Reconfiguration of the basic multi-agent architecture.

QueryEngine/llms/__init__.py

@@ -0,0 +1,10 @@
+"""
+LLM调用模块
+支持多种大语言模型的统一接口
+"""
+
+from .base import BaseLLM
+from .deepseek import DeepSeekLLM
+from .openai_llm import OpenAILLM
+
+__all__ = ["BaseLLM", "DeepSeekLLM", "OpenAILLM"]

QueryEngine/llms/base.py

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+"""
+LLM基础抽象类
+定义所有LLM实现需要遵循的接口标准
+"""
+
+from abc import ABC, abstractmethod
+from typing import Optional, Dict, Any
+
+
+class BaseLLM(ABC):
+    """LLM基础抽象类"""
+    
+    def __init__(self, api_key: str, model_name: Optional[str] = None):
+        """
+        初始化LLM客户端
+        
+        Args:
+            api_key: API密钥
+            model_name: 模型名称，如果不指定则使用默认模型
+        """
+        self.api_key = api_key
+        self.model_name = model_name
+        
+    @abstractmethod
+    def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """
+        调用LLM生成回复
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户输入
+            **kwargs: 其他参数，如temperature、max_tokens等
+            
+        Returns:
+            LLM生成的回复文本
+        """
+        pass
+    
+    @abstractmethod
+    def get_default_model(self) -> str:
+        """
+        获取默认模型名称
+        
+        Returns:
+            默认模型名称
+        """
+        pass
+    
+    def validate_response(self, response: str) -> str:
+        """
+        验证和清理响应内容
+        
+        Args:
+            response: LLM原始响应
+            
+        Returns:
+            清理后的响应内容
+        """
+        if response is None:
+            return ""
+        return response.strip()

QueryEngine/llms/deepseek.py

@@ -0,0 +1,95 @@
+"""
+DeepSeek LLM实现
+使用DeepSeek API进行文本生成
+"""
+
+import os
+from typing import Optional, Dict, Any
+from openai import OpenAI
+from .base import BaseLLM
+
+
+class DeepSeekLLM(BaseLLM):
+    """DeepSeek LLM实现类"""
+    
+    def __init__(self, api_key: Optional[str] = None, model_name: Optional[str] = None):
+        """
+        初始化DeepSeek客户端
+        
+        Args:
+            api_key: DeepSeek API密钥，如果不提供则从环境变量读取
+            model_name: 模型名称，默认使用deepseek-chat
+        """
+        if api_key is None:
+            api_key = os.getenv("DEEPSEEK_API_KEY")
+            if not api_key:
+                raise ValueError("DeepSeek API Key未找到！请设置DEEPSEEK_API_KEY环境变量或在初始化时提供")
+        
+        super().__init__(api_key, model_name)
+        
+        # 初始化OpenAI客户端，使用DeepSeek的endpoint
+        self.client = OpenAI(
+            api_key=self.api_key,
+            base_url="https://api.deepseek.com"
+        )
+        
+        self.default_model = model_name or self.get_default_model()
+    
+    def get_default_model(self) -> str:
+        """获取默认模型名称"""
+        return "deepseek-chat"
+    
+    def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """
+        调用DeepSeek API生成回复
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户输入
+            **kwargs: 其他参数，如temperature、max_tokens等
+            
+        Returns:
+            DeepSeek生成的回复文本
+        """
+        try:
+            # 构建消息
+            messages = [
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_prompt}
+            ]
+            
+            # 设置默认参数
+            params = {
+                "model": self.default_model,
+                "messages": messages,
+                "temperature": kwargs.get("temperature", 0.7),
+                "max_tokens": kwargs.get("max_tokens", 4000),
+                "stream": False
+            }
+            
+            # 调用API
+            response = self.client.chat.completions.create(**params)
+            
+            # 提取回复内容
+            if response.choices and response.choices[0].message:
+                content = response.choices[0].message.content
+                return self.validate_response(content)
+            else:
+                return ""
+                
+        except Exception as e:
+            print(f"DeepSeek API调用错误: {str(e)}")
+            raise e
+    
+    def get_model_info(self) -> Dict[str, Any]:
+        """
+        获取当前模型信息
+        
+        Returns:
+            模型信息字典
+        """
+        return {
+            "provider": "DeepSeek",
+            "model": self.default_model,
+            "api_base": "https://api.deepseek.com"
+        }

QueryEngine/llms/openai_llm.py

@@ -0,0 +1,90 @@
+"""
+OpenAI LLM实现
+使用OpenAI API进行文本生成
+"""
+
+import os
+from typing import Optional, Dict, Any
+from openai import OpenAI
+from .base import BaseLLM
+
+
+class OpenAILLM(BaseLLM):
+    """OpenAI LLM实现类"""
+    
+    def __init__(self, api_key: Optional[str] = None, model_name: Optional[str] = None):
+        """
+        初始化OpenAI客户端
+        
+        Args:
+            api_key: OpenAI API密钥，如果不提供则从环境变量读取
+            model_name: 模型名称，默认使用gpt-4o-mini
+        """
+        if api_key is None:
+            api_key = os.getenv("OPENAI_API_KEY")
+            if not api_key:
+                raise ValueError("OpenAI API Key未找到！请设置OPENAI_API_KEY环境变量或在初始化时提供")
+        
+        super().__init__(api_key, model_name)
+        
+        # 初始化OpenAI客户端
+        self.client = OpenAI(api_key=self.api_key)
+        self.default_model = model_name or self.get_default_model()
+    
+    def get_default_model(self) -> str:
+        """获取默认模型名称"""
+        return "gpt-4o-mini"
+    
+    def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
+        """
+        调用OpenAI API生成回复
+        
+        Args:
+            system_prompt: 系统提示词
+            user_prompt: 用户输入
+            **kwargs: 其他参数，如temperature、max_tokens等
+            
+        Returns:
+            OpenAI生成的回复文本
+        """
+        try:
+            # 构建消息
+            messages = [
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_prompt}
+            ]
+            
+            # 设置默认参数
+            params = {
+                "model": self.default_model,
+                "messages": messages,
+                "temperature": kwargs.get("temperature", 0.7),
+                "max_tokens": kwargs.get("max_tokens", 4000)
+            }
+            
+            # 调用API
+            response = self.client.chat.completions.create(**params)
+            
+            # 提取回复内容
+            if response.choices and response.choices[0].message:
+                content = response.choices[0].message.content
+                return self.validate_response(content)
+            else:
+                return ""
+                
+        except Exception as e:
+            print(f"OpenAI API调用错误: {str(e)}")
+            raise e
+    
+    def get_model_info(self) -> Dict[str, Any]:
+        """
+        获取当前模型信息
+        
+        Returns:
+            模型信息字典
+        """
+        return {
+            "provider": "OpenAI",
+            "model": self.default_model,
+            "api_base": "https://api.openai.com"
+        }