[Frontend] Abstract prompt and SpeechToTextConfig for transcriptions models (#20637)

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

vllm/config.py

@@ -4958,3 +4958,34 @@ def get_layers_from_vllm_config(vllm_config: VllmConfig,
         vllm_config.compilation_config.static_forward_context.items()
         if isinstance(layer, layer_type)
     }
+
+
+@config
+@dataclass
+class SpeechToTextConfig:
+    """Configuration for speech-to-text models."""
+
+    sample_rate: float = 16_000
+    """Sample rate (Hz) to resample input audio to. Most speech models expect
+    16kHz audio input. The input audio will be automatically resampled to this
+    rate before processing."""
+
+    max_audio_clip_s: int = 30
+    """Maximum duration in seconds for a single audio clip without chunking.
+    Audio longer than this will be split into smaller chunks if
+    `allow_audio_chunking` evaluates to True, otherwise it will be rejected."""
+
+    overlap_chunk_second: int = 1
+    """Overlap duration in seconds between consecutive audio chunks when
+    splitting long audio. This helps maintain context across chunk boundaries
+    and improves transcription quality at split points."""
+
+    min_energy_split_window_size: Optional[int] = 1600
+    """Window size in samples for finding low-energy (quiet) regions to split
+    audio chunks. The algorithm looks for the quietest moment within this
+    window to minimize cutting through speech. Default 1600 samples ≈ 100ms
+    at 16kHz. If None, no chunking will be done."""
+
+    @property
+    def allow_audio_chunking(self) -> bool:
+        return self.min_energy_split_window_size is not None