修复: DeepSeek reasoning_content 全链路透传(跨6 crate补字段+映射+agentic loop累积回传)

crates/df-ai/src/anthropic_compat.rs

@@ -109,7 +109,7 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
     let v: serde_json::Value = match serde_json::from_str(data) {
         Ok(v) => v,
         Err(_) => {
-            return StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
+            return StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None }
         }
     };
     let ty = v.get("type").and_then(|t| t.as_str()).unwrap_or("");
@@ -128,7 +128,7 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                     total_tokens: inp as u32,
                 });
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None }
         }
         // 消息增量：output_tokens 是累计值（非增量），直接覆盖 completion + 重算 total
         "message_delta" => {
@@ -138,14 +138,14 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                 acc.completion_tokens = out as u32;
                 acc.total_tokens = acc.prompt_tokens + acc.completion_tokens;
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None }
         }
         // 文本增量
         "content_block_delta" => {
             if let Some(delta) = v.get("delta") {
                 if delta.get("type").and_then(|t| t.as_str()) == Some("text_delta") {
                     let text = delta.get("text").and_then(|t| t.as_str()).unwrap_or("").to_string();
-                    return StreamChunk { delta: text, finished: false, tool_calls: None, usage: None, error: None };
+                    return StreamChunk { delta: text, finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None };
                 }
                 // 工具入参增量
                 if delta.get("type").and_then(|t| t.as_str()) == Some("input_json_delta") {
@@ -162,10 +162,11 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                         }]),
                         usage: None,
                         error: None,
+                        reasoning_content: None,
                     };
                 }
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None }
         }
         // 工具块开始：带 id + name
         "content_block_start" => {
@@ -194,10 +195,11 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                         }]),
                         usage: None,
                         error: None,
+                        reasoning_content: None,
                     };
                 }
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None }
         }
         // 消息结束：带出累积 usage
         "message_stop" => StreamChunk {
@@ -206,16 +208,17 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
             tool_calls: None,
             usage: usage_accum.take(),
             error: None,
+            reasoning_content: None,
         },
         // 错误事件：流中途出错。不走 finished 完成路径（避免残缺响应被当正常完成入库），
         // 改由 stream_llm 识别 error 非空 → 发 AiError + 丢弃残缺（与 OpenAI 路径 Err 一致）。
         "error" => {
             let msg = v.get("error").and_then(|e| e.get("message")).and_then(|m| m.as_str()).unwrap_or("stream error").to_string();
             error!(%msg, "Anthropic 流式错误事件");
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: Some(msg) }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: Some(msg), reasoning_content: None }
         }
         // content_block_stop / ping 等不产出 chunk
-        _ => StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None },
+        _ => StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None, reasoning_content: None },
     }
 }
 
@@ -541,6 +544,7 @@ impl LlmProvider for AnthropicCompatProvider {
                     model: resp.model,
                     usage,
                     tool_calls: if tool_calls.is_empty() { None } else { Some(tool_calls) },
+                    reasoning_content: None,
                 })
             }
         })
@@ -808,6 +812,7 @@ mod tests {
             stream: false,
             tools: None,
             tool_choice: None,
+            reasoning_content: None,
         };
         let body = provider.convert_request(req);
         // user 消息 content 应为数组形态
@@ -839,6 +844,7 @@ mod tests {
             stream: false,
             tools: None,
             tool_choice: None,
+            reasoning_content: None,
         };
         let body = provider.convert_request(req);
         let user_msg = body