diff --git a/zhenxun/services/llm/config/__init__.py b/zhenxun/services/llm/config/__init__.py
index 778a04bd..09fd9599 100644
--- a/zhenxun/services/llm/config/__init__.py
+++ b/zhenxun/services/llm/config/__init__.py
@@ -12,14 +12,24 @@ from .generation import (
     validate_override_params,
 )
 from .presets import CommonOverrides
-from .providers import register_llm_configs
+from .providers import (
+    LLMConfig,
+    get_llm_config,
+    register_llm_configs,
+    set_default_model,
+    validate_llm_config,
+)
 
 __all__ = [
     "CommonOverrides",
+    "LLMConfig",
     "LLMGenerationConfig",
     "ModelConfigOverride",
     "apply_api_specific_mappings",
     "create_generation_config_from_kwargs",
+    "get_llm_config",
     "register_llm_configs",
+    "set_default_model",
+    "validate_llm_config",
     "validate_override_params",
 ]
diff --git a/zhenxun/services/llm/config/providers.py b/zhenxun/services/llm/config/providers.py
index bdb1c584..d16050a3 100644
--- a/zhenxun/services/llm/config/providers.py
+++ b/zhenxun/services/llm/config/providers.py
@@ -4,104 +4,326 @@ LLM 提供商配置管理
 负责注册和管理 AI 服务提供商的配置项。
 """
 
+from typing import Any
+
+from pydantic import BaseModel, Field
+
 from zhenxun.configs.config import Config
 from zhenxun.services.log import logger
 
-from ..types.models import ProviderConfig
+from ..types.models import ModelDetail, ProviderConfig
 
 AI_CONFIG_GROUP = "AI"
 PROVIDERS_CONFIG_KEY = "PROVIDERS"
 
 
+class LLMConfig(BaseModel):
+    """LLM 服务配置类"""
+
+    default_model_name: str | None = Field(
+        default=None,
+        description="LLM服务全局默认使用的模型名称 (格式: ProviderName/ModelName)",
+    )
+    proxy: str | None = Field(
+        default=None,
+        description="LLM服务请求使用的网络代理，例如 http://127.0.0.1:7890",
+    )
+    timeout: int = Field(default=180, description="LLM服务API请求超时时间（秒）")
+    max_retries_llm: int = Field(
+        default=3, description="LLM服务请求失败时的最大重试次数"
+    )
+    retry_delay_llm: int = Field(
+        default=2, description="LLM服务请求重试的基础延迟时间（秒）"
+    )
+    providers: list[ProviderConfig] = Field(
+        default_factory=list, description="配置多个 AI 服务提供商及其模型信息"
+    )
+
+    def get_provider_by_name(self, name: str) -> ProviderConfig | None:
+        """根据名称获取提供商配置
+
+        参数:
+            name: 提供商名称
+
+        返回:
+            ProviderConfig | None: 提供商配置，如果未找到则返回 None
+        """
+        for provider in self.providers:
+            if provider.name == name:
+                return provider
+        return None
+
+    def get_model_by_provider_and_name(
+        self, provider_name: str, model_name: str
+    ) -> tuple[ProviderConfig, ModelDetail] | None:
+        """根据提供商名称和模型名称获取配置
+
+        参数:
+            provider_name: 提供商名称
+            model_name: 模型名称
+
+        返回:
+            tuple[ProviderConfig, ModelDetail] | None: 提供商配置和模型详情的元组，
+                如果未找到则返回 None
+        """
+        provider = self.get_provider_by_name(provider_name)
+        if not provider:
+            return None
+
+        for model in provider.models:
+            if model.model_name == model_name:
+                return provider, model
+        return None
+
+    def list_available_models(self) -> list[dict[str, Any]]:
+        """列出所有可用的模型
+
+        返回:
+            list[dict[str, Any]]: 模型信息列表
+        """
+        models = []
+        for provider in self.providers:
+            for model in provider.models:
+                models.append(
+                    {
+                        "provider_name": provider.name,
+                        "model_name": model.model_name,
+                        "full_name": f"{provider.name}/{model.model_name}",
+                        "is_available": model.is_available,
+                        "is_embedding_model": model.is_embedding_model,
+                        "api_type": provider.api_type,
+                    }
+                )
+        return models
+
+    def validate_model_name(self, provider_model_name: str) -> bool:
+        """验证模型名称格式是否正确
+
+        参数:
+            provider_model_name: 格式为 "ProviderName/ModelName" 的字符串
+
+        返回:
+            bool: 是否有效
+        """
+        if not provider_model_name or "/" not in provider_model_name:
+            return False
+
+        parts = provider_model_name.split("/", 1)
+        if len(parts) != 2:
+            return False
+
+        provider_name, model_name = parts
+        return (
+            self.get_model_by_provider_and_name(provider_name, model_name) is not None
+        )
+
+
 def get_ai_config():
     """获取 AI 配置组"""
     return Config.get(AI_CONFIG_GROUP)
 
