[Bugfix] Fix Qwen3ASR language asr tag in output (#33410)

Signed-off-by: NickLucche <nlucches@redhat.com>

vllm/model_executor/models/interfaces.py

@@ -1145,6 +1145,22 @@ class SupportsTranscription(Protocol):
         """
         return None
 
+    @classmethod
+    def post_process_output(cls, text: str) -> str:
+        """
+        Post-process the raw model output text.
+
+        Some ASR models output structured formats (e.g., language tags,
+        special tokens) that need to be stripped before returning to the user.
+
+        Args:
+            text: Raw decoded text from the model.
+
+        Returns:
+            Cleaned transcription text.
+        """
+        return text
+
 
 @overload
 def supports_transcription(

vllm/model_executor/models/qwen3_asr.py

@@ -90,6 +90,7 @@ from vllm.transformers_utils.processors.qwen3_asr import (
 )
 
 logger = init_logger(__name__)
+_ASR_TEXT_TAG = "<asr_text>"
 
 
 def _get_feat_extract_output_lengths(input_lengths: torch.Tensor):
@@ -556,7 +557,7 @@ class Qwen3ASRForConditionalGeneration(
         else:
             prompt = (
                 f"<|im_start|>user\n{audio_placeholder}<|im_end|>\n"
-                f"<|im_start|>assistant\nlanguage {full_lang_name_to}<asr_text>"
+                f"<|im_start|>assistant\nlanguage {full_lang_name_to}{_ASR_TEXT_TAG}"
             )
 
         prompt_token_ids = tokenizer.encode(prompt)
@@ -565,3 +566,21 @@ class Qwen3ASRForConditionalGeneration(
             "multi_modal_data": {"audio": audio},
         }
         return cast(PromptType, prompt_dict)
+
+    @classmethod
+    def post_process_output(cls, text: str) -> str:
+        """
+        Post-process Qwen3-ASR raw output to extract clean transcription.
+
+        The model outputs in format: "language {lang}<asr_text>{transcription}"
+        This method strips the language prefix and asr_text tags.
+        """
+        if not text:
+            return ""
+
+        if _ASR_TEXT_TAG not in text:
+            return text
+
+        # Split on <asr_text> tag and take the transcription part
+        _, text_part = text.rsplit(_ASR_TEXT_TAG, 1)
+        return text_part