Delete config.py

config.py

@@ -1,177 +0,0 @@
-from enum import Enum
-
-import os
-from typing import List, Dict, Literal
-
-
-class ModelConfig:
-    def __init__(self, name: str, url: str, path: str = None, type: str = "whisper", tokenizer_url: str = None):
-        """
-        Initialize a model configuration.
-
-        name: Name of the model
-        url: URL to download the model from
-        path: Path to the model file. If not set, the model will be downloaded from the URL.
-        type: Type of model. Can be whisper or huggingface.
-        """
-        self.name = name
-        self.url = url
-        self.path = path
-        self.type = type
-        self.tokenizer_url = tokenizer_url
-
-VAD_INITIAL_PROMPT_MODE_VALUES=["prepend_all_segments", "prepend_first_segment", "json_prompt_mode"]
-
-class VadInitialPromptMode(Enum):
-    PREPEND_ALL_SEGMENTS = 1
-    PREPREND_FIRST_SEGMENT = 2
-    JSON_PROMPT_MODE = 3
-
-    @staticmethod
-    def from_string(s: str):
-        normalized = s.lower() if s is not None and len(s) > 0 else None
-
-        if normalized == "prepend_all_segments":
-            return VadInitialPromptMode.PREPEND_ALL_SEGMENTS
-        elif normalized == "prepend_first_segment":
-            return VadInitialPromptMode.PREPREND_FIRST_SEGMENT
-        elif normalized == "json_prompt_mode":
-            return VadInitialPromptMode.JSON_PROMPT_MODE
-        elif normalized is not None and normalized != "":
-            raise ValueError(f"Invalid value for VadInitialPromptMode: {s}")
-        else:
-            return None
-
-class ApplicationConfig:
-    def __init__(self, models: Dict[Literal["whisper", "m2m100", "nllb", "mt5", "ALMA"], List[ModelConfig]],
-                 input_audio_max_duration: int = 600, share: bool = False, server_name: str = None, server_port: int = 7860, 
-                 queue_concurrency_count: int = 1, delete_uploaded_files: bool = True,
-                 whisper_implementation: str = "whisper", default_model_name: str = "medium", 
-                 default_nllb_model_name: str = "distilled-600M", default_vad: str = "silero-vad", 
-                 vad_parallel_devices: str = "", vad_cpu_cores: int = 1, vad_process_timeout: int = 1800, 
-                 auto_parallel: bool = False, output_dir: str = None,
-                 model_dir: str = None, device: str = None, 
-                 verbose: bool = True, task: str = "transcribe", language: str = None,
-                 vad_initial_prompt_mode: str = "prepend_first_segment ", 
-                 vad_merge_window: float = 5, vad_max_merge_size: float = 30,
-                 vad_padding: float = 1, vad_prompt_window: float = 3,
-                 temperature: float = 0, best_of: int = 5, beam_size: int = 5,
-                 patience: float = None, length_penalty: float = None,
-                 suppress_tokens: str = "-1", initial_prompt: str = None,
-                 condition_on_previous_text: bool = True, fp16: bool = True,
-                 compute_type: str = "float16", 
-                 temperature_increment_on_fallback: float = 0.2, compression_ratio_threshold: float = 2.4,
-                 logprob_threshold: float = -1.0, no_speech_threshold: float = 0.6,
-                 repetition_penalty: float = 1.0, no_repeat_ngram_size: int = 0,
-                 # Word timestamp settings
-                 word_timestamps: bool = False, prepend_punctuations: str = "\"\'“¿([{-",
-                 append_punctuations: str = "\"\'.。,，!！?？:：”)]}、", 
-                 highlight_words: bool = False,
-                 # Diarization
-                 auth_token: str = None, diarization: bool = False, diarization_speakers: int = 2,
-                 diarization_min_speakers: int = 1, diarization_max_speakers: int = 5,
-                 diarization_process_timeout: int = 60,
-                 # Translation
-                 translation_batch_size: int = 2,
-                 translation_no_repeat_ngram_size: int = 3,
-                 translation_num_beams: int = 2,
-                 ):
-        
