diff --git a/app.py b/app.py index 6d81e30..75836e5 100644 --- a/app.py +++ b/app.py @@ -1,4 +1,4 @@ -from flask import Flask, jsonify, render_template, request +from flask import Flask, jsonify, render_template, request, send_from_directory from flask_socketio import SocketIO import pyautogui import base64 @@ -10,9 +10,17 @@ from PIL import Image, ImageDraw import pyperclip from models import ModelFactory import time +import os +import json + app = Flask(__name__) socketio = SocketIO(app, cors_allowed_origins="*", ping_timeout=30, ping_interval=5, max_http_buffer_size=50 * 1024 * 1024) +# 添加配置文件路径 +CONFIG_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'config') + +# 初始化模型工厂 +ModelFactory.initialize() def get_local_ip(): try: @@ -67,15 +75,21 @@ def handle_disconnect(): -def stream_model_response(response_generator, sid): +def stream_model_response(response_generator, sid, model_name=None): """Stream model responses to the client""" try: print("Starting response streaming...") + # 判断模型是否为推理模型 + is_reasoning = model_name and ModelFactory.is_reasoning(model_name) + if is_reasoning: + print(f"使用推理模型 {model_name}，将显示思考过程") + # 初始化：发送开始状态 socketio.emit('claude_response', { 'status': 'started', - 'content': '' + 'content': '', + 'is_reasoning': is_reasoning }, room=sid) print("Sent initial status to client") @@ -101,27 +115,33 @@ def stream_model_response(response_generator, sid): # 根据不同的状态进行处理 if status == 'thinking': - # 直接使用模型提供的完整思考内容 - thinking_buffer = content - - # 控制发送频率，至少间隔0.3秒 - current_time = time.time() - if current_time - last_emit_time >= 0.3: - socketio.emit('claude_response', { - 'status': 'thinking', - 'content': thinking_buffer - }, room=sid) - last_emit_time = current_time + # 仅对推理模型处理思考过程 + if is_reasoning: + # 直接使用模型提供的完整思考内容 + thinking_buffer = content + + # 控制发送频率，至少间隔0.3秒 + current_time = time.time() + if current_time - last_emit_time >= 0.3: + socketio.emit('claude_response', { + 'status': 'thinking', + 'content': thinking_buffer, + 'is_reasoning': True + }, room=sid) + last_emit_time = current_time elif status == 'thinking_complete': - # 直接使用完整的思考内容 - thinking_buffer = content - - print(f"Thinking complete, total length: {len(thinking_buffer)} chars") - socketio.emit('claude_response', { - 'status': 'thinking_complete', - 'content': thinking_buffer - }, room=sid) + # 仅对推理模型处理思考过程 + if is_reasoning: + # 直接使用完整的思考内容 + thinking_buffer = content + + print(f"Thinking complete, total length: {len(thinking_buffer)} chars") + socketio.emit('claude_response', { + 'status': 'thinking_complete', + 'content': thinking_buffer, + 'is_reasoning': True + }, room=sid) elif status == 'streaming': # 直接使用模型提供的完整内容 @@ -132,7 +152,8 @@ def stream_model_response(response_generator, sid): if current_time - last_emit_time >= 0.3: socketio.emit('claude_response', { 'status': 'streaming', - 'content': response_buffer + 'content': response_buffer, + 'is_reasoning': is_reasoning }, room=sid) last_emit_time = current_time @@ -140,17 +161,20 @@ def stream_model_response(response_generator, sid): # 确保发送最终完整内容 socketio.emit('claude_response', { 'status': 'completed', - 'content': content or response_buffer + 'content': content or response_buffer, + 'is_reasoning': is_reasoning }, room=sid) print("Response completed") elif status == 'error': # 错误状态直接转发 + response['is_reasoning'] = is_reasoning socketio.emit('claude_response', response, room=sid) print(f"Error: {response.get('error', 'Unknown error')}") # 其他状态直接转发 else: + response['is_reasoning'] = is_reasoning socketio.emit('claude_response', response, room=sid) except Exception as e: @@ -158,7 +182,8 @@ def stream_model_response(response_generator, sid): print(error_msg) socketio.emit('claude_response', { 'status': 'error', - 'error': error_msg + 'error': error_msg, + 'is_reasoning': model_name and ModelFactory.is_reasoning(model_name) }, room=sid) @socketio.on('request_screenshot') @@ -227,6 +252,7 @@ def handle_text_extraction(data): raise ValueError("Invalid Mathpix API key format. Expected format: 'app_id:app_key'") print("Creating Mathpix model instance...") + # 只传递必需的参数，ModelFactory.create_model会处理不同模型类型 model = ModelFactory.create_model( model_name='mathpix', api_key=mathpix_key @@ -262,15 +288,53 @@ def handle_analyze_text(data): settings = data.get('settings', {}) sid = request.sid - print("Selected model:", settings.get('model', 