
model="qwen-vl-ocr-latest",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": "https://ylt.oss-cn-hangzhou.aliyuncs.com/HuangHai/Test/Source.jpg",
# 输入图像的最小像素阈值小于该值图像会按原比例放大直到总像素大于min_pixels
"min_pixels": 28 * 28 * 4,
# 输入图像的最大像素阈值超过该值图像会按原比例缩小直到总像素低于max_pixels
"max_pixels": 28 * 28 * 8192
},
# qwen-vl-ocr-latest支持在以下text字段中传入Prompt若未传入则会使用默认的PromptPlease output only the text content from the image without any additional descriptions or formatting.
# 如调用qwen-vl-ocr-1028模型会使用固定PromptRead all the text in the image.不支持用户在text中传入自定义Prompt
{"type": "text",
"text": prompt},
]
}
])
print(completion.choices[0].message.content)
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# 二、再次调用大模型整理内容
prompt = """
我将提供一份markdown格式的试卷请帮我整理出每道题的以下内容
1. 题目序号
2. 题目内容自动识别并添加$$$包裹数学公式
3. 选项如果有
4. 答案
5. 解析
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要求
- 一道题一道题输出不要使用表格
- 自动检测数学表达式并用$$$正确包裹
- 确保公式中的特殊字符正确转义
- 除题目内容外不要输出其它无关信息
内容如下
"""
text = completion.choices[0].message.content
prompt += text
completion = client.chat.completions.create(
model="deepseek-v3",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user",
"content": prompt},
],
)
print(completion.choices[0].message.content)
# 将上面的返回内容写入到文件 整理后的结果.md 中
with open("Res/整理后的结果.md", "w", encoding="utf-8") as f:
f.write(completion.choices[0].message.content)
print("保存成功!")