[Bugfix] Relax lang pin for voxtral (#21833)

Signed-off-by: Sanchit Gandhi <sgandhi3141@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

vllm/model_executor/models/voxtral.py

@@ -26,8 +26,7 @@ from vllm.logger import init_logger
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 from vllm.model_executor.models import SupportsPP
 # yapf: disable
-from vllm.model_executor.models.whisper import (
-    WhisperEncoder, WhisperForConditionalGeneration)
+from vllm.model_executor.models.whisper import WhisperEncoder
 # yapf: enable
 from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.multimodal import MULTIMODAL_REGISTRY
@@ -50,6 +49,18 @@ from .utils import (flatten_bn, init_vllm_registered_model, maybe_prefix,
 
 logger = init_logger(__name__)
 
+ISO639_1_SUPPORTED_LANGS = {
+    "ar": "Arabic",
+    "nl": "Dutch",
+    "en": "English",
+    "fr": "French",
+    "de": "German",
+    "hi": "Hindi",
+    "it": "Italian",
+    "pt": "Portuguese",
+    "es": "Spanish",
+}
+
 
 class VoxtralProcessorAdapter:
     """
@@ -301,6 +312,7 @@ class VoxtralMultiModalProcessor(BaseMultiModalProcessor[VoxtralProcessingInfo]
                                         dummy_inputs=VoxtralDummyInputsBuilder)
 class VoxtralForConditionalGeneration(nn.Module, SupportsMultiModal,
                                       SupportsPP, SupportsTranscription):
+    supported_languages = ISO639_1_SUPPORTED_LANGS
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()
@@ -441,8 +453,8 @@ class VoxtralForConditionalGeneration(nn.Module, SupportsMultiModal,
     # for speech-to-text transcription
     def get_generation_prompt(cls, audio: np.ndarray,
                               model_config: ModelConfig,
-                              stt_config: SpeechToTextConfig, language: str,
-                              task_type: str,
+                              stt_config: SpeechToTextConfig,
+                              language: Optional[str], task_type: str,
                               request_prompt: str) -> PromptType:
         tokenizer = cached_tokenizer_from_config(model_config)
         audio = Audio(audio, int(stt_config.sample_rate),
@@ -457,11 +469,6 @@ class VoxtralForConditionalGeneration(nn.Module, SupportsMultiModal,
         prompts_dict["prompt_token_ids"] = tokenized.tokens
         return cast(PromptType, prompts_dict)
 
-    @classmethod
-    def validate_language(cls, language: str) -> bool:
-        # same as whisper
-        return WhisperForConditionalGeneration.validate_language(language)
-
     @classmethod
     def get_num_audio_tokens(cls, audio_duration_s: float,
                              stt_config: SpeechToTextConfig,