'claude-3-7-sonnet-20250219')) + # 从前端传递的设置中获取模型能力信息 + model_capabilities = settings.get('modelCapabilities', {}) + is_reasoning = model_capabilities.get('isReasoning', False) - # Get API key and create model + # 获取模型名称、提供商和API密钥 model_name = settings.get('model', 'claude-3-7-sonnet-20250219') - api_key = settings.get('api_keys', {}).get(model_name) + model_provider = settings.get('modelInfo', {}).get('provider', '').lower() + + print(f"Selected model: {model_name}, Provider: {model_provider}") + + # 获取API密钥 - 同时支持apiKeys和api_keys两种格式 + api_keys = settings.get('apiKeys', {}) or settings.get('api_keys', {}) + print("Debug - 接收到的API密钥(文本分析):", api_keys) + + # 根据提供商或模型名称确定使用哪个API密钥ID + api_key_id = None + + # 首先尝试通过provider匹配 + if model_provider == 'anthropic': + api_key_id = "AnthropicApiKey" + elif model_provider == 'openai': + api_key_id = "OpenaiApiKey" + elif model_provider == 'deepseek': + api_key_id = "DeepseekApiKey" + else: + # 如果provider不可用，尝试通过模型名称匹配 + if "claude" in model_name.lower(): + api_key_id = "AnthropicApiKey" + elif any(keyword in model_name.lower() for keyword in ["gpt", "openai"]): + api_key_id = "OpenaiApiKey" + elif "deepseek" in model_name.lower(): + api_key_id = "DeepseekApiKey" + + api_key = api_keys.get(api_key_id) + print(f"Debug - 使用API密钥ID: {api_key_id}, 密钥值是否存在: {bool(api_key)}") + + language = settings.get('language', '中文') # Validate required settings if not api_key: - raise ValueError("API key is required for the selected model") + raise ValueError(f"API key is required for the selected model (keyId: {api_key_id})") + + # Log with model name for better debugging + print(f"Using API key for {model_name}: {api_key[:6] if api_key else 'None'}...") + print("Selected model:", model_name) + print("Response language:", language) + print(f"Model features: Reasoning={is_reasoning}") # Configure proxy settings if enabled proxies = None @@ -283,18 +347,19 @@ def handle_analyze_text(data): } try: - # Create model instance using factory + # Create model instance using factory - 推理模型不使用temperature参数 model = ModelFactory.create_model( model_name=model_name, api_key=api_key, - temperature=float(settings.get('temperature', 0.7)), - system_prompt=settings.get('systemPrompt') + temperature=None if is_reasoning else float(settings.get('temperature', 0.7)), + system_prompt=settings.get('systemPrompt'), + language=language ) # Start streaming in a separate thread Thread( target=stream_model_response, - args=(model.analyze_text(text, proxies), sid) + args=(model.analyze_text(text, proxies), sid, model_name) ).start() except Exception as e: @@ -313,36 +378,60 @@ def handle_analyze_text(data): @socketio.on('analyze_image') def handle_analyze_image(data): try: - # 检查数据是否有效 - if not data or not isinstance(data, dict): - raise ValueError("Invalid request data") - - image_data = data.get('image') - if not image_data: - raise ValueError("No image data provided") - - # 检查图像大小，避免处理过大的图像导致断开连接 - image_size_bytes = len(image_data) * 3 / 4 # 估算base64的实际大小 - if image_size_bytes > 10 * 1024 * 1024: # 10MB - raise ValueError("Image too large, please crop to a smaller area or use text extraction") - + print("Starting image analysis...") + base64_data = data.get('image', '') settings = data.get('settings', {}) - # 不需要分割了，因为前端已经做了分割 - # _, base64_data = image_data_url.split(',', 1) - base64_data = image_data + # 首先从前端传递的设置中获取模型能力信息 + model_capabilities = settings.get('modelCapabilities', {}) + is_multimodal = model_capabilities.get('supportsMultimodal', False) + is_reasoning = model_capabilities.get('isReasoning', False) - # Get API key and create model + # 获取模型名称、提供商和API密钥 model_name = settings.get('model', 'claude-3-7-sonnet-20250219') - api_key = settings.get('api_keys', {}).get(model_name) - - # Validate required settings + model_provider = settings.get('modelInfo', {}).get('provider', '').lower() + + print(f"Selected model: {model_name}, Provider: {model_provider}") + + # 获取API密钥 - 同时支持apiKeys和api_keys两种格式 + api_keys = settings.get('apiKeys', {}) or settings.get('api_keys', {}) + print("Debug - 接收到的API密钥:", api_keys) + + # 根据提供商或模型名称确定使用哪个API密钥ID + api_key_id = None + + # 首先尝试通过provider匹配 + if model_provider == 'anthropic': + api_key_id = "AnthropicApiKey" + elif model_provider == 'openai': + api_key_id = "OpenaiApiKey" + elif model_provider == 'deepseek': + api_key_id = "DeepseekApiKey" + else: + # 如果provider不可用，尝试通过模型名称匹配 + if "claude" in model_name.lower(): + api_key_id = "AnthropicApiKey" + elif any(keyword in model_name.lower() for keyword in ["gpt", "openai"]): + api_key_id = "OpenaiApiKey" + elif "deepseek" in model_name.lower(): + api_key_id = "DeepseekApiKey" + + api_key = api_keys.get(api_key_id) + print(f"Debug - 使用API密钥ID: {api_key_id}, 密钥值是否存在: {bool(api_key)}") + + language = settings.get('language', '中文') + + # Validate required params + if not base64_data: + raise ValueError("No image data provided") + if not api_key: - raise ValueError(f"API key is required for the selected model: {model_name}") - - # Log with model name for better debugging - print(f"Using API key for {model_name}: {api_key[:6]}...") + raise ValueError(f"API key is required for the selected model (keyId: {api_key_id})") + + # 记录模型信息以便调试 print("Selected model:", model_name) + print("Response language:", language) + print(f"Model capabilities: Multimodal={is_multimodal}, Reasoning={is_reasoning}") # Configure proxy settings if enabled proxies = None @@ -354,27 +443,60 @@ def handle_analyze_image(data): 'https': f'http://{proxy_host}:{proxy_port}' } - try: - # 先回复客户端，确认已收到请求，防止超时断开 - # 注意：这里不能使用return，否则后续代码不会执行 - socketio.emit('request_acknowledged', { - 'status': 'received', - 'message': 'Image received, analysis in progress' - }, room=request.sid) + # 先回复客户端，确认已收到请求，防止超时断开 + socketio.emit('request_acknowledged', { + 'status': 'received', + 'message': 'Image received, analysis in progress' + }, room=request.sid) + + # 如果不是多模态模型，需要先提取文本 + extracted_text = None + if not is_multimodal: + mathpix_key = settings.get('mathpixApiKey') + if not mathpix_key: + raise ValueError("非多模态模型需要Mathpix API Key进行文本提取") + + print("非多模态模型，需要先提取文本...") + mathpix_model = ModelFactory.create_model('mathpix', mathpix_key) - # Create model instance using factory + # 这里假设MathpixModel有一个extract_full_text方法 + # 如果没有，需要实现或调用其他方法来提取文本 + try: + extracted_text = mathpix_model.extract_full_text(base64_data) + print("文本提取成功，长度:", len(extracted_text)) + + # 提示用户文本提取已完成 + socketio.emit('text_extracted', { + 'status': 'success', + 'message': '图像文本提取成功，正在分析...', + 'for_analysis': True + }, room=request.sid) + except Exception as e: + raise ValueError(f"文本提取失败: {str(e)}") + + try: + # Create model instance using factory - 推理模型不使用temperature参数 model = ModelFactory.create_model( model_name=model_name, api_key=api_key, - temperature=float(settings.get('temperature', 0.7)), - system_prompt=settings.get('systemPrompt') + temperature=None if is_reasoning else float(settings.get('temperature', 0.7)), + system_prompt=settings.get('systemPrompt'), + language=language ) # Start streaming in a separate thread - Thread( - target=stream_model_response, - args=(model.analyze_image(base64_data, proxies), request.sid) - ).start() + if not is_multimodal and extracted_text: + # 对于非多模态模型，使用提取的文本 + Thread( + target=stream_model_response, + args=(model.analyze_text(extracted_text, proxies), request.sid, model_name) + ).start() + else: + # 对于多模态模型，直接使用图像 + Thread( + target=stream_model_response, + args=(model.analyze_image(base64_data, proxies), request.sid, model_name) + ).start() except Exception as e: socketio.emit('claude_response', { @@ -417,11 +539,63 @@ def run_tray(): icon = create_tray_icon() icon.run() +# 添加配置文件路由 +@app.route('/config/') +def serve_config(filename): + return send_from_directory(CONFIG_DIR, filename) + +# 添加用于获取所有模型信息的API +@app.route('/api/models', methods=['GET']) +def get_models(): + """返回可用的模型列表""" + models = ModelFactory.get_available_models() + return jsonify(models) + +def load_model_config(): + """加载模型配置信息""" + try: + config_path = os.path.join(CONFIG_DIR, 'models.json') + with open(config_path, 'r', encoding='utf-8') as f: + config = json.load(f) + return config + except Exception as e: + print(f"加载模型配置失败: {e}") + return { + "providers": {}, + "models": {} + } + +# 替换 before_first_request 装饰器 +def init_model_config(): + """初始化模型配置""" + try: + model_config = load_model_config() + # 更新ModelFactory的模型信息 + if hasattr(ModelFactory, 'update_model_capabilities'): + ModelFactory.update_model_capabilities(model_config) + print("已加载模型配置") + except Exception as e: + print(f"初始化模型配置失败: {e}") + +# 在请求处理前注册初始化函数 +@app.before_request +def before_request_handler(): + # 使用全局变量跟踪是否已初始化 + if not