[Bugfix] Add get_supported_tasks interface to fix broken CI (#2023)

### What this PR does / why we need it?
Added `get_supported_tasks` interface to adapt to vllm
[changes](46d81d6951 (diff-80ee7e2a62f9dcfbb8a312dc4e3948557e97ef187290daebbcae1e28596bda29))
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.9.2
- vLLM main:
5ac3168ee3

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

vllm_ascend/worker/model_runner_v1.py

@@ -92,6 +92,10 @@ if vllm_version_is("0.9.2"):
     from vllm.model_executor.models.interfaces import has_step_pooler
     from vllm.v1.utils import bind_kv_cache
 else:
+    from vllm.model_executor.models.interfaces import supports_transcription
+    from vllm.model_executor.models.interfaces_base import \
+        is_text_generation_model
+    from vllm.tasks import GenerationTask, SupportedTask
     from vllm.v1.worker.utils import bind_kv_cache
 
 if TYPE_CHECKING:
@@ -706,6 +710,31 @@ class NPUModelRunner(LoRAModelRunnerMixin):
     def get_model(self) -> nn.Module:
         return self.model
 
+    def get_supported_generation_tasks(self) -> "list[GenerationTask]":
+        model = self.get_model()
+        supported_tasks = list[GenerationTask]()
+
+        if is_text_generation_model(model):
+            supported_tasks.append("generate")
+
+        if supports_transcription(model):
+            if model.supports_transcription_only:
+                return ["transcription"]
+
+            supported_tasks.append("transcription")
+
+        return supported_tasks
+
+    def get_supported_tasks(self) -> "tuple[SupportedTask, ...]":
+        tasks = list[SupportedTask]()
+
+        if self.model_config.runner_type == "generate":
+            tasks.extend(self.get_supported_generation_tasks())
+        if self.model_config.runner_type == "pooling":
+            tasks.extend(self.get_supported_pooling_tasks())
+
+        return tuple(tasks)
+
     def _make_attention_mask(self, seq_lens, query_lens, position,
                              attn_state) -> torch.Tensor:
         # Chunk Prefill situation.

vllm_ascend/worker/worker_v1.py

@@ -41,9 +41,13 @@ from vllm.v1.worker.worker_base import WorkerBase
 from vllm_ascend.ascend_config import init_ascend_config
 from vllm_ascend.device_allocator.camem import CaMemAllocator
 from vllm_ascend.platform import NPUPlatform
-from vllm_ascend.utils import sleep_mode_enabled, try_register_lib
+from vllm_ascend.utils import (sleep_mode_enabled, try_register_lib,
+                               vllm_version_is)
 from vllm_ascend.worker.model_runner_v1 import NPUModelRunner
 
+if not vllm_version_is("0.9.2"):
+    from vllm.tasks import SupportedTask
+
 
 class NPUWorker(WorkerBase):
 
@@ -326,3 +330,6 @@ class NPUWorker(WorkerBase):
 
     def get_supported_pooling_tasks(self):
         return self.model_runner.get_supported_pooling_tasks()
+
+    def get_supported_tasks(self) -> "tuple[SupportedTask, ...]":
+        return self.model_runner.get_supported_tasks()