diff --git a/mcp_server.py b/mcp_server.py index 8508f6ca..6b12661a 100644 --- a/mcp_server.py +++ b/mcp_server.py @@ -2005,12 +2005,12 @@ class MCPAgentIntegrated: # 添加当前用户问题 messages.append({"role": "user", "content": user_query}) - # 使用 Kimi 思考模型 + # 使用 Kimi 思考模型(实际是 deepseek,max_tokens 限制 8192) response = self.kimi_client.chat.completions.create( model=self.kimi_model, messages=messages, - temperature=1.0, # Kimi 推荐 - max_tokens=32768, # 足够容纳 reasoning_content + temperature=1.0, + max_tokens=8192, ) choice = response.choices[0] @@ -2085,7 +2085,7 @@ class MCPAgentIntegrated: model=self.deepmoney_model, messages=messages, temperature=0.7, - max_tokens=32784, + max_tokens=8192, ) summary = response.choices[0].message.content @@ -2279,7 +2279,7 @@ class MCPAgentIntegrated: model="kimi-k2-turbo-preview", # 使用非思考模型,更快 messages=messages, temperature=0.7, - max_tokens=32768, # 增加 token 限制以支持图表配置 + max_tokens=8192, ) summary = response.choices[0].message.content @@ -2366,7 +2366,7 @@ class MCPAgentIntegrated: model=self.deepmoney_model, messages=messages, temperature=0.3, - max_tokens=32768, + max_tokens=8192, ) title = response.choices[0].message.content.strip() @@ -2507,7 +2507,7 @@ class MCPAgentIntegrated: model=self.deepmoney_model, messages=messages, temperature=0.7, - max_tokens=32768, + max_tokens=8192, ) plan_content = fallback_response.choices[0].message.content @@ -2703,7 +2703,7 @@ class MCPAgentIntegrated: model="kimi-k2-turbo-preview", messages=messages, temperature=0.7, - max_tokens=32768, + max_tokens=8192, stream=True, # 启用流式输出 )