重构模型管理和配置加载逻辑，支持多模态和推理模型，优化API密钥管理，改进前端模型选择和版本显示

models/__init__.py

@@ -1,13 +1,13 @@
 from .base import BaseModel
-from .claude import ClaudeModel
-from .gpt4o import GPT4oModel
+from .anthropic import AnthropicModel
+from .openai import OpenAIModel
 from .deepseek import DeepSeekModel
 from .factory import ModelFactory
 
 __all__ = [
     'BaseModel',
-    'ClaudeModel',
-    'GPT4oModel',
+    'AnthropicModel',
+    'OpenAIModel',
     'DeepSeekModel',
     'ModelFactory'
 ]

models/anthropic.py

@@ -3,7 +3,7 @@ import requests
 from typing import Generator
 from .base import BaseModel
 
-class ClaudeModel(BaseModel):
+class AnthropicModel(BaseModel):
     def get_default_system_prompt(self) -> str:
         return """You are an expert at analyzing questions and providing detailed solutions. When presented with an image of a question:
 1. First read and understand the question carefully
@@ -168,6 +168,11 @@ class ClaudeModel(BaseModel):
         # 获取系统提示词，确保包含语言设置
         system_prompt = self.system_prompt
         
+        # 根据language参数设置回复语言
+        language = self.language or '中文'
+        if not any(phrase in system_prompt for phrase in ['Please respond in', '请用', '使用', '回答']):
+            system_prompt = f"{system_prompt}\n\n请务必使用{language}回答，无论问题是什么语言。即使在分析图像时也请使用{language}回答。这是最重要的指令。"
+        
         payload = {
             'model': 'claude-3-7-sonnet-20250219',
             'stream': True,
@@ -191,7 +196,7 @@ class ClaudeModel(BaseModel):
                     },
                     {
                         'type': 'text',
-                        'text': "Please analyze this question and provide a detailed solution. If you see multiple questions, focus on solving them one at a time."
+                        'text': "请分析这个问题并提供详细的解决方案。如果你看到多个问题，请逐一解决。请务必使用中文回答。"
                     }
                 ]
             }]

models/base.py

@@ -2,9 +2,10 @@ from abc import ABC, abstractmethod
 from typing import Generator, Any
 
 class BaseModel(ABC):
-    def __init__(self, api_key: str, temperature: float = 0.7, system_prompt: str = None):
+    def __init__(self, api_key: str, temperature: float = 0.7, system_prompt: str = None, language: str = None):
         self.api_key = api_key
         self.temperature = temperature
+        self.language = language
         self.system_prompt = system_prompt or self.get_default_system_prompt()
 
     @abstractmethod

models/deepseek.py

@@ -105,9 +105,18 @@ class DeepSeekModel(BaseModel):
 
             client = OpenAI(**client_args)
 
+            # 检查系统提示词是否已包含语言设置指令
+            system_prompt = self.system_prompt
+            language = self.language or '中文'
+            if not any(phrase in system_prompt for phrase in ['Please respond in', '请用', '使用', '回答']):
+                system_prompt = f"{system_prompt}\n\n请务必使用{language}回答，无论问题是什么语言。即使在分析图像时也请使用{language}回答。"
+
             response = client.chat.completions.create(
                 model=self.get_model_identifier(),
                 messages=[{
+                    'role': 'system',
+                    'content': system_prompt
+                }, {
                     'role': 'user',
                     'content': f"Here's an image of a question to analyze: data:image/png;base64,{image_data}"
                 }],

models/factory.py

@@ -1,20 +1,102 @@
-from typing import Dict, Type
+from typing import Dict, Type, Any
+import json
+import os
+import importlib
 from .base import BaseModel
-from .claude import ClaudeModel
-from .gpt4o import GPT4oModel
-from .deepseek import DeepSeekModel
-from .mathpix import MathpixModel
+from .mathpix import MathpixModel  # MathpixModel仍然需要直接导入，因为它是特殊工具
 