getattr(app, '_model_config_initialized', False): + init_model_config() + app._model_config_initialized = True + if __name__ == '__main__': local_ip = get_local_ip() print(f"Local IP Address: {local_ip}") print(f"Connect from your mobile device using: {local_ip}:5000") + # 加载模型配置 + model_config = load_model_config() + if hasattr(ModelFactory, 'update_model_capabilities'): + ModelFactory.update_model_capabilities(model_config) + print("已加载模型配置信息") + # Run system tray icon in a separate thread tray_thread = Thread(target=run_tray) tray_thread.daemon = True diff --git a/config/models.json b/config/models.json new file mode 100644 index 0000000..a5f97de --- /dev/null +++ b/config/models.json @@ -0,0 +1,53 @@ +{ + "providers": { + "anthropic": { + "name": "Anthropic", + "api_key_id": "AnthropicApiKey", + "class_name": "AnthropicModel" + }, + "openai": { + "name": "OpenAI", + "api_key_id": "OpenaiApiKey", + "class_name": "OpenAIModel" + }, + "deepseek": { + "name": "DeepSeek", + "api_key_id": "DeepseekApiKey", + "class_name": "DeepSeekModel" + } + }, + "models": { + "claude-3-7-sonnet-20250219": { + "name": "Claude 3.7 Sonnet", + "provider": "anthropic", + "supportsMultimodal": true, + "isReasoning": true, + "version": "20250219", + "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": { + "name": "GPT-4o", + "provider": "openai", + "supportsMultimodal": true, + "isReasoning": false, + "version": "2024-11-20", + "description": "OpenAI的GPT-4o模型，支持图像理解" + }, + "o3-mini": { + "name": "o3-mini", + "provider": "openai", + "supportsMultimodal": false, + "isReasoning": true, + "version": "2025-01-31", + "description": "OpenAI的o3-mini模型，支持图像理解和思考过程" + }, + "deepseek-r1": { + "name": "DeepSeek-R1", + "provider": "deepseek", + "supportsMultimodal": false, + "isReasoning": true, + "version": "latest", + "description": "DeepSeek推理模型，提供详细思考过程（仅支持文本）" + } + } +} \ No newline at end of file diff --git a/models/__init__.py b/models/__init__.py index e7e9945..eded06f 100644 --- a/models/__init__.py +++ b/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' ] diff --git a/models/claude.py b/models/anthropic.py similarity index 95% rename from models/claude.py rename to models/anthropic.py index 813d61a..6d70941 100644 --- a/models/claude.py +++ b/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。" } ] }] diff --git a/models/base.py b/models/base.py index 5a45d9c..f5db031 100644 --- a/models/base.py +++ b/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 diff --git a/models/deepseek.py b/models/deepseek.py index fa02fb4..046df93 100644 --- a/models/deepseek.py +++ b/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}" }], diff --git a/models/factory.py b/models/factory.py index 37e56fe..42eeb67 100644 --- a/models/factory.py +++ b/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 '' + } diff --git a/models/mathpix.py b/models/mathpix.py index ce2cbfc..ba7863b 100644 --- a/models/mathpix.py +++ b/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(':') diff --git a/models/gpt4o.py b/models/openai.py similarity index 93% rename from models/gpt4o.py rename to models/openai.py index b5d86c1..1845016 100644 --- a/models/gpt4o.py +++ b/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", diff --git a/static/js/main.js b/static/js/main.js index 8ceb735..cb379f7 100644 --- a/static/js/main.js +++ b/static/js/main.js @@ -189,9 +189,8 @@ class SnapSolver { this.imagePreview.classList.remove('hidden'); this.emptyState.classList.add('hidden'); - // 显示Claude和提取文本按钮 - this.sendToClaudeBtn.classList.remove('hidden'); - this.extractTextBtn.classList.remove('hidden'); + // 根据模型类型显示适当的按钮 + this.updateImageActionButtons(); // 恢复按钮状态 this.captureBtn.disabled = false; @@ -221,9 +220,8 @@ class SnapSolver { this.imagePreview.classList.remove('hidden'); this.emptyState.classList.add('hidden'); - // 显示Claude和提取文本按钮 - this.sendToClaudeBtn.classList.remove('hidden'); - this.extractTextBtn.classList.remove('hidden'); + // 根据模型类型显示适当的按钮 + this.updateImageActionButtons(); // 初始化裁剪工具 this.initializeCropper(); @@ -599,6 +597,13 @@ class SnapSolver { this.setupAnalysisEvents(); this.setupKeyboardShortcuts(); this.setupThinkingToggle(); + + // 监听模型选择变化，更新界面 + if (window.settingsManager && window.settingsManager.modelSelect) { + window.settingsManager.modelSelect.addEventListener('change', () => { + this.updateImageActionButtons(); + }); + } } setupCaptureEvents() { @@ -741,10 +746,9 @@ class SnapSolver { this.extractTextBtn.innerHTML = '提取中...'; const settings = window.settingsManager.getSettings(); - const mathpixAppId = settings.mathpixAppId; - const mathpixAppKey = settings.mathpixAppKey; + const mathpixApiKey = settings.mathpixApiKey; - if (!mathpixAppId || !mathpixAppKey) { + if (!mathpixApiKey || mathpixApiKey === ':') { window.uiManager.showToast('请在设置中输入Mathpix API凭据', 'error'); document.getElementById('settingsPanel').classList.remove('hidden'); this.extractTextBtn.disabled = false; @@ -772,7 +776,7 @@ class SnapSolver { this.socket.emit('extract_text', { image: this.croppedImage.split(',')[1], settings: { - mathpixApiKey: `${mathpixAppId}:${mathpixAppKey}` + mathpixApiKey: mathpixApiKey } }); @@ -806,12 +810,15 @@ class SnapSolver { const settings = window.settingsManager.getSettings(); const apiKeys = {}; - Object.entries(window.settingsManager.apiKeyInputs).forEach(([model, input]) => { - if (input.value) { - apiKeys[model] = input.value; + Object.keys(window.settingsManager.apiKeyInputs).forEach(keyId => { + const input = window.settingsManager.apiKeyInputs[keyId]; + if (input && input.value) { + apiKeys[keyId] = input.value; } }); + console.log("Debug - 发送文本分析API密钥:", apiKeys); + // 清空之前的结果 this.responseContent.innerHTML = ''; this.thinkingContent.innerHTML = ''; @@ -827,8 +834,13 @@ class SnapSolver { text: text, settings: { ...settings, - api_keys: apiKeys, + apiKeys: apiKeys, model: settings.model || 'claude-3-7-sonnet-20250219', + modelInfo: settings.modelInfo || {}, + modelCapabilities: { + supportsMultimodal: settings.modelInfo?.supportsMultimodal || false, + isReasoning: settings.modelInfo?.isReasoning || false + } } }); } catch (error) { @@ -972,12 +984,15 @@ class SnapSolver { // 获取API密钥 const apiKeys = {}; - Object.entries(window.settingsManager.apiKeyInputs).forEach(([model, input]) => { - if (input.value) { - apiKeys[model] = input.value; + Object.keys(window.settingsManager.apiKeyInputs).forEach(keyId => { + const input = window.settingsManager.apiKeyInputs[keyId]; + if (input && input.value) { + apiKeys[keyId] = input.value; } }); + console.log("Debug - 发送API密钥:", apiKeys); + try { // 处理图像数据，去除base64前缀 let processedImageData = imageData; @@ -990,8 +1005,13 @@ class SnapSolver { image: processedImageData, settings: { ...settings, - api_keys: apiKeys, + apiKeys: apiKeys, model: settings.model || 'claude-3-7-sonnet-20250219', + modelInfo: settings.modelInfo || {}, + modelCapabilities: { + supportsMultimodal: settings.modelInfo?.supportsMultimodal || false, + isReasoning: settings.modelInfo?.isReasoning || false + } } }); @@ -1045,6 +1065,9 @@ class SnapSolver { // 设置默认UI状态 this.enableInterface(); + // 更新图像操作按钮 + this.updateImageActionButtons(); + console.log('SnapSolver initialization complete'); } @@ -1161,6 +1184,30 @@ class SnapSolver { } } } + + // 新增方法：根据所选模型更新图像操作按钮 + updateImageActionButtons() { + if (!window.settingsManager) return; + + const settings = window.settingsManager.getSettings(); + const isMultimodalModel = settings.modelInfo?.supportsMultimodal || false; + + // 对于截图后的操作按钮显示逻辑 + if (this.sendToClaudeBtn && this.extractTextBtn) { + if (!isMultimodalModel) { + // 非多模态模型：只显示提取文本按钮，隐藏发送到AI按钮 + this.sendToClaudeBtn.classList.add('hidden'); + this.extractTextBtn.classList.remove('hidden'); + } else { + // 多模态模型：显示两个按钮 + if (!this.imagePreview.classList.contains('hidden')) { + // 只有在有图像时才显示按钮 + this.sendToClaudeBtn.classList.remove('hidden'); + this.extractTextBtn.classList.remove('hidden'); + } + } + } + } } // Initialize the application when the DOM is loaded diff --git a/static/js/settings.js b/static/js/settings.js index d393e0e..e0e2d27 100644 --- a/static/js/settings.js +++ b/static/js/settings.js @@ -1,8 +1,147 @@ class SettingsManager { constructor() { + // 初始化属性 + this.modelDefinitions = {}; + this.providerDefinitions = {}; + + // 初始化界面元素 this.initializeElements(); - this.loadSettings(); - this.setupEventListeners(); + + // 加载模型配置 + this.loadModelConfig() + .then(() => { + // 成功加载配置后，执行后续初始化 + this.updateModelOptions(); + this.loadSettings(); + this.setupEventListeners(); + this.updateUIBasedOnModelType(); + }) + .catch(error => { + console.error('加载模型配置失败:', error); + window.uiManager?.showToast('加载模型配置失败，使用默认配置', 'error'); + + // 使用默认配置作为备份 + this.setupDefaultModels(); + this.updateModelOptions(); + this.loadSettings(); + this.setupEventListeners(); + this.updateUIBasedOnModelType(); + }); + } + + // 从配置文件加载模型定义 + async loadModelConfig() { + try { + // 使用API端点获取模型列表 + const response = await fetch('/api/models'); + if (!response.ok) { + throw new Error(`加载模型列表失败: ${response.status} ${response.statusText}`); + } + + // 获取模型列表 + const modelsList = await response.json(); + + // 获取提供商配置 + const configResponse = await fetch('/config/models.json'); + if (!configResponse.ok) { + throw new Error(`加载提供商配置失败: ${configResponse.status} ${configResponse.statusText}`); + } + + const config = await configResponse.json(); + + // 保存提供商定义 + this.providerDefinitions = config.providers || {}; + + // 处理模型定义 + this.modelDefinitions = {}; + + // 从API获取的模型列表创建模型定义 + modelsList.forEach(model => { + this.modelDefinitions[model.id] = { + name: model.display_name, + provider: this.getProviderIdByModel(model.id, config), + supportsMultimodal: model.is_multimodal, + isReasoning: model.is_reasoning, + apiKeyId: this.getApiKeyIdByModel(model.id, config), + description: model.description, + version: this.getVersionByModel(model.id, config) + }; + }); + + console.log('模型配置加载成功:', this.modelDefinitions); + } catch (error) { + console.error('加载模型配置时出错:', error); + throw error; + } + } + + // 从配置中根据模型ID获取提供商ID + getProviderIdByModel(modelId, config) { + const modelConfig = config.models[modelId]; + return modelConfig ? modelConfig.provider : 'unknown'; + } + + // 从配置中根据模型ID获取API密钥ID + getApiKeyIdByModel(modelId, config) { + const modelConfig = config.models[modelId]; + if (!modelConfig) return null; + + const providerId = modelConfig.provider; + const provider = config.providers[providerId]; + return provider ? provider.api_key_id : null; + } + + // 从配置中根据模型ID获取版本信息 + getVersionByModel(modelId, config) { + const modelConfig = config.models[modelId]; + return modelConfig ? modelConfig.version : 'latest'; + } + + // 设置默认模型定义（当配置加载失败时使用） + setupDefaultModels() { + this.providerDefinitions = { + 'anthropic': { + name: 'Anthropic', + api_key_id: 'AnthropicApiKey' + }, + 'openai': { + name: 'OpenAI', + api_key_id: 'OpenaiApiKey' + }, + 'deepseek': { + name: 'DeepSeek', + api_key_id: 'DeepseekApiKey' + } + }; + + this.modelDefinitions = { + 'claude-3-7-sonnet-20250219': { + name: 'Claude 3.7 Sonnet', + provider: 'anthropic', + supportsMultimodal: true, + isReasoning: true, + apiKeyId: 'AnthropicApiKey', + version: '20250219' + }, + 'gpt-4o-2024-11-20': { + name: 'GPT-4o', + provider: 'openai', + supportsMultimodal: true, + isReasoning: false, + apiKeyId: 'OpenaiApiKey', + version: '2024-11-20' + }, + 'deepseek-reasoner': { + name: 'DeepSeek Reasoner', + provider: 'deepseek', + supportsMultimodal: false, + isReasoning: true, + apiKeyId: 'DeepseekApiKey', + version: 'latest' + } + }; + + console.log('使用默认模型配置'); } initializeElements() { @@ -11,6 +150,8 @@ class SettingsManager { this.modelSelect = document.getElementById('modelSelect'); this.temperatureInput = document.getElementById('temperature'); this.temperatureValue = document.getElementById('temperatureValue'); + this.temperatureGroup = document.querySelector('.setting-group:has(#temperature)') || + document.querySelector('div.setting-group:has(input[id="temperature"])'); this.systemPromptInput = document.getElementById('systemPrompt'); this.languageInput = document.getElementById('language'); this.proxyEnabledInput = document.getElementById('proxyEnabled'); @@ -22,25 +163,29 @@ class SettingsManager { this.mathpixAppIdInput = document.getElementById('mathpixAppId'); this.mathpixAppKeyInput = document.getElementById('mathpixAppKey'); - // API Key elements + // API Key elements - 所有的密钥输入框 this.apiKeyInputs = { - 'claude-3-7-sonnet-20250219': document.getElementById('claudeApiKey'), - 'gpt-4o-2024-11-20': document.getElementById('gpt4oApiKey'), - 'deepseek-reasoner': document.getElementById('deepseekApiKey') + 'AnthropicApiKey': document.getElementById('AnthropicApiKey'), + 'OpenaiApiKey': document.getElementById('OpenaiApiKey'), + 'DeepseekApiKey': document.getElementById('DeepseekApiKey'), + 'mathpixAppId': this.mathpixAppIdInput, + 'mathpixAppKey': this.mathpixAppKeyInput }; // Settings toggle elements this.settingsToggle = document.getElementById('settingsToggle'); this.closeSettings = document.getElementById('closeSettings'); + + // 获取所有密钥输入组元素 this.apiKeyGroups = document.querySelectorAll('.api-key-group'); // Initialize API key toggle buttons document.querySelectorAll('.toggle-api-key').forEach(button => { button.addEventListener('click', (e) => { - const input = e.target.closest('.input-group').querySelector('input'); + const input = e.currentTarget.closest('.input-group').querySelector('input'); const type = input.type === 'password' ? 