Trace scheduled, webhook, search, MCP and graph-extraction runs

run_agent_headless records each unattended run under its endpoint; the
scheduler passes its run id and the webhook worker its task id so Logs rows
can find their trace, while the LLM's own request id stays untouched for
quota counts. /api/search and MCP search_docs record their retrieval, and a
graph build records every extraction call under one step.

docsgpt/api/user/scheduler_worker.py

@@ -277,6 +277,8 @@ def execute_scheduled_run_body(run_id: str, celery_task_id: Optional[str]) -> Di
             endpoint="schedule",
             conversation_id=schedule.get("origin_conversation_id"),
             chat_history=chat_history,
+            # Links the run's execution trace to its Logs row.
+            request_id=str(run_id),
         )
     except SoftTimeLimitExceeded:
         timed_out = True