 class ModelFactory:
-    _models: Dict[str, Type[BaseModel]] = {
-        'claude-3-7-sonnet-20250219': ClaudeModel,
-        'gpt-4o-2024-11-20': GPT4oModel,
-        'deepseek-reasoner': DeepSeekModel,
-        'mathpix': MathpixModel
-    }
+    # 模型基本信息，包含类型和特性
+    _models: Dict[str, Dict[str, Any]] = {}
+    _class_map: Dict[str, Type[BaseModel]] = {}
+    
+    @classmethod
+    def initialize(cls):
+        """从配置文件加载模型信息"""
+        try:
+            config_path = os.path.join(os.path.dirname(__file__), '..', 'config', 'models.json')
+            with open(config_path, 'r', encoding='utf-8') as f:
+                config = json.load(f)
+            
+            # 加载提供商信息和类映射
+            providers = config.get('providers', {})
+            for provider_id, provider_info in providers.items():
+                class_name = provider_info.get('class_name')
+                if class_name:
+                    # 从当前包动态导入模型类
+                    module = importlib.import_module(f'.{provider_id.lower()}', package=__package__)
+                    cls._class_map[provider_id] = getattr(module, class_name)
+            
+            # 加载模型信息
+            for model_id, model_info in config.get('models', {}).items():
+                provider_id = model_info.get('provider')
+                if provider_id and provider_id in cls._class_map:
+                    cls._models[model_id] = {
+                        'class': cls._class_map[provider_id],
+                        'is_multimodal': model_info.get('supportsMultimodal', False),
+                        'is_reasoning': model_info.get('isReasoning', False),
+                        'display_name': model_info.get('name', model_id),
+                        'description': model_info.get('description', '')
+                    }
+            
+            # 添加Mathpix模型（特殊工具模型）
+            cls._models['mathpix'] = {
+                'class': MathpixModel,
+                'is_multimodal': True,
+                'is_reasoning': False,
+                'display_name': 'Mathpix OCR',
+                'description': '文本提取工具，适用于数学公式和文本',
+                'is_ocr_only': True
+            }
+            
+            print(f"已从配置加载 {len(cls._models)} 个模型")
+        except Exception as e:
+            print(f"加载模型配置失败: {str(e)}")
+            cls._initialize_defaults()
+    
+    @classmethod
+    def _initialize_defaults(cls):
+        """初始化默认模型（当配置加载失败时）"""
+        print("使用默认模型配置")
+        # 导入所有模型类作为备份
+        from .anthropic import AnthropicModel
+        from .openai import OpenAIModel 
+        from .deepseek import DeepSeekModel
+        
+        cls._models = {
+            'claude-3-7-sonnet-20250219': {
+                'class': AnthropicModel,
+                'is_multimodal': True,
+                'is_reasoning': True,
+                'display_name': 'Claude 3.7 Sonnet',
+                'description': '强大的Claude 3.7 Sonnet模型，支持图像理解和思考过程'
+            },
+            'gpt-4o-2024-11-20': {
+                'class': OpenAIModel,
+                'is_multimodal': True,
+                'is_reasoning': False,
+                'display_name': 'GPT-4o',
+                'description': 'OpenAI的GPT-4o模型，支持图像理解'
+            },
+            'deepseek-reasoner': {
+                'class': DeepSeekModel,
+                'is_multimodal': False,
+                'is_reasoning': True,
+                'display_name': 'DeepSeek Reasoner',
+                'description': 'DeepSeek推理模型，提供详细思考过程（仅支持文本）'
+            },
+            'mathpix': {
+                'class': MathpixModel,
+                'is_multimodal': True,
+                'is_reasoning': False,
+                'display_name': 'Mathpix OCR',
+                'description': '文本提取工具，适用于数学公式和文本',
+                'is_ocr_only': True
+            }
+        }
 
     @classmethod
-    def create_model(cls, model_name: str, api_key: str, temperature: float = 0.7, system_prompt: str = None) -> BaseModel:
+    def create_model(cls, model_name: str, api_key: str, temperature: float = 0.7, system_prompt: str = None, language: str = None) -> BaseModel:
         """
         Create and return an instance of the specified model.
         
@@ -23,6 +105,7 @@ class ModelFactory:
             api_key: The API key for the model
             temperature: Optional temperature parameter for response generation
             system_prompt: Optional custom system prompt
+            language: Optional language preference for responses
             
         Returns:
             An instance of the specified model
@@ -30,28 +113,86 @@ class ModelFactory:
         Raises:
             ValueError: If the model_name is not recognized
         """
-        model_class = cls._models.get(model_name)
-        if not model_class:
+        model_info = cls._models.get(model_name)
+        if not model_info:
             raise ValueError(f"Unknown model: {model_name}")
         