-        self.models = models
-        
-        # WebUI settings
-        self.input_audio_max_duration = input_audio_max_duration
-        self.share = share
-        self.server_name = server_name
-        self.server_port = server_port
-        self.queue_concurrency_count = queue_concurrency_count
-        self.delete_uploaded_files = delete_uploaded_files
-
-        self.whisper_implementation = whisper_implementation
-        self.default_model_name = default_model_name
-        self.default_nllb_model_name = default_nllb_model_name
-        self.default_vad = default_vad
-        self.vad_parallel_devices = vad_parallel_devices
-        self.vad_cpu_cores = vad_cpu_cores
-        self.vad_process_timeout = vad_process_timeout
-        self.auto_parallel = auto_parallel
-        self.output_dir = output_dir
-
-        self.model_dir = model_dir
-        self.device = device
-        self.verbose = verbose
-        self.task = task
-        self.language = language
-        self.vad_initial_prompt_mode = vad_initial_prompt_mode
-        self.vad_merge_window = vad_merge_window
-        self.vad_max_merge_size = vad_max_merge_size
-        self.vad_padding = vad_padding
-        self.vad_prompt_window = vad_prompt_window
-        self.temperature = temperature
-        self.best_of = best_of
-        self.beam_size = beam_size
-        self.patience = patience
-        self.length_penalty = length_penalty
-        self.suppress_tokens = suppress_tokens
-        self.initial_prompt = initial_prompt
-        self.condition_on_previous_text = condition_on_previous_text
-        self.fp16 = fp16
-        self.compute_type = compute_type
-        self.temperature_increment_on_fallback = temperature_increment_on_fallback
-        self.compression_ratio_threshold = compression_ratio_threshold
-        self.logprob_threshold = logprob_threshold
-        self.no_speech_threshold = no_speech_threshold
-        self.repetition_penalty = repetition_penalty
-        self.no_repeat_ngram_size = no_repeat_ngram_size
-        
-        # Word timestamp settings
-        self.word_timestamps = word_timestamps
-        self.prepend_punctuations = prepend_punctuations
-        self.append_punctuations = append_punctuations
-        self.highlight_words = highlight_words
-        
-        # Diarization settings
-        self.auth_token = auth_token
-        self.diarization = diarization
-        self.diarization_speakers = diarization_speakers
-        self.diarization_min_speakers = diarization_min_speakers
-        self.diarization_max_speakers = diarization_max_speakers
-        self.diarization_process_timeout = diarization_process_timeout
-        # Translation
-        self.translation_batch_size = translation_batch_size
-        self.translation_no_repeat_ngram_size = translation_no_repeat_ngram_size
-        self.translation_num_beams = translation_num_beams
-
-    def get_model_names(self, name: str):
-        return [ x.name for x in self.models[name] ]
-
-    def update(self, **new_values):
-        result = ApplicationConfig(**self.__dict__)
-
-        for key, value in new_values.items():
-            setattr(result, key, value)
-        return result
-
-    @staticmethod
-    def create_default(**kwargs):
-        app_config = ApplicationConfig.parse_file(os.environ.get("WHISPER_WEBUI_CONFIG", "config.json5"))
-
-        # Update with kwargs
-        if len(kwargs) > 0:
-            app_config = app_config.update(**kwargs)
-        return app_config
-
-    @staticmethod
-    def parse_file(config_path: str):
-        import json5
-
-        with open(config_path, "r", encoding="utf-8") as f:
-            # Load using json5
-            data = json5.load(f)
-            data_models = data.pop("models", [])
-            models: Dict[Literal["whisper", "m2m100", "nllb", "mt5", "ALMA"], List[ModelConfig]] = {
-                key: [ModelConfig(**item) for item in value]
-                for key, value in data_models.items()
-            }
-
-            return ApplicationConfig(models, **data)