'text' : 'password'; input.type = type; - const icon = e.target.querySelector('i'); + const icon = e.currentTarget.querySelector('i'); if (icon) { icon.className = `fas fa-${type === 'password' ? 'eye' : 'eye-slash'}`; } @@ -48,6 +193,49 @@ class SettingsManager { }); } + // 更新模型选择下拉框 + updateModelOptions() { + // 清空现有选项 + this.modelSelect.innerHTML = ''; + + // 提取提供商信息 + const providers = {}; + Object.entries(this.providerDefinitions).forEach(([providerId, provider]) => { + providers[providerId] = provider.name; + }); + + // 为每个提供商创建一个选项组 + for (const [providerId, providerName] of Object.entries(providers)) { + const optgroup = document.createElement('optgroup'); + optgroup.label = providerName; + + // 过滤该提供商的模型 + const providerModels = Object.entries(this.modelDefinitions) + .filter(([_, modelInfo]) => modelInfo.provider === providerId) + .sort((a, b) => a[1].name.localeCompare(b[1].name)); + + // 添加该提供商的模型选项 + for (const [modelId, modelInfo] of providerModels) { + const option = document.createElement('option'); + option.value = modelId; + + // 显示模型名称和版本（如果不是latest） + let displayName = modelInfo.name; + if (modelInfo.version && modelInfo.version !== 'latest') { + displayName += ` (${modelInfo.version})`; + } + + option.textContent = displayName; + optgroup.appendChild(option); + } + + // 只添加有模型的提供商 + if (optgroup.children.length > 0) { + this.modelSelect.appendChild(optgroup); + } + } + } + loadSettings() { const settings = JSON.parse(localStorage.getItem('aiSettings') || '{}'); @@ -61,21 +249,28 @@ class SettingsManager { // Load API keys if (settings.apiKeys) { - Object.entries(this.apiKeyInputs).forEach(([model, input]) => { - if (settings.apiKeys[model]) { - input.value = settings.apiKeys[model]; + Object.entries(this.apiKeyInputs).forEach(([keyId, input]) => { + if (settings.apiKeys[keyId]) { + input.value = settings.apiKeys[keyId]; } }); } - if (settings.model) { - this.modelSelect.value = settings.model; - this.updateVisibleApiKey(settings.model); + // 选择模型并更新相关UI + let selectedModel = ''; + + if (settings.model && this.modelExists(settings.model)) { + selectedModel = settings.model; + this.modelSelect.value = selectedModel; } else { - // Default to first model if none selected - this.updateVisibleApiKey(this.modelSelect.value); + // Default to first model if none selected or if saved model no longer exists + selectedModel = this.modelSelect.value; } + // 更新相关UI显示 + this.updateVisibleApiKey(selectedModel); + this.updateModelVersionDisplay(selectedModel); + if (settings.temperature) { this.temperatureInput.value = settings.temperature; this.temperatureValue.textContent = settings.temperature; @@ -89,13 +284,74 @@ class SettingsManager { if (settings.proxyPort) this.proxyPortInput.value = settings.proxyPort; this.proxySettings.style.display = this.proxyEnabledInput.checked ? 'block' : 'none'; + + this.updateUIBasedOnModelType(); + } + + modelExists(modelId) { + return this.modelDefinitions.hasOwnProperty(modelId); + } + + // 更新模型版本显示 + updateModelVersionDisplay(modelId) { + const modelVersionText = document.getElementById('modelVersionText'); + if (!modelVersionText) return; + + const model = this.modelDefinitions[modelId]; + if (!model) { + modelVersionText.textContent = '-'; + return; + } + + // 显示版本信息（如果有） + if (model.version && model.version !== 'latest') { + modelVersionText.textContent = model.version; + } else if (model.version === 'latest') { + modelVersionText.textContent = '最新版'; + } else { + modelVersionText.textContent = '-'; + } } updateVisibleApiKey(selectedModel) { + const modelInfo = this.modelDefinitions[selectedModel]; + if (!modelInfo) return; + + const requiredApiKeyId = modelInfo.apiKeyId; + const providerInfo = this.providerDefinitions[modelInfo.provider]; + + // 更新API密钥标签突出显示，而不是隐藏不需要的密钥 this.apiKeyGroups.forEach(group => { - const modelValue = group.dataset.model; - group.style.display = modelValue === selectedModel ? 