mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-30 03:18:57 +01:00
120 lines
5.6 KiB
Python
120 lines
5.6 KiB
Python
import base64
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import gc
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import io
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from pathlib import Path
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import gradio as gr
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import numpy as np
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import torch
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import whisper
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from pydub import AudioSegment
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from modules import shared
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input_hijack = {
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'state': False,
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'value': ["", ""]
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}
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# parameters which can be customized in settings.yaml of webui
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params = {
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'whipser_language': 'english',
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'whipser_model': 'small.en',
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'auto_submit': True
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}
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startup_device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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WHISPERMODEL = whisper.load_model(params['whipser_model'], device=startup_device)
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def chat_input_modifier(text, visible_text, state):
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global input_hijack
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if input_hijack['state']:
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input_hijack['state'] = False
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return input_hijack['value']
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else:
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return text, visible_text
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def do_stt(audio, whipser_language):
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# use pydub to convert sample_rate and sample_width for whisper input
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dubaudio = AudioSegment.from_file(io.BytesIO(audio))
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dubaudio = dubaudio.set_channels(1)
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dubaudio = dubaudio.set_frame_rate(16000)
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dubaudio = dubaudio.set_sample_width(2)
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# same method to get the array as openai whisper repo used from wav file
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audio_np = np.frombuffer(dubaudio.raw_data, np.int16).flatten().astype(np.float32) / 32768.0
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if len(whipser_language) == 0:
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result = WHISPERMODEL.transcribe(audio=audio_np)
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else:
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result = WHISPERMODEL.transcribe(audio=audio_np, language=whipser_language)
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return result["text"]
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def auto_transcribe(audio, auto_submit, whipser_language):
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if audio is None or audio == "":
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print("Whisper received no audio data")
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return "", ""
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audio_bytes = base64.b64decode(audio.split(',')[1])
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transcription = do_stt(audio_bytes, whipser_language)
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if auto_submit:
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input_hijack.update({"state": True, "value": [transcription, transcription]})
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return transcription
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def reload_whispermodel(whisper_model_name: str, whisper_language: str, device: str):
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if len(whisper_model_name) > 0:
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global WHISPERMODEL
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WHISPERMODEL = None
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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gc.collect()
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if device != "none":
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if device == "cuda":
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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WHISPERMODEL = whisper.load_model(whisper_model_name, device=device)
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params.update({"whipser_model": whisper_model_name})
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if ".en" in whisper_model_name:
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whisper_language = "english"
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audio_update = gr.Audio.update(interactive=True)
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else:
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audio_update = gr.Audio.update(interactive=False)
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return [whisper_model_name, whisper_language, str(device), audio_update]
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def ui():
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with gr.Accordion("Whisper STT", open=True):
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with gr.Row():
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audio = gr.Textbox(elem_id="audio-base64", visible=False)
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record_button = gr.Button("Rec.", elem_id="record-button", elem_classes="custom-button")
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with gr.Row():
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with gr.Accordion("Settings", open=False):
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auto_submit = gr.Checkbox(label='Submit the transcribed audio automatically', value=params['auto_submit'])
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device_dropd = gr.Dropdown(label='Device', value=str(startup_device), choices=["cuda", "cpu", "none"])
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whisper_model_dropd = gr.Dropdown(label='Whisper Model', value=params['whipser_model'], choices=["tiny.en", "base.en", "small.en", "medium.en", "tiny", "base", "small", "medium", "large"])
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whisper_language = gr.Dropdown(label='Whisper Language', value=params['whipser_language'], choices=["english", "chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese"])
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audio.change(
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auto_transcribe, [audio, auto_submit, whisper_language], [shared.gradio['textbox']]).then(
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None, auto_submit, None, _js="(check) => {if (check) { document.getElementById('Generate').click() }}")
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device_dropd.input(reload_whispermodel, [whisper_model_dropd, whisper_language, device_dropd], [whisper_model_dropd, whisper_language, device_dropd, audio])
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whisper_model_dropd.change(reload_whispermodel, [whisper_model_dropd, whisper_language, device_dropd], [whisper_model_dropd, whisper_language, device_dropd, audio])
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whisper_language.change(lambda x: params.update({"whipser_language": x}), whisper_language, None)
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auto_submit.change(lambda x: params.update({"auto_submit": x}), auto_submit, None)
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def custom_js():
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"""
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Returns custom javascript as a string. It is applied whenever the web UI is
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loaded.
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:return:
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"""
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with open(Path(__file__).parent.resolve() / "script.js", "r") as f:
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return f.read()
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