feat(llm): 添加 tracing 日志与 ContentField 扩展

为 OpenAI 消息类型引入 ContentField 以支持 string 和 array 两种 content 格式，新增 reasoning_content 字段；添加 tracing 日志初始化函数及请求
/响应日志；修正多处文件末尾换行与 import 顺序。

src/llm/provider/openai.rs

@@ -2,10 +2,11 @@ use std::time::Duration;
 
 use async_trait::async_trait;
 use reqwest::Client;
+use tracing::{debug, error, info};
 
+use super::LlmProvider;
 use crate::llm::error::LlmError;
 use crate::llm::types::{ChatRequest, ChatResponse, OpenaiChatResponse};
-use super::LlmProvider;
 
 pub struct OpenaiProvider {
     http_client: Client,
@@ -50,6 +51,8 @@ impl LlmProvider for OpenaiProvider {
     async fn chat(&self, request: ChatRequest) -> Result<ChatResponse, LlmError> {
         let url = format!("{}/chat/completions", self.base_url.trim_end_matches('/'));
 
+        info!(model = %request.model, max_tokens = request.max_tokens, temperature = request.temperature, "发送 LLM 请求");
+
         let response = self
             .http_client
             .post(&url)
@@ -57,7 +60,10 @@ impl LlmProvider for OpenaiProvider {
             .json(&request)
             .send()
             .await
-            .map_err(Self::map_reqwest_error)?;
+            .map_err(|e| {
+                error!(error = %e, "请求失败");
+                Self::map_reqwest_error(e)
+            })?;
 
         let status = response.status();
         let status_code: u16 = status.as_u16();
@@ -71,6 +77,8 @@ impl LlmProvider for OpenaiProvider {
                 .map(Duration::from_secs);
             let body_text = response.text().await.unwrap_or_default();
 
+            error!(status = status_code, body = %body_text, "请求失败");
+
             return match status_code {
                 401 => Err(LlmError::Authentication(body_text)),
                 429 => Err(LlmError::RateLimit { retry_after }),
@@ -91,11 +99,16 @@ impl LlmProvider for OpenaiProvider {
             };
         }
 
-        let chat_response: OpenaiChatResponse = response
-            .json()
-            .await
-            .map_err(|e| LlmError::Other(format!("响应解析失败: {}", e)))?;
+        let body_text = response.text().await.unwrap_or_default();
+        debug!(body = %body_text, "收到响应体");
+
+        let chat_response: OpenaiChatResponse = serde_json::from_str(&body_text).map_err(|e| {
+            error!(error = %e, body = %body_text, "响应解析失败");
+            LlmError::Other(format!("响应解析失败: {}", e))
+        })?;
+
+        debug!(response = ?chat_response, "收到 LLM 响应");
 
         Ok(ChatResponse::from(chat_response))
     }
-}
+}