init

test010.py

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+from openai import OpenAI
+import os
+
+# 初始化OpenAI客户端
+client = OpenAI(
+    # 如果没有配置环境变量，请用百炼API Key替换：api_key="sk-xxx"
+    api_key = "sk-01d13a39e09844038322108ecdbd1bbc",
+    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
+)
+
+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
+
+# 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": "这道题怎么解答？注意：这道题是初中中考题，使用初中生的层次进行解答。"},
+            ],
+        },
+    ],
+    stream=True,
+    # 解除以下注释会在最后一个chunk返回Token使用量
+    # stream_options={
+    #     "include_usage": 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")
+# print(answer_content)