diff --git a/vllm/lora/models.py b/vllm/lora/models.py
index 46cce598121cd..6afc73d2b04e5 100644
--- a/vllm/lora/models.py
+++ b/vllm/lora/models.py
@@ -385,15 +385,16 @@ class LoRAModelManager(AdapterModelManager):
                 self.info, "get_num_mm_encoder_tokens")
         else:
             self.supports_mm_lora = False
-        if self.supports_mm_lora:
+        if self.supports_mm_lora: # 从init传进来就可以了，不需要model_config了
             self.mm_mapping: MultiModelKeys = self.model.get_mm_mapping()
             self.mm_config = model_config.multimodal_config
-            limit_per_prompt: int = max(
-                [1] + \
-                list(self.mm_config.limit_per_prompt.values())
-                )
+            # limit_per_prompt: int = max(
+            #     self.info.get_allowed_mm_limits().values())
+            limit_per_prompt = 5
 
             # For vision tower
+            # max_num_batched_tokens = encoder_budget
+            # max_batches = max_batches * limit_per_prompt
             self.mm_punica_wrapper_mapping = {
                 name:
                 get_punica_wrapper(
@@ -411,8 +412,13 @@ class LoRAModelManager(AdapterModelManager):
                     self.mm_mapping.language_model[0]: self.punica_wrapper
                 }
             )
-            # For other
-            # TODO
+            # TODO Connector is not supported at the moment.
+            self.mm_punica_wrapper_mapping.update(
+                {
+                    name: None
+                    for name in self.mm_mapping.connector
+                }
+            )
 
         self.is_pooling_model = is_pooling_model(self.model)
         self.packed_modules: dict[str, list[str]] = {}
@@ -702,15 +708,17 @@ class LoRAModelManager(AdapterModelManager):
 
     def _get_mm_punica_wrapper(self, module_name: str) -> PunicaWrapperBase:
         """
-        TODO
+        Match the corresponding punica_wrapper based on module_name, 
+        and return None if lora is not supported for this module.
         """
         if self.supports_mm_lora:
-            for (
-                    prefix,
-                    punica_wrapper,
-            ) in self.mm_punica_wrapper_mapping.items():
+            # Ensure matching by the longest prefix.
+            sorted_prefixes = sorted(self.mm_punica_wrapper_mapping.keys(), 
+                                     key=lambda x: len(x), reverse=True)
+
+            for prefix in sorted_prefixes:
                 if module_name.startswith(prefix):
-                    return punica_wrapper
+                    return self.mm_punica_wrapper_mapping[prefix]
         return None
 
     def _register_packed_modules(self, module_full_name: str) -> None:
diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index 43620a0cc2d67..a8a513fd57aad 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -2271,7 +2271,9 @@ class GPUModelRunner(LoRAModelRunnerMixin):
                 mm_counts={
                     dummy_data_modality: 1
                 },
-            ).multi_modal_data
+            )
+            dummy_mm_kwargs = dummy_mm_data.multi_modal_data
+            dummy_mm_token_ids = dummy_mm_data.multi_modal_token_ids
 
             batched_dummy_mm_inputs = MultiModalKwargs.batch(
                 [dummy_mm_kwargs] * max_num_mm_items,