import logging from enum import Enum from pydantic import ( AnyUrl, ) from docling.datamodel.accelerator_options import AcceleratorDevice from docling.datamodel.pipeline_options_asr_model import ( # AsrResponseFormat, # ApiAsrOptions, InferenceAsrFramework, InlineAsrNativeWhisperOptions, TransformersModelType, ) _log = logging.getLogger(__name__) WHISPER_TINY = InlineAsrNativeWhisperOptions( repo_id="tiny", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) WHISPER_SMALL = InlineAsrNativeWhisperOptions( repo_id="small", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) WHISPER_MEDIUM = InlineAsrNativeWhisperOptions( repo_id="medium", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) WHISPER_BASE = InlineAsrNativeWhisperOptions( repo_id="base", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) WHISPER_LARGE = InlineAsrNativeWhisperOptions( repo_id="large", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) WHISPER_TURBO = InlineAsrNativeWhisperOptions( repo_id="turbo", inference_framework=InferenceAsrFramework.WHISPER, verbose=True, timestamps=True, word_timestamps=True, temperatue=0.0, max_new_tokens=256, max_time_chunk=30.0, ) class AsrModelType(str, Enum): WHISPER_TINY = "whisper_tiny" WHISPER_SMALL = "whisper_small" WHISPER_MEDIUM = "whisper_medium" WHISPER_BASE = "whisper_base" WHISPER_LARGE = "whisper_large" WHISPER_TURBO = "whisper_turbo"