[Frontend] Add max-completion-token option to transcription/translation endpoints (#30769)

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

vllm/entrypoints/openai/protocol.py

@@ -2054,6 +2054,9 @@ class TranscriptionRequest(OpenAIBaseModel):
 
     presence_penalty: float | None = 0.0
     """The presence penalty to use for sampling."""
+
+    max_completion_tokens: int | None = None
+    """The maximum number of tokens to generate."""
     # --8<-- [end:transcription-sampling-params]
 
     # Default sampling parameters for transcription requests.
@@ -2300,6 +2303,9 @@ class TranslationRequest(OpenAIBaseModel):
     # Flattened stream option to simplify form data.
     stream_include_usage: bool | None = False
     stream_continuous_usage_stats: bool | None = False
+
+    max_completion_tokens: int | None = None
+    """The maximum number of tokens to generate."""
     # --8<-- [end:translation-extra-params]
 
     # Default sampling parameters for translation requests.

vllm/entrypoints/openai/speech_to_text.py

@@ -293,8 +293,14 @@ class OpenAISpeechToText(OpenAIServing):
         try:
             # Unlike most decoder-only models, whisper generation length is not
             # constrained by the size of the input audio, which is mapped to a
-            # fixed-size log-mel-spectogram.
-            default_max_tokens = self.model_config.max_model_len
+            # fixed-size log-mel-spectogram. Still, allow for fewer tokens to be
+            # generated by respecting the extra completion tokens arg.
+            if request.max_completion_tokens is None:
+                default_max_tokens = self.model_config.max_model_len
+            else:
+                default_max_tokens = min(
+                    self.model_config.max_model_len, request.max_completion_tokens
+                )
             sampling_params = request.to_sampling_params(
                 default_max_tokens, self.default_sampling_params
             )