'commit'

dsLightRag/Test/TestGoogleGemini.py

@@ -4,66 +4,84 @@ import requests
 
 from Config.Config import GPTNB_API_KEY
 
-# API配置
-API_URL = "https://goapi.gptnb.ai/v1/chat/completions"
-
-# 请求头
-headers = {
+class ModelInteractor:
+    def __init__(self,  api_url="https://goapi.gptnb.ai/v1/chat/completions"):
+        self.api_url = api_url
+        self.headers = {
             "Content-Type": "application/json",
             "Authorization": f"Bearer {GPTNB_API_KEY}"
         }
     
-# 请求体 - 添加stream: true参数启用流式响应
+    def stream_request(self, model, prompt, temperature=0.7):
+        """
+        发送流式请求到模型API
+        
+        参数:
+        - model: 模型名称
+        - prompt: 用户提示词
+        - temperature: 温度参数，控制输出的随机性
+        
+        返回:
+        - 无返回值，直接打印流式响应
+        """
         payload = {
-    "model": "gemini-2.5-pro",
+            "model": model,
             "messages": [{
                 "role": "user",
-        "content": "请详细介绍一下你自己，分成几个段落来说明"
+                "content": prompt
             }],
-    "temperature": 0.7,
-    "stream": True  # 启用流式响应
+            "temperature": temperature,
+            "stream": True
         }
         
         try:
-    # 发送POST请求，设置stream=True
             response = requests.post(
-        API_URL,
-        headers=headers,
+                self.api_url,
+                headers=self.headers,
                 data=json.dumps(payload),
                 stream=True,
-        timeout=30  # 设置超时时间
+                timeout=30
             )
-    response.raise_for_status()  # 检查请求是否成功
+            response.raise_for_status()
             
-    # 逐块处理响应
+            print(f"使用模型 {model} 的流式响应内容: ")
             for chunk in response.iter_content(chunk_size=None):
                 if chunk:
-            # 解码chunk
                     chunk_data = chunk.decode('utf-8', errors='replace')
                     
-            # 处理可能的多部分响应
                     for line in chunk_data.splitlines():
                         line = line.strip()
                         if not line:
                             continue
                             
-                # 检查是否结束
                         if line == 'data: [DONE]':
-                    break
+                            print("\n流式响应结束")
+                            return
                             
-                # 去除可能的前缀
                         if line.startswith('data: '):
                             line = line[6:]
                             
-                # 解析JSON
+                        try:
                             data = json.loads(line)
-                # 提取文本内容
                             if 'choices' in data and len(data['choices']) > 0:
                                 delta = data['choices'][0].get('delta', {})
                                 content = delta.get('content', '')
                                 if content and content != '\n':
-                        # 实时输出内容，不换行
                                     print(content, end='', flush=True)
+                        except json.JSONDecodeError as e:
+                            print(f"[调试] JSON解析错误: {e}, 内容: {line}")
                             
         except requests.exceptions.RequestException as e:
             print(f"请求发生错误: {e}")
+
+# 示例使用
+if __name__ == "__main__":
+    # 创建模型交互器实例
+    interactor = ModelInteractor()
+    
+    # 使用不同的模型和提示词
+    model_name = "gemini-2.5-pro"
+    prompt_text = "请详细介绍一下你自己，分成几个段落来说明"
+    
+    # 发送流式请求
+    interactor.stream_request(model_name, prompt_text)