diff --git a/Wargame/common/llmcaller.py b/Wargame/common/llmcaller.py
new file mode 100644
index 0000000..5756114
--- /dev/null
+++ b/Wargame/common/llmcaller.py
@@ -0,0 +1,159 @@
+import os
+from typing import Optional, Dict, Any
+import requests
+import json
+
+
+class LLMCaller:
+    """统一的LLM调用类，支持多种模型服务"""
+    
+    def __init__(self, provider: str, api_key: Optional[str] = None, 
+                 base_url: Optional[str] = None, model: Optional[str] = None):
+        """
+        初始化LLM调用器
+        
+        Args:
+            provider: 服务提供商 ('deepseek', 'claude', 'openai', 'qwen', 'ollama')
+            api_key: API密钥（ollama不需要）
+            base_url: API基础URL（可选，用于自定义端点）
+            model: 模型名称（可选，使用默认值）
+        """
+        self.provider = provider.lower()
+        self.api_key = api_key or os.environ.get(f"{provider.upper()}_API_KEY")
+        
+        # 默认配置
+        self.configs = {
+            'deepseek': {
+                'base_url': base_url or 'https://api.deepseek.com/v1',
+                'model': model or 'deepseek-chat',
+                'endpoint': '/chat/completions'
+            },
+            'claude': {
+                'base_url': base_url or 'https://api.anthropic.com/v1',
+                'model': model or 'claude-3-5-sonnet-20241022',
+                'endpoint': '/messages'
+            },
+            'openai': {
+                'base_url': base_url or 'https://api.openai.com/v1',
+                'model': model or 'gpt-4o-mini',
+                'endpoint': '/chat/completions'
+            },
+            'qwen': {
+                'base_url': base_url or 'https://dashscope.aliyuncs.com/compatible-mode/v1',
+                'model': model or 'qwen-plus',
+                'endpoint': '/chat/completions'
+            },
+            'ollama': {
+                'base_url': base_url or 'http://localhost:11434',
+                'model': model or 'llama3.2',
+                'endpoint': '/api/chat'
+            }
+        }
+        
+        if self.provider not in self.configs:
+            raise ValueError(f"不支持的provider: {self.provider}")
+        
+        self.config = self.configs[self.provider]
+    
+    def call(self, system_prompt: str, user_prompt: str, model: Optional[str] = None, **kwargs) -> str:
+        """
+        调用LLM
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户提示词
+            model: 模型名称（可选，不传则使用默认模型）
+            **kwargs: 其他参数（temperature, max_tokens等）
+        
+        Returns:
+            LLM的响应文本
+        """
+        # 如果传入了model参数，临时使用该模型
+        original_model = self.config['model']
+        if model:
+            self.config['model'] = model
+        
+        try:
+            if self.provider == 'claude':
+                return self._call_claude(system_prompt, user_prompt, **kwargs)
+            elif self.provider == 'ollama':
+                return self._call_ollama(system_prompt, user_prompt, **kwargs)
+            else:
+                return self._call_openai_compatible(system_prompt, user_prompt, **kwargs)
+        finally:
+            # 恢复原始模型设置
+            self.config['model'] = original_model
+    
+    def _call_openai_compatible(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """调用OpenAI兼容的API（OpenAI, DeepSeek, Qwen）"""
+        headers = {
+            'Content-Type': 'application/json',
+            'Authorization': f'Bearer {self.api_key}'
+        }
+        
+        data = {
+            'model': self.config['model'],
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_prompt}
+            ],
+            **kwargs
+        }
+        
+        response = requests.post(
+            f"{self.config['base_url']}{self.config['endpoint']}",
+            headers=headers,
+            json=data
+        )
+        response.raise_for_status()
+        
+        return response.json()['choices'][0]['message']['content']
+    
+    def _call_claude(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """调用Claude API"""
+        headers = {
+            'Content-Type': 'application/json',
+            'X-API-Key': self.api_key,
+            'anthropic-version': '2023-06-01'
+        }
+        
+        data = {
+            'model': self.config['model'],
+            'system': system_prompt,
+            'messages': [
+                {'role': 'user', 'content': user_prompt}
+            ],
+            'max_tokens': kwargs.get('max_tokens', 4096),
+            **{k: v for k, v in kwargs.items() if k != 'max_tokens'}
+        }
+        
+        response = requests.post(
+            f"{self.config['base_url']}{self.config['endpoint']}",
+            headers=headers,
+            json=data
+        )
+        response.raise_for_status()
+        
+        return response.json()['content'][0]['text']
+    
+    def _call_ollama(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """调用Ollama API"""
+        data = {
+            'model': self.config['model'],
+            'messages': [
+                {'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': user_prompt}
+            ],
+            'stream': False,
+            **kwargs
+        }
+        
+        response = requests.post(
+            f"{self.config['base_url']}{self.config['endpoint']}",
+            json=data
+        )
+        response.raise_for_status()
+        
+        return response.json()['message']['content']
+
+