""" LLM服务配置验证器 验证大模型服务的配置是否正确，并提供配置建议 """ from typing import Dict, List, Any, Optional from loguru import logger from app.config import config from .manager import LLMServiceManager from .exceptions import ConfigurationError class LLMConfigValidator: """LLM服务配置验证器""" @staticmethod def validate_all_configs() -> Dict[str, Any]: """ 验证所有LLM服务配置 Returns: 验证结果字典 """ results = { "vision_providers": {}, "text_providers": {}, "summary": { "total_vision_providers": 0, "valid_vision_providers": 0, "total_text_providers": 0, "valid_text_providers": 0, "errors": [], "warnings": [] } } # 验证视觉模型提供商 vision_providers = LLMServiceManager.list_vision_providers() results["summary"]["total_vision_providers"] = len(vision_providers) for provider in vision_providers: try: validation_result = LLMConfigValidator.validate_vision_provider(provider) results["vision_providers"][provider] = validation_result if validation_result["is_valid"]: results["summary"]["valid_vision_providers"] += 1 else: results["summary"]["errors"].extend(validation_result["errors"]) except Exception as e: error_msg = f"验证视觉模型提供商 {provider} 时发生错误: {str(e)}" results["vision_providers"][provider] = { "is_valid": False, "errors": [error_msg], "warnings": [] } results["summary"]["errors"].append(error_msg) # 验证文本模型提供商 text_providers = LLMServiceManager.list_text_providers() results["summary"]["total_text_providers"] = len(text_providers) for provider in text_providers: try: validation_result = LLMConfigValidator.validate_text_provider(provider) results["text_providers"][provider] = validation_result if validation_result["is_valid"]: results["summary"]["valid_text_providers"] += 1 else: results["summary"]["errors"].extend(validation_result["errors"]) except Exception as e: error_msg = f"验证文本模型提供商 {provider} 时发生错误: {str(e)}" results["text_providers"][provider] = { "is_valid": False, "errors": [error_msg], "warnings": [] } results["summary"]["errors"].append(error_msg) return results @staticmethod def validate_vision_provider(provider_name: str) -> Dict[str, Any]: """ 验证视觉模型提供商配置 Args: provider_name: 提供商名称 Returns: 验证结果字典 """ result = { "is_valid": False, "errors": [], "warnings": [], "config": {} } try: # 获取配置 config_prefix = f"vision_{provider_name}" api_key = config.app.get(f'{config_prefix}_api_key') model_name = config.app.get(f'{config_prefix}_model_name') base_url = config.app.get(f'{config_prefix}_base_url') result["config"] = { "api_key": "***" if api_key else None, "model_name": model_name, "base_url": base_url } # 验证必需配置 if not api_key: result["errors"].append(f"缺少API密钥配置: {config_prefix}_api_key") if not model_name: result["errors"].append(f"缺少模型名称配置: {config_prefix}_model_name") # 尝试创建提供商实例 if api_key and model_name: try: provider_instance = LLMServiceManager.get_vision_provider(provider_name) result["is_valid"] = True logger.debug(f"视觉模型提供商 {provider_name} 配置验证成功") except Exception as e: result["errors"].append(f"创建提供商实例失败: {str(e)}") # 添加警告 if not base_url: result["warnings"].append(f"未配置base_url，将使用默认值") except Exception as e: result["errors"].append(f"配置验证过程中发生错误: {str(e)}") return result @staticmethod def validate_text_provider(provider_name: str) -> Dict[str, Any]: """ 验证文本模型提供商配置 Args: provider_name: 提供商名称 Returns: 验证结果字典 """ result = { "is_valid": False, "errors": [], "warnings": [], "config": {} } try: # 获取配置 config_prefix = f"text_{provider_name}" api_key = config.app.get(f'{config_prefix}_api_key') model_name = config.app.get(f'{config_prefix}_model_name') base_url = config.app.get(f'{config_prefix}_base_url') result["config"] = { "api_key": "***" if api_key else None, "model_name": model_name, "base_url": base_url } # 验证必需配置 if not api_key: result["errors"].append(f"缺少API密钥配置: {config_prefix}_api_key") if not model_name: result["errors"].append(f"缺少模型名称配置: {config_prefix}_model_name") # 尝试创建提供商实例 if api_key and model_name: try: provider_instance = LLMServiceManager.get_text_provider(provider_name) result["is_valid"] = True logger.debug(f"文本模型提供商 {provider_name} 配置验证成功") except Exception as e: result["errors"].append(f"创建提供商实例失败: {str(e)}") # 添加警告 if not base_url: result["warnings"].append(f"未配置base_url，将使用默认值") except Exception as e: result["errors"].append(f"配置验证过程中发生错误: {str(e)}") return result @staticmethod def get_config_suggestions() -> Dict[str, Any]: """ 获取配置建议 Returns: 配置建议字典 """ suggestions = { "vision_providers": {}, "text_providers": {}, "general_tips": [ "确保所有API密钥都已正确配置", "建议为每个提供商配置base_url以提高稳定性", "定期检查模型名称是否为最新版本", "建议配置多个提供商作为备用方案", "推荐使用 LiteLLM 作为统一接口，支持 100+ providers" ] } # 为每个视觉模型提供商提供建议 vision_providers = LLMServiceManager.list_vision_providers() for provider in vision_providers: suggestions["vision_providers"][provider] = { "required_configs": [ f"vision_{provider}_api_key", f"vision_{provider}_model_name" ], "optional_configs": [ f"vision_{provider}_base_url" ], "example_models": LLMConfigValidator._get_example_models(provider, "vision") } # 为每个文本模型提供商提供建议 text_providers = LLMServiceManager.list_text_providers() for provider in text_providers: suggestions["text_providers"][provider] = { "required_configs": [ f"text_{provider}_api_key", f"text_{provider}_model_name" ], "optional_configs": [ f"text_{provider}_base_url" ], "example_models": LLMConfigValidator._get_example_models(provider, "text") } return suggestions @staticmethod def _get_example_models(provider_name: str, model_type: str) -> List[str]: """获取示例模型名称""" examples = { "gemini": { "vision": ["gemini-2.5-flash", "gemini-2.0-flash-lite", "gemini-2.0-flash"], "text": ["gemini-2.5-flash", "gemini-2.0-flash", "gemini-1.5-pro"] }, "openai": { "vision": [], "text": ["gpt-4o", "gpt-4o-mini", "gpt-4-turbo"] }, "qwen": { "vision": ["qwen2.5-vl-32b-instruct"], "text": ["qwen-plus-1127", "qwen-turbo"] }, "deepseek": { "vision": [], "text": ["deepseek-chat", "deepseek-reasoner"] }, "siliconflow": { "vision": ["Qwen/Qwen2.5-VL-32B-Instruct"], "text": ["deepseek-ai/DeepSeek-R1", "Qwen/Qwen2.5-72B-Instruct"] } } return examples.get(provider_name, {}).get(model_type, []) @staticmethod def print_validation_report(validation_results: Dict[str, Any]): """ 打印验证报告 Args: validation_results: 验证结果 """ summary = validation_results["summary"] print("\n" + "="*60) print("LLM服务配置验证报告") print("="*60) print(f"\n📊 总体统计:") print(f" 视觉模型提供商: {summary['valid_vision_providers']}/{summary['total_vision_providers']} 有效") print(f" 文本模型提供商: {summary['valid_text_providers']}/{summary['total_text_providers']} 有效") if summary["errors"]: print(f"\n❌ 错误 ({len(summary['errors'])}):") for error in summary["errors"]: print(f" - {error}") if summary["warnings"]: print(f"\n⚠️ 警告 ({len(summary['warnings'])}):") for warning in summary["warnings"]: print(f" - {warning}") print(f"\n✅ 配置验证完成") print("="*60)