 
+def get_default_providers() -> list[dict[str, Any]]:
+    """获取默认的提供商配置
+
+    返回:
+        list[dict[str, Any]]: 默认提供商配置列表
+    """
+    return [
+        {
+            "name": "DeepSeek",
+            "api_key": "sk-******",
+            "api_base": "https://api.deepseek.com",
+            "api_type": "openai",
+            "models": [
+                {
+                    "model_name": "deepseek-chat",
+                    "max_tokens": 4096,
+                    "temperature": 0.7,
+                },
+                {
+                    "model_name": "deepseek-reasoner",
+                },
+            ],
+        },
+        {
+            "name": "GLM",
+            "api_key": "",
+            "api_base": "https://open.bigmodel.cn",
+            "api_type": "zhipu",
+            "models": [
+                {"model_name": "glm-4-flash"},
+                {"model_name": "glm-4-plus"},
+            ],
+        },
+        {
+            "name": "Gemini",
+            "api_key": [
+                "AIzaSy*****************************",
+                "AIzaSy*****************************",
+                "AIzaSy*****************************",
+            ],
+            "api_base": "https://generativelanguage.googleapis.com",
+            "api_type": "gemini",
+            "models": [
+                {"model_name": "gemini-2.0-flash"},
+                {"model_name": "gemini-2.5-flash-preview-05-20"},
+            ],
+        },
+    ]
+
+
 def register_llm_configs():
     """注册 LLM 服务的配置项"""
     logger.info("注册 LLM 服务的配置项")
+
+    llm_config = LLMConfig()
+    model_fields = LLMConfig.model_fields
+
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         "default_model_name",
-        None,
-        help="LLM服务全局默认使用的模型名称 (格式: ProviderName/ModelName)",
+        llm_config.default_model_name,
+        help=model_fields["default_model_name"].description,
         type=str,
     )
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         "proxy",
-        None,
-        help="LLM服务请求使用的网络代理，例如 http://127.0.0.1:7890",
+        llm_config.proxy,
+        help=model_fields["proxy"].description,
         type=str,
     )
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         "timeout",
-        180,
-        help="LLM服务API请求超时时间（秒）",
+        llm_config.timeout,
+        help=model_fields["timeout"].description,
         type=int,
     )
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         "max_retries_llm",
-        3,
-        help="LLM服务请求失败时的最大重试次数",
+        llm_config.max_retries_llm,
+        help=model_fields["max_retries_llm"].description,
         type=int,
     )
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         "retry_delay_llm",
-        2,
-        help="LLM服务请求重试的基础延迟时间（秒）",
+        llm_config.retry_delay_llm,
+        help=model_fields["retry_delay_llm"].description,
         type=int,
     )
+
     Config.add_plugin_config(
         AI_CONFIG_GROUP,
         PROVIDERS_CONFIG_KEY,
-        [
-            {
-                "name": "DeepSeek",
-                "api_key": "sk-******",
-                "api_base": "https://api.deepseek.com",
-                "api_type": "openai",
-                "models": [
-                    {
-                        "model_name": "deepseek-chat",
-                        "max_tokens": 4096,
-                        "temperature": 0.7,
-                    },
-                    {
-                        "model_name": "deepseek-reasoner",
-                    },
-                ],
-            },
-            {
-                "name": "GLM",
-                "api_key": "",
-                "api_base": "https://open.bigmodel.cn",
-                "api_type": "zhipu",
-                "models": [
-                    {"model_name": "glm-4-flash"},
-                    {"model_name": "glm-4-plus"},
-                ],
-            },
-            {
