diff --git a/python/sglang/srt/managers/scheduler.py b/python/sglang/srt/managers/scheduler.py
index 91c3c01b8..655b39a4e 100644
--- a/python/sglang/srt/managers/scheduler.py
+++ b/python/sglang/srt/managers/scheduler.py
@@ -273,6 +273,48 @@ class Scheduler(
 ):
     """A scheduler that manages a tensor parallel GPU worker."""
 
+    def launch_draft_worker(
+        self, gpu_id, tp_rank, moe_ep_rank, server_args, port_args, dp_rank
+    ):
+        if self.spec_algorithm.is_eagle():
+            from sglang.srt.speculative.eagle_worker import EAGLEWorker
+
+            self.draft_worker = EAGLEWorker(
+                gpu_id=gpu_id,
+                tp_rank=tp_rank,
+                moe_ep_rank=moe_ep_rank,
+                server_args=server_args,
+                nccl_port=port_args.nccl_port,
+                target_worker=self.tp_worker,
+                dp_rank=dp_rank,
+            )
+        elif self.spec_algorithm.is_standalone():
+            from sglang.srt.speculative.standalone_worker import StandaloneWorker
+
+            self.draft_worker = StandaloneWorker(
+                gpu_id=gpu_id,
+                tp_rank=tp_rank,
+                moe_ep_rank=moe_ep_rank,
+                server_args=server_args,
+                nccl_port=port_args.nccl_port,
+                target_worker=self.tp_worker,
+                dp_rank=dp_rank,
+            )
+        elif self.spec_algorithm.is_ngram():
+            from sglang.srt.speculative.ngram_worker import NGRAMWorker
+
+            self.draft_worker = NGRAMWorker(
+                gpu_id=gpu_id,
+                tp_rank=tp_rank,
+                moe_ep_rank=moe_ep_rank,
+                server_args=server_args,
+                nccl_port=port_args.nccl_port,
+                target_worker=self.tp_worker,
+                dp_rank=dp_rank,
+            )
+        else:
+            self.draft_worker = None
+
     def __init__(
         self,
         server_args: ServerArgs,
@@ -412,44 +454,9 @@ class Scheduler(
         )
 
         # Launch a draft worker for speculative decoding
-        if self.spec_algorithm.is_eagle():
-            from sglang.srt.speculative.eagle_worker import EAGLEWorker
-
-            self.draft_worker = EAGLEWorker(
-                gpu_id=gpu_id,
-                tp_rank=tp_rank,
-                moe_ep_rank=moe_ep_rank,
-                server_args=server_args,
-                nccl_port=port_args.nccl_port,
-                target_worker=self.tp_worker,
-                dp_rank=dp_rank,
-            )
-        elif self.spec_algorithm.is_standalone():
-            from sglang.srt.speculative.standalone_worker import StandaloneWorker
-
-            self.draft_worker = StandaloneWorker(
-                gpu_id=gpu_id,
-                tp_rank=tp_rank,
-                moe_ep_rank=moe_ep_rank,
-                server_args=server_args,
-                nccl_port=port_args.nccl_port,
-                target_worker=self.tp_worker,
-                dp_rank=dp_rank,
-            )
-        elif self.spec_algorithm.is_ngram():
-            from sglang.srt.speculative.ngram_worker import NGRAMWorker
-
-            self.draft_worker = NGRAMWorker(
-                gpu_id=gpu_id,
-                tp_rank=tp_rank,
-                moe_ep_rank=moe_ep_rank,
-                server_args=server_args,
-                nccl_port=port_args.nccl_port,
-                target_worker=self.tp_worker,
-                dp_rank=dp_rank,
-            )
-        else:
-            self.draft_worker = None
+        self.launch_draft_worker(
+            gpu_id, tp_rank, moe_ep_rank, server_args, port_args, dp_rank
+        )
 
         # Dispatch the model worker
         if self.spec_algorithm.is_none():