76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
from openai import OpenAI
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import os
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# 初始化OpenAI客户端
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client = OpenAI(
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api_key="sk-01d13a39e09844038322108ecdbd1bbc",
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
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)
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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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def 几何预处理(text):
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# 坐标系标准化
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建立参考坐标系(以最长边为x轴基准)
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计算各点相对坐标(保留2位小数)
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# 约束显式化
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将"直角在上方"转换为： if 角C是直角：
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设置C.y = max(A.y, B.y) + offset
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添加约束 Angle(A,C,B)=90°
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# 指令优化
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移除所有文字描述
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输出结构化指令元组： return [ ('CreatePoint', 'A', (x1,y1)), ('SetConstraint', 'Perpendicular', ['AC','BC']), ('VisualHint', 'C', {'color':'red','size':8}) ]
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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", # 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/math.jpg"
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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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# print(answer_content)
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