-        return model_class(
-            api_key=api_key,
-            temperature=temperature,
-            system_prompt=system_prompt
-        )
+        model_class = model_info['class']
+        
+        # 对于Mathpix模型，不传递language参数
+        if model_name == 'mathpix':
+            return model_class(
+                api_key=api_key,
+                temperature=temperature,
+                system_prompt=system_prompt
+            )
+        else:
+            # 对于其他模型，传递所有参数
+            return model_class(
+                api_key=api_key,
+                temperature=temperature,
+                system_prompt=system_prompt,
+                language=language
+            )
 
     @classmethod
-    def get_available_models(cls) -> list[str]:
+    def get_available_models(cls) -> list[Dict[str, Any]]:
+        """Return a list of available models with their information"""
+        models_info = []
+        for model_id, info in cls._models.items():
+            # 跳过仅OCR工具模型
+            if info.get('is_ocr_only', False):
+                continue
+                
+            models_info.append({
+                'id': model_id,
+                'display_name': info.get('display_name', model_id),
+                'description': info.get('description', ''),
+                'is_multimodal': info.get('is_multimodal', False),
+                'is_reasoning': info.get('is_reasoning', False)
+            })
+        return models_info
+    
+    @classmethod
+    def get_model_ids(cls) -> list[str]:
         """Return a list of available model identifiers"""
-        return list(cls._models.keys())
+        return [model_id for model_id in cls._models.keys() 
+                if not cls._models[model_id].get('is_ocr_only', False)]
 
     @classmethod
-    def register_model(cls, model_name: str, model_class: Type[BaseModel]) -> None:
+    def is_multimodal(cls, model_name: str) -> bool:
+        """判断模型是否支持多模态输入"""
+        return cls._models.get(model_name, {}).get('is_multimodal', False)
+    
+    @classmethod
+    def is_reasoning(cls, model_name: str) -> bool:
+        """判断模型是否为推理模型"""
+        return cls._models.get(model_name, {}).get('is_reasoning', False)
+    
+    @classmethod
+    def get_model_display_name(cls, model_name: str) -> str:
+        """获取模型的显示名称"""
+        return cls._models.get(model_name, {}).get('display_name', model_name)
+
+    @classmethod
+    def register_model(cls, model_name: str, model_class: Type[BaseModel], 
+                      is_multimodal: bool = False, is_reasoning: bool = False,
+                      display_name: str = None, description: str = None) -> None:
         """
         Register a new model type with the factory.
         
         Args:
             model_name: The identifier for the model
             model_class: The model class to register
+            is_multimodal: Whether the model supports image input
+            is_reasoning: Whether the model provides reasoning process
+            display_name: Human-readable name for the model
+            description: Description of the model
         """
-        cls._models[model_name] = model_class
+        cls._models[model_name] = {
+            'class': model_class,
+            'is_multimodal': is_multimodal,
+            'is_reasoning': is_reasoning,
+            'display_name': display_name or model_name,
+            'description': description or ''
+        }

models/mathpix.py

@@ -21,6 +21,7 @@ class MathpixModel(BaseModel):
         Raises:
             ValueError: If the API key format is invalid
         """
+        # 只传递必需的参数，不传递language参数
         super().__init__(api_key, temperature, system_prompt)
         try:
             self.app_id, self.app_key = api_key.split(':')

models/openai.py

@@ -3,7 +3,7 @@ from typing import Generator, Dict, Optional
 from openai import OpenAI
 from .base import BaseModel
 
-class GPT4oModel(BaseModel):
+class OpenAIModel(BaseModel):
     def get_default_system_prompt(self) -> str:
         return """You are an expert at analyzing questions and providing detailed solutions. When presented with an image of a question:
 1. First read and understand the question carefully
@@ -126,11 +126,17 @@ class GPT4oModel(BaseModel):
                 # Initialize OpenAI client
                 client = OpenAI(api_key=self.api_key)
 
+                # 检查系统提示词是否已包含语言设置指令
+                system_prompt = self.system_prompt
+                language = self.language or '中文'
+                if not any(phrase in system_prompt for phrase in ['Please respond in', '请用', '使用', '回答']):
+                    system_prompt = f"{system_prompt}\n\n请务必使用{language}回答，无论问题是什么语言。即使在分析图像时也请使用{language}回答。"
+
                 # Prepare messages with image
                 messages = [
                     {
                         "role": "system",
-                        "content": self.system_prompt
+                        "content": system_prompt
                     },
                     {
                         "role": "user",