feat(llm): 添加 Provider 工厂方法和枚举类型

- 新增 `ProviderType` 枚举和 `FromStr` 解析，支持通过环境变量选择 Provider
- 新增 `ProviderConfig` 结构体和 `create_provider` 工厂方法，统一 Provider 创建
- 更新示例代码使用新的工厂模式，移除直接实例化 OpenaiProvider 的方式
- 移除 Assistant 消息中未使用的 `reasoning_content` 字段

examples/simple_visit.rs

@@ -3,7 +3,7 @@ use std::env;
 use agcore::init_tracing;
 use agcore::llm::{
     cycle::{CycleConfig, LlmCycle},
-    provider::openai::OpenaiProvider,
+    provider::{create_provider, ProviderConfig, ProviderType},
     types::{ChatResponse, OpenaiContentPart},
 };
 
@@ -31,17 +31,30 @@ async fn main() {
 
     let api_key = env::var("OPENAI_API_KEY").expect("未设置 OPENAI_API_KEY 环境变量");
     let base_url = env::var("OPENAI_BASE_URL").expect("未设置 OPENAI_BASE_URL 环境变量");
-    let model = env::var("OPENAI_MODEL").expect("未设置 OPENAI_MODEL 环境变量选择所要使用的模型");
+    let model = env::var("OPENAI_MODEL").expect("未设置 OPENAI_MODEL 环境变量");
 
-    let provider = OpenaiProvider::new(base_url, api_key, model.clone());
+    let provider_type = env::var("PROVIDER")
-    let config = CycleConfig {
+        .unwrap_or_else(|_| "openai".into())
+        .parse::<ProviderType>()
+        .expect("无效的 PROVIDER 值");
+
+    let config = ProviderConfig {
+        base_url,
+        api_key,
+        model: model.clone(),
+    };
+
+    let provider = create_provider(provider_type, config)
+        .expect("创建 Provider 失败");
+
+    let cycle_config = CycleConfig {
         model,
         max_tokens: Some(65536),
         temperature: Some(1.3),
         ..CycleConfig::default()
     };
 
-    let mut cycle = LlmCycle::new(Box::new(provider), config)
+    let mut cycle = LlmCycle::new(provider, cycle_config)
         .with_system_prompt("你是一个简洁的助手，对于任何问题都是用一句话回答。".to_string());
 
     println!("发送请求...");

src/llm/provider.rs

@@ -4,6 +4,51 @@ use crate::llm::error::LlmError;
 use crate::llm::types::{ChatRequest, ChatResponse};
 use async_trait::async_trait;
 
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum ProviderType {
+    OpenAI,
+    DeepSeek,
+    Qwen,
+}
+
+impl std::str::FromStr for ProviderType {
+    type Err = String;
+
+    fn from_str(s: &str) -> Result<Self, Self::Err> {
+        match s.to_lowercase().as_str() {
+            "openai" => Ok(ProviderType::OpenAI),
+            "deepseek" => Ok(ProviderType::DeepSeek),
+            "qwen" | "dashscope" | "tongyi" => Ok(ProviderType::Qwen),
+            _ => Err(format!("未知的 Provider 类型: {}", s)),
+        }
+    }
+}
+
+pub struct ProviderConfig {
+    pub base_url: String,
+    pub api_key: String,
+    pub model: String,
+}
+
+pub fn create_provider(
+    provider_type: ProviderType,
+    config: ProviderConfig,
+) -> Result<Box<dyn LlmProvider>, LlmError> {
+    match provider_type {
+        ProviderType::OpenAI => Ok(Box::new(openai::OpenaiProvider::new(
+            config.base_url,
+            config.api_key,
+            config.model,
+        ))),
+        ProviderType::DeepSeek => {
+            unimplemented!("DeepSeek Provider 尚未实现")
+        }
+        ProviderType::Qwen => {
+            unimplemented!("Qwen Provider 尚未实现")
+        }
+    }
+}
+
 /// LLM Provider 抽象接口。
 ///
 /// 所有具体的 LLM 后端实现（OpenAI、Anthropic、Azure 等）

src/llm/types/message.rs

@@ -107,8 +107,6 @@ pub enum OpenaiChatMessage {
     Assistant {
         content: ContentField,
         #[serde(skip_serializing_if = "Option::is_none")]
-        reasoning_content: Option<String>,
-        #[serde(skip_serializing_if = "Option::is_none")]
         refusal: Option<String>,
         #[serde(skip_serializing_if = "Option::is_none")]
         name: Option<String>,
@@ -136,7 +134,6 @@ impl OpenaiChatMessage {
     pub fn assistant_text<S: Into<String>>(text: S) -> Self {
         OpenaiChatMessage::Assistant {
             content: ContentField::String(text.into()),
-            reasoning_content: None,
             refusal: None,
             name: None,
             tool_calls: None,