{"repo": "charrrrls/ai-scripts", "files": {"ai_config.py": {"d63c57663165b3af540fa7b5a2bc556644b6eaad": {"t": 1785674168.6186538, "n": 9385, "h": "4045b48e490442f7", "c": "#!/usr/bin/env python3\n\"\"\"\nAI配置管理模块 - by 阮阮\n统一管理所有AI相关配置，支持多环境配置\n\"\"\"\n\nimport os\nimport json\nfrom typing import Dict, Any, Optional\nfrom enum import Enum\n\n\nclass Environment(Enum):\n    \"\"\"环境类型枚举\"\"\"\n    DEVELOPMENT = \"development\"\n    PRODUCTION = \"production\"\n    TESTING = \"testing\"\n\n\nclass AIProvider(Enum):\n    \"\"\"AI服务提供商枚举\"\"\"\n    SILICONFLOW = \"siliconflow\"\n    OPENAI = \"openai\"\n    ANTHROPIC = \"anthropic\"\n    QWEN = \"qwen\"\n    DASHSCOPE = \"dashscope\"\n\n\nclass AIConfig:\n    \"\"\"AI配置管理类\"\"\"\n    \n    def __init__(self, env: Environment = Environment.PRODUCTION):\n        self.env = env\n        self._config = self._load_config()\n    \n    def _load_config(self) -> Dict[str, Any]:\n        \"\"\"加载配置\"\"\"\n        # 基础配置\n        base_config = {\n            \"provider\": AIProvider.SILICONFLOW.value,\n            \"api_key\": \"sk-luicbwpmghinywzxkumosqyvurpohzgycdmumowkhlwleuwp\",\n            \"api_url\": \"https://api.siliconflow.cn/v1/chat/completions\",\n            \"model_name\": \"THUDM/GLM-4-32B-0414\",\n            \"timeout\": 60,\n            \"max_retries\": 3,\n            \"retry_delay\": 2,  # 秒\n            \"max_tokens\": 4096,\n            \"temperature\": 0.7,\n            \"stream\": False,  # 默认批量模式\n\n            # 流式模式配置\n            \"enable_streaming\": True,  # 是否支持流式模式\n            \"stream_chunk_size\": 1,    # 流式输出块大小\n            \"stream_delay\": 0.005,      # 流式输出延迟（秒）\n            \"show_thinking\": True,     # 是否显示思考状态\n\n            # 场景特定配置\n            \"scenarios\": {\n                \"chat\": {\n                    \"stream\": True,      # 对话使用流式模式\n                    \"temperature\": 0.8,  # 对话更有创造性\n                    \"show_thinking\": True\n                },\n                \"commit\": {\n                    \"stream\": False,     # commit信息使用批量模式\n                    \"temperature\": 0.3,  # commit信息更稳定\n                    \"max_tokens\": 100,\n                    \"show_thinking\": False\n                },\n                \"blog\": {\n                    \"stream\": False,     # 博客生成使用批量模式\n                    \"temperature\": 0.7,\n                    \"max_tokens\": 3000,\n                    \"show_thinking\": False\n                },\n                \"qwen\": {\n                    \"stream\": True,      # 千问支持流式\n                    \"temperature\": 0.7,\n                    \"max_tokens\": 4096,\n                    \"show_thinking\": False\n                },\n                \"vector_query\": {\n                    \"stream\": False,     # 向量查询使用批量模式\n                    \"temperature\": 0.5,  # 查询更精确\n                    \"max_tokens\": 2000,\n                    \"show_thinking\": False\n                },\n                \"vision\": {\n                    \"stream\": True,      # 视觉分析使用流式模式\n                    \"temperature\": 0.7,  # 视觉描述需要一定创造性\n                    \"max_tokens\": 2000,\n                    \"model_name\": \"Qwen/Qwen2.5-VL-72B-Instruct\",  # 视觉模型\n                    \"show_thinking\": False\n                }\n            },\n            \n            # 千问配置\n            \"qwen_config\": {\n                \"api_key\": \"\",  # 需要配置\n                \"api_url\": \"https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation\",\n                \"model_name\": \"qwen-turbo\",\n                \"workspace_id\": \"\"  # 可选\n            },\n            \n            # 向量库配置\n            \"vector_config\": {\n                \"enabled\": True,\n                \"db_path\": \"./vector_db\",\n                \"embedding_model\": \"text-embedding-v1\",\n                \"chunk_size\": 1000,\n                \"chunk_overlap\": 100,\n                \"similarity_threshold\": 0.7\n            }\n        }\n        \n        # 环境特定配置\n        env_configs = {\n            Environment.DEVELOPMENT: {\n                \"timeout\": 30,\n                \"max_retries\": 2,\n                \"temperature\": 0.8,\n                \"debug\": True\n            },\n            Environment.PRODUCTION: {\n                \"timeout\": 60,\n                \"max_retries\": 3,\n                \"temperature\": 0.7,\n                \"debug\": False\n            },\n            Environment.TESTING: {\n                \"timeout\": 15,\n                \"max_retries\": 1,\n                \"temperature\": 0.5,\n                \"debug\": True,\n                \"model_name\": \"THUDM/GLM-4-9B-Chat\"  # 测试用较小模型\n            }\n        }\n        \n        # 合并配置\n        config = base_config.copy()\n        if self.env in env_configs:\n            config.update(env_configs[self.env])\n        \n        # 从环境变量覆盖配置\n        self._load_from_env(config)\n        \n        # 从配置文件覆盖配置\n        self._load_from_file(config)\n        \n        return config\n    \n    def _load_from_env(self, config: Dict[str, Any]) -> None:\n        \"\"\"从环境变量加载配置\"\"\"\n        env_mappings = {\n            \"AI_API_KEY\": \"api_key\",\n            \"AI_API_URL\": \"api_url\", \n            \"AI_MODEL_NAME\": \"model_name\",\n            \"AI_TIMEOUT\": \"timeout\",\n            \"AI_MAX_RETRIES\": \"max_retries\",\n            \"AI_TEMPERATURE\": \"temperature\"\n        }\n        \n        for env_var, config_key in env_mappings.items():\n            value = os.getenv(env_var)\n            if value:\n                # 类型转换\n                if config_key in [\"timeout\", \"max_retries\"]:\n                    config[config_key] = int(value)\n                elif config_key in [\"temperature\"]:\n                    config[config_key] = float(value)\n                else:\n                    config[config_key] = value\n    \n    def _load_from_file(self, config: Dict[str, Any]) -> None:\n        \"\"\"从配置文件加载配置\"\"\"\n        config_file = f\"ai_config_{self.env.value}.json\"\n        if os.path.exists(config_file):\n            try:\n                with open(config_file, 'r', encoding='utf-8') as f:\n                    file_config = json.load(f)\n                config.update(file_config)\n            except Exception:\n                pass  # 忽略配置文件错误\n    \n    @property\n    def api_key(self) -> str:\n        \"\"\"API密钥\"\"\"\n        return self._config[\"api_key\"]\n    \n    @property\n    def api_url(self) -> str:\n        \"\"\"API URL\"\"\"\n        return self._config[\"api_url\"]\n    \n    @property\n    def model_name(self) -> str:\n        \"\"\"模型名称\"\"\"\n        return self._config[\"model_name\"]\n    \n    @property\n    def timeout(self) -> int:\n        \"\"\"超时时间（秒）\"\"\"\n        return self._config[\"timeout\"]\n    \n    @property\n    def