完善消息链路trace并贯通AI与发送动作

utils/ai/unified_llm.py

@@ -15,6 +15,7 @@ from requests import HTTPError
 from loguru import logger
 
 from utils.ai.llm_registry import LLMRegistry
+from utils.trace_context import get_current_trace_id, format_trace_prefix
 
 
 class UnifiedLLMClient:
@@ -58,6 +59,7 @@ class UnifiedLLMClient:
         backend: str,
         scene: str,
         model: str,
+        trace_id: str,
         success: bool,
         latency_ms: float,
         error: str = "",
@@ -70,6 +72,7 @@ class UnifiedLLMClient:
                 "backend": str(backend or "").strip(),
                 "scene": str(scene or "").strip(),
                 "model": str(model or "").strip(),
+                "trace_id": str(trace_id or "").strip(),
                 "success": bool(success),
                 "latency_ms": round(float(latency_ms or 0.0), 2),
                 "error": str(error or "").strip()[:300],
@@ -236,6 +239,7 @@ class UnifiedLLMClient:
         started_at = time.monotonic()
         self.last_error = ""
         result: Optional[Dict[str, Any]] = None
+        current_trace_id = get_current_trace_id()
         if not self.is_available():
             self.last_error = "client_unavailable"
         elif self.provider == "dify":
@@ -272,10 +276,19 @@ class UnifiedLLMClient:
             backend=str(self.config.get("backend", "") or ""),
             scene=str(self.config.get("scene", "") or ""),
             model=self.model or str(self.mode or ""),
+            trace_id=current_trace_id,
             success=bool(result and result.get("text")),
             latency_ms=latency_ms,
             error=self.last_error,
         )
+        # 在统一出口补一条轻量 trace 日志，方便把“消息 -> AI 调用”快速串起来。
+        self.LOG.debug(
+            f"{format_trace_prefix(current_trace_id)}LLM调用结束 "
+            f"provider={self.provider} backend={self.config.get('backend', '') or '-'} "
+            f"scene={self.config.get('scene', '') or '-'} "
+            f"success={bool(result and result.get('text'))} latency_ms={round(latency_ms, 2)} "
+            f"error={self.last_error or '-'}"
+        )
         return result
 
     def _generate_openai(