-                "name": "Gemini",
-                "api_key": [
-                    "AIzaSy*****************************",
-                    "AIzaSy*****************************",
-                    "AIzaSy*****************************",
-                ],
-                "api_base": "https://generativelanguage.googleapis.com",
-                "api_type": "gemini",
-                "models": [
-                    {"model_name": "gemini-2.0-flash"},
-                    {"model_name": "gemini-2.5-flash-preview-05-20"},
-                ],
-            },
-        ],
-        help="配置多个 AI 服务提供商及其模型信息 (列表)",
+        get_default_providers(),
+        help=model_fields["providers"].description,
         default_value=[],
         type=list[ProviderConfig],
     )
+
+
+def get_llm_config() -> LLMConfig:
+    """获取 LLM 配置实例
+
+    返回:
+        LLMConfig: LLM 配置实例
+    """
+    ai_config = get_ai_config()
+
+    config_data = {
+        "default_model_name": ai_config.get("default_model_name"),
+        "proxy": ai_config.get("proxy"),
+        "timeout": ai_config.get("timeout", 180),
+        "max_retries_llm": ai_config.get("max_retries_llm", 3),
+        "retry_delay_llm": ai_config.get("retry_delay_llm", 2),
+        "providers": ai_config.get(PROVIDERS_CONFIG_KEY, []),
+    }
+
+    return LLMConfig(**config_data)
+
+
+def validate_llm_config() -> tuple[bool, list[str]]:
+    """验证 LLM 配置的有效性
+
+    返回:
+        tuple[bool, list[str]]: (是否有效, 错误信息列表)
+    """
+    errors = []
+
+    try:
+        llm_config = get_llm_config()
+
+        if llm_config.timeout <= 0:
+            errors.append("timeout 必须大于 0")
+
+        if llm_config.max_retries_llm < 0:
+            errors.append("max_retries_llm 不能小于 0")
+
+        if llm_config.retry_delay_llm <= 0:
+            errors.append("retry_delay_llm 必须大于 0")
+
+        if not llm_config.providers:
+            errors.append("至少需要配置一个 AI 服务提供商")
+        else:
+            provider_names = set()
+            for provider in llm_config.providers:
+                if provider.name in provider_names:
+                    errors.append(f"提供商名称重复: {provider.name}")
+                provider_names.add(provider.name)
+
+                if not provider.api_key:
+                    errors.append(f"提供商 {provider.name} 缺少 API Key")
+
+                if not provider.models:
+                    errors.append(f"提供商 {provider.name} 没有配置任何模型")
+                else:
+                    model_names = set()
+                    for model in provider.models:
+                        if model.model_name in model_names:
+                            errors.append(
+                                f"提供商 {provider.name} 中模型名称重复: "
+                                f"{model.model_name}"
+                            )
+                        model_names.add(model.model_name)
+
+        if llm_config.default_model_name:
+            if not llm_config.validate_model_name(llm_config.default_model_name):
+                errors.append(
+                    f"默认模型 {llm_config.default_model_name} 在配置中不存在"
+                )
+
+    except Exception as e:
+        errors.append(f"配置解析失败: {e!s}")
+
+    return len(errors) == 0, errors
+
+
+def set_default_model(provider_model_name: str | None) -> bool:
+    """设置默认模型
+
+    参数:
+        provider_model_name: 模型名称，格式为 "ProviderName/ModelName"，None 表示清除
+
+    返回:
+        bool: 是否设置成功
+    """
+    if provider_model_name:
+        llm_config = get_llm_config()
+        if not llm_config.validate_model_name(provider_model_name):
+            logger.error(f"模型 {provider_model_name} 在配置中不存在")
+            return False
+
+    Config.set_config(
+        AI_CONFIG_GROUP, "default_model_name", provider_model_name, auto_save=True
+    )
+
+    if provider_model_name:
+        logger.info(f"默认模型已设置为: {provider_model_name}")
+    else:
+        logger.info("默认模型已清除")
+
+    return True