max_retries(self) -> int:\n        \"\"\"最大重试次数\"\"\"\n        return self._config[\"max_retries\"]\n    \n    @property\n    def retry_delay(self) -> int:\n        \"\"\"重试延迟（秒）\"\"\"\n        return self._config[\"retry_delay\"]\n    \n    @property\n    def max_tokens(self) -> int:\n        \"\"\"最大token数\"\"\"\n        return self._config[\"max_tokens\"]\n    \n    @property\n    def temperature(self) -> float:\n        \"\"\"温度参数\"\"\"\n        return self._config[\"temperature\"]\n    \n    @property\n    def stream(self) -> bool:\n        \"\"\"是否流式输出\"\"\"\n        return self._config[\"stream\"]\n    \n    @property\n    def debug(self) -> bool:\n        \"\"\"是否调试模式\"\"\"\n        return self._config.get(\"debug\", False)\n    \n    @property\n    def provider(self) -> str:\n        \"\"\"服务提供商\"\"\"\n        return self._config[\"provider\"]\n    \n    def get(self, key: str, default: Any = None) -> Any:\n        \"\"\"获取配置项\"\"\"\n        return self._config.get(key, default)\n    \n    def update(self, **kwargs) -> None:\n        \"\"\"更新配置\"\"\"\n        self._config.update(kwargs)\n    \n    def to_dict(self) -> Dict[str, Any]:\n        \"\"\"转换为字典\"\"\"\n        return self._config.copy()\n\n    def get_scenario_config(self, scenario: str) -> Dict[str, Any]:\n        \"\"\"获取特定场景的配置\"\"\"\n        scenarios = self._config.get(\"scenarios\", {})\n        scenario_config = scenarios.get(scenario, {})\n\n        # 合并基础配置和场景配置\n        merged_config = self._config.copy()\n        merged_config.update(scenario_config)\n\n        return merged_config\n\n    def is_streaming_enabled(self) -> bool:\n        \"\"\"检查是否启用流式模式\"\"\"\n        return self._config.get(\"enable_streaming\", False)\n\n    def should_show_thinking(self, scenario: str = None) -> bool:\n        \"\"\"检查是否应该显示思考状态\"\"\"\n        if scenario:\n            scenario_config = self.get_scenario_config(scenario)\n            return scenario_config.get(\"show_thinking\", False)\n        return self._config.get(\"show_thinking\", False)\n\n    @property\n    def stream_delay(self) -> float:\n        \"\"\"流式输出延迟\"\"\"\n        return self._config.get(\"stream_delay\", 0.02)\n\n    @property\n    def stream_chunk_size(self) -> int:\n        \"\"\"流式输出块大小\"\"\"\n        return self._config.get(\"stream_chunk_size\", 1)\n\n\n# 全局配置实例\n_global_config: Optional[AIConfig] = None\n\n\ndef get_config(env: Environment = Environment.PRODUCTION) -> AIConfig:\n    \"\"\"获取全局配置实例\"\"\"\n    global _global_config\n    if _global_config is None or _global_config.env != env:\n        _global_config = AIConfig(env)\n    return _global_config\n\n\ndef set_environment(env: Environment) -> None:\n    \"\"\"设置环境\"\"\"\n    global _global_config\n    _global_config = AIConfig(env)\n\n\n# 便捷函数\ndef get_api_key() -> str:\n    \"\"\"获取API密钥\"\"\"\n    return get_config().api_key\n\n\ndef get_model_name() -> str:\n    \"\"\"获取模型名称\"\"\"\n    return get_config().model_name\n\n\ndef get_api_url() -> str:\n    \"\"\"获取API URL\"\"\"\n    return get_config().api_url\n\n\nif __name__ == \"__main__\":\n    # 测试配置\n    config = get_config()\n    print(\"AI配置信息:\")\n    print(f\"环境: {config.env.value}\")\n    print(f\"提供商: {config.provider}\")\n    print(f\"模型: {config.model_name}\")\n    print(f\"API URL: {config.api_url}\")\n    print(f\"超时: {config.timeout}秒\")\n    print(f\"重试: {config.max_retries}次\")\n    print(f\"调试: {config.debug}\")\n"}}}}