'block' : 'none'; + const keyInputId = group.querySelector('input').id; + const isRequired = keyInputId === requiredApiKeyId; + + // 为需要的API密钥添加突出显示样式 + if (isRequired) { + group.classList.add('api-key-active'); + } else { + group.classList.remove('api-key-active'); + } + + // 更新Mathpix相关输入框的必要性 + if ((keyInputId === 'mathpixAppId' || keyInputId === 'mathpixAppKey') && + !modelInfo.supportsMultimodal) { + group.classList.add('api-key-active'); // 非多模态模型需要Mathpix + } }); + + // 更新模型版本显示 + this.updateModelVersionDisplay(selectedModel); + } + + updateUIBasedOnModelType() { + const selectedModel = this.modelSelect.value; + const modelInfo = this.modelDefinitions[selectedModel]; + + if (!modelInfo) return; + + if (this.temperatureGroup) { + this.temperatureGroup.style.display = modelInfo.isReasoning ? 'none' : 'block'; + } } saveSettings() { @@ -113,9 +369,9 @@ class SettingsManager { }; // Save all API keys - Object.entries(this.apiKeyInputs).forEach(([model, input]) => { + Object.entries(this.apiKeyInputs).forEach(([keyId, input]) => { if (input.value) { - settings.apiKeys[model] = input.value; + settings.apiKeys[keyId] = input.value; } }); @@ -125,7 +381,12 @@ class SettingsManager { getApiKey() { const selectedModel = this.modelSelect.value; - const apiKey = this.apiKeyInputs[selectedModel]?.value; + const modelInfo = this.modelDefinitions[selectedModel]; + + if (!modelInfo) return ''; + + const apiKeyId = modelInfo.apiKeyId; + const apiKey = this.apiKeyInputs[apiKeyId]?.value; if (!apiKey) { window.showToast('Please enter API key for the selected model', 'error'); @@ -139,22 +400,38 @@ class SettingsManager { const language = this.languageInput.value || '中文'; const basePrompt = this.systemPromptInput.value || ''; - // 检查系统提示词是否已包含语言设置 let systemPrompt = basePrompt; if (!basePrompt.includes('Please respond in') && !basePrompt.includes('请用') && !basePrompt.includes('使用')) { systemPrompt = `${basePrompt}\n\n请务必使用${language}回答。`; } + const selectedModel = this.modelSelect.value; + const modelInfo = this.modelDefinitions[selectedModel] || {}; + return { - model: this.modelSelect.value, + model: selectedModel, temperature: this.temperatureInput.value, language: language, systemPrompt: systemPrompt, proxyEnabled: this.proxyEnabledInput.checked, proxyHost: this.proxyHostInput.value, proxyPort: this.proxyPortInput.value, - mathpixAppId: this.mathpixAppIdInput.value, - mathpixAppKey: this.mathpixAppKeyInput.value + mathpixApiKey: `${this.mathpixAppIdInput.value}:${this.mathpixAppKeyInput.value}`, + modelInfo: { + supportsMultimodal: modelInfo.supportsMultimodal || false, + isReasoning: modelInfo.isReasoning || false, + provider: modelInfo.provider || 'unknown' + } + }; + } + + getModelCapabilities(modelId) { + const model = this.modelDefinitions[modelId]; + if (!model) return { supportsMultimodal: false, isReasoning: false }; + + return { + supportsMultimodal: model.supportsMultimodal, + isReasoning: model.isReasoning }; } @@ -170,6 +447,8 @@ class SettingsManager { this.modelSelect.addEventListener('change', (e) => { this.updateVisibleApiKey(e.target.value); + this.updateUIBasedOnModelType(); + this.updateModelVersionDisplay(e.target.value); this.saveSettings(); }); diff --git a/static/style.css b/static/style.css index 8379f09..e4b1cde 100644 --- a/static/style.css +++ b/static/style.css @@ -1288,3 +1288,41 @@ button:disabled { align-self: flex-end; } } + +/* 模型版本信息样式 */ +.model-version-info { + margin-top: 5px; + font-size: 0.85em; + color: var(--text-secondary); + display: flex; + align-items: center; +} + +.model-version-info i { + margin-right: 5px; + color: var(--accent); +} + +/* 在模型选择后添加版本信息 */ +#modelSelect + .model-version-info { + margin-top: 5px; +} + +/* API密钥高亮显示样式 */ +.api-key-group { + transition: all 0.3s ease; + border-left: 3px solid transparent; + padding-left: 0.5rem; +} + +.api-key-active { + border-left: 3px solid var(--primary); + background-color: rgba(var(--primary-rgb), 0.05); + padding-left: 0.5rem; + border-radius: 4px; +} + +.api-key-active label { + color: var(--primary); + font-weight: 600; +} diff --git a/templates/index.html b/templates/index.html index 44a3019..020678c 100644 --- a/templates/index.html +++ b/templates/index.html @@ -111,68 +111,17 @@
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代理设置

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