diff --git a/vllm_spyre/core/scheduler.py b/vllm_spyre/core/scheduler.py
index 38adfa49a..2dc740c98 100644
--- a/vllm_spyre/core/scheduler.py
+++ b/vllm_spyre/core/scheduler.py
@@ -1267,7 +1267,6 @@ def schedule(
                     multi_modal_placeholders=(
                         seq_group.multi_modal_placeholders
                         if scheduler_outputs.num_prefill_groups > 0 else None),
-                    prompt_adapter_request=seq_group.prompt_adapter_request,
                 )
             else:
                 # When SPMD mode is enabled, we only send delta data except for
diff --git a/vllm_spyre/v1/worker/spyre_model_runner.py b/vllm_spyre/v1/worker/spyre_model_runner.py
index 6ef9025c2..71139b470 100644
--- a/vllm_spyre/v1/worker/spyre_model_runner.py
+++ b/vllm_spyre/v1/worker/spyre_model_runner.py
@@ -3,7 +3,7 @@
 from collections import deque
 from collections.abc import Iterable
 from dataclasses import asdict, dataclass
-from typing import TYPE_CHECKING, Optional, cast
+from typing import TYPE_CHECKING, Literal, Optional, cast, get_args
 
 import torch
 from torch import nn
@@ -34,6 +34,19 @@
 
 from vllm.v1.outputs import EMPTY_MODEL_RUNNER_OUTPUT, ModelRunnerOutput
 
+#############################################################
+# from vllm.tasks import GenerationTask, PoolingTask, SupportedTask
+# TODO: remove when we have this in vllm/tasks.py
+#############################################################
+GenerationTask = Literal["generate", "transcription"]
+GENERATION_TASKS = get_args(GenerationTask)
+
+PoolingTask = Literal["encode", "embed", "classify", "score"]
+POOLING_TASKS = get_args(PoolingTask)
+
+SupportedTask = Literal[GenerationTask]
+#############################################################
+
 logger = init_logger(__name__)
 
 
@@ -76,7 +89,6 @@ def __init__(
         self.scheduler_config = vllm_config.scheduler_config
         self.device_config = vllm_config.device_config
         self.speculative_config = vllm_config.speculative_config
-        self.prompt_adapter_config = vllm_config.prompt_adapter_config
         self.observability_config = vllm_config.observability_config
 
         self.pad_token_id = 0
@@ -375,6 +387,14 @@ def prepare_model_input(
         else:
             return self._prepare_decode(scheduler_output.scheduled_cached_reqs)
 
+    def get_supported_tasks(self) -> tuple[SupportedTask, ...]:
+        tasks = list[SupportedTask]()
+
+        if "generate" in self.model_config.supported_tasks:
+            tasks.extend(["generate"])
+
+        return tuple(tasks)
+
     @SpyrePlatform.inference_mode()
     def execute_model(
         self,
diff --git a/vllm_spyre/v1/worker/spyre_worker.py b/vllm_spyre/v1/worker/spyre_worker.py
index fbe69374e..3ac799d14 100644
--- a/vllm_spyre/v1/worker/spyre_worker.py
+++ b/vllm_spyre/v1/worker/spyre_worker.py
@@ -29,7 +29,8 @@
 from vllm_spyre.model_executor.model_loader import spyre_setup
 from vllm_spyre.platform import SpyrePlatform
 from vllm_spyre.v1.worker.spyre_model_runner import (
-    ContinuousBatchingSpyreModelRunner, StaticBatchingSpyreModelRunner)
+    ContinuousBatchingSpyreModelRunner, StaticBatchingSpyreModelRunner,
+    SupportedTask)
 
 logger = init_logger(__name__)
 
@@ -616,6 +617,9 @@ def do_metadata_broadcast(self) -> bool:
     def kv_cache(self) -> Optional[list[list[torch.Tensor]]]:
         return None
 
+    def get_supported_tasks(self) -> tuple[SupportedTask, ...]:
+        return self.model_runner.get_supported_tasks()
+
     @SpyrePlatform.inference_mode()
     def execute_model(
         self,
diff --git a/vllm_spyre/worker/spyre_embedding_model_runner.py b/vllm_spyre/worker/spyre_embedding_model_runner.py
index fe5c830b3..3be4e67c3 100644
--- a/vllm_spyre/worker/spyre_embedding_model_runner.py
+++ b/vllm_spyre/worker/spyre_embedding_model_runner.py
@@ -42,11 +42,20 @@ def __init__(
                          is_driver_worker=is_driver_worker)
 
         pooler_config = model_config.pooler_config
-        self.pooler = Pooler.from_config_with_defaults(
-            pooler_config,
-            pooling_type=PoolingType.CLS,
-            normalize=True,
-            softmax=False)
+        if hasattr(Pooler, "from_config_with_defaults"):
+            # TODO: remove this when we no longer support
+            # vllm version v0.9.2
+            self.pooler = Pooler.from_config_with_defaults(
+                pooler_config,
+                pooling_type=PoolingType.CLS,
+                normalize=True,
+                softmax=False)
+        else:
+            self.pooler = Pooler.for_embed(
+                pooler_config=pooler_config,
+                default_pooling_type=PoolingType.CLS,
+                default_normalize=True,
+                default_softmax=False)
 
     def load_model(self, prompt_lens: Iterable[int],
                    num_decode_tokens: Iterable[int]) -> None: