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https://github.com/oobabooga/text-generation-webui.git
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Merge pull request #192 from xanthousm/main
Add text generation stream status to shared module, use for better TTS with auto-play
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commit
d8bea766d7
@ -1,21 +1,45 @@
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import re
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import time
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from pathlib import Path
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import gradio as gr
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import torch
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import modules.chat as chat
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import modules.shared as shared
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torch._C._jit_set_profiling_mode(False)
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params = {
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'activate': True,
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'speaker': 'en_56',
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'speaker': 'en_5',
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'language': 'en',
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'model_id': 'v3_en',
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'sample_rate': 48000,
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'device': 'cpu',
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'show_text': False,
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'autoplay': True,
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'voice_pitch': 'medium',
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'voice_speed': 'medium',
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}
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current_params = params.copy()
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voices_by_gender = ['en_99', 'en_45', 'en_18', 'en_117', 'en_49', 'en_51', 'en_68', 'en_0', 'en_26', 'en_56', 'en_74', 'en_5', 'en_38', 'en_53', 'en_21', 'en_37', 'en_107', 'en_10', 'en_82', 'en_16', 'en_41', 'en_12', 'en_67', 'en_61', 'en_14', 'en_11', 'en_39', 'en_52', 'en_24', 'en_97', 'en_28', 'en_72', 'en_94', 'en_36', 'en_4', 'en_43', 'en_88', 'en_25', 'en_65', 'en_6', 'en_44', 'en_75', 'en_91', 'en_60', 'en_109', 'en_85', 'en_101', 'en_108', 'en_50', 'en_96', 'en_64', 'en_92', 'en_76', 'en_33', 'en_116', 'en_48', 'en_98', 'en_86', 'en_62', 'en_54', 'en_95', 'en_55', 'en_111', 'en_3', 'en_83', 'en_8', 'en_47', 'en_59', 'en_1', 'en_2', 'en_7', 'en_9', 'en_13', 'en_15', 'en_17', 'en_19', 'en_20', 'en_22', 'en_23', 'en_27', 'en_29', 'en_30', 'en_31', 'en_32', 'en_34', 'en_35', 'en_40', 'en_42', 'en_46', 'en_57', 'en_58', 'en_63', 'en_66', 'en_69', 'en_70', 'en_71', 'en_73', 'en_77', 'en_78', 'en_79', 'en_80', 'en_81', 'en_84', 'en_87', 'en_89', 'en_90', 'en_93', 'en_100', 'en_102', 'en_103', 'en_104', 'en_105', 'en_106', 'en_110', 'en_112', 'en_113', 'en_114', 'en_115']
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wav_idx = 0
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voice_pitches = ['x-low', 'low', 'medium', 'high', 'x-high']
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voice_speeds = ['x-slow', 'slow', 'medium', 'fast', 'x-fast']
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last_msg_id = 0
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# Used for making text xml compatible, needed for voice pitch and speed control
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table = str.maketrans({
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"<": "<",
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">": ">",
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"&": "&",
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"'": "'",
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'"': """,
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})
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def xmlesc(txt):
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return txt.translate(table)
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def load_model():
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model, example_text = torch.hub.load(repo_or_dir='snakers4/silero-models', model='silero_tts', language=params['language'], speaker=params['model_id'])
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@ -33,12 +57,59 @@ def remove_surrounded_chars(string):
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new_string += char
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return new_string
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def remove_tts_from_history():
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suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''
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for i, entry in enumerate(shared.history['internal']):
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reply = entry[1]
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reply = re.sub("(<USER>|<user>|{{user}})", shared.settings[f'name1{suffix}'], reply)
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if shared.args.chat:
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reply = reply.replace('\n', '<br>')
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shared.history['visible'][i][1] = reply
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if shared.args.cai_chat:
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return chat.generate_chat_html(shared.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name1{suffix}'], shared.character)
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else:
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return shared.history['visible']
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def toggle_text_in_history():
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suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''
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audio_str='\n\n' # The '\n\n' used after </audio>
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if shared.args.chat:
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audio_str='<br><br>'
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if params['show_text']==True:
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#for i, entry in enumerate(shared.history['internal']):
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for i, entry in enumerate(shared.history['visible']):
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vis_reply = entry[1]
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if vis_reply.startswith('<audio'):
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reply = shared.history['internal'][i][1]
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reply = re.sub("(<USER>|<user>|{{user}})", shared.settings[f'name1{suffix}'], reply)
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if shared.args.chat:
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reply = reply.replace('\n', '<br>')
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shared.history['visible'][i][1] = vis_reply.split(audio_str,1)[0]+audio_str+reply
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else:
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for i, entry in enumerate(shared.history['visible']):
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vis_reply = entry[1]
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if vis_reply.startswith('<audio'):
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shared.history['visible'][i][1] = vis_reply.split(audio_str,1)[0]+audio_str
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if shared.args.cai_chat:
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return chat.generate_chat_html(shared.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name1{suffix}'], shared.character)
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else:
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return shared.history['visible']
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def input_modifier(string):
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"""
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This function is applied to your text inputs before
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they are fed into the model.
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"""
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# Remove autoplay from previous chat history
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if (shared.args.chat or shared.args.cai_chat)and len(shared.history['internal'])>0:
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[visible_text, visible_reply] = shared.history['visible'][-1]
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vis_rep_clean = visible_reply.replace('controls autoplay>','controls>')
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shared.history['visible'][-1] = [visible_text, vis_rep_clean]
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return string
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def output_modifier(string):
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@ -46,7 +117,7 @@ def output_modifier(string):
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This function is applied to the model outputs.
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"""
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global wav_idx, model, current_params
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global model, current_params
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for i in params:
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if params[i] != current_params[i]:
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@ -57,20 +128,34 @@ def output_modifier(string):
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if params['activate'] == False:
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return string
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orig_string = string
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string = remove_surrounded_chars(string)
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string = string.replace('"', '')
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string = string.replace('“', '')
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string = string.replace('\n', ' ')
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string = string.strip()
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silent_string = False # Used to prevent unnecessary audio file generation
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if string == '':
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string = 'empty reply, try regenerating'
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silent_string = True
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output_file = Path(f'extensions/silero_tts/outputs/{wav_idx:06d}.wav')
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model.save_wav(text=string, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
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pitch = params['voice_pitch']
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speed = params['voice_speed']
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prosody=f'<prosody rate="{speed}" pitch="{pitch}">'
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string = '<speak>'+prosody+xmlesc(string)+'</prosody></speak>'
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string = f'<audio src="file/{output_file.as_posix()}" controls></audio>'
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wav_idx += 1
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if not shared.still_streaming and not silent_string:
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output_file = Path(f'extensions/silero_tts/outputs/{shared.character}_{int(time.time())}.wav')
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model.save_wav(ssml_text=string, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
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autoplay_str = ' autoplay' if params['autoplay'] else ''
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string = f'<audio src="file/{output_file.as_posix()}" controls{autoplay_str}></audio>\n\n'
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else:
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# Placeholder so text doesn't shift around so much
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string = '<audio controls></audio>\n\n'
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if params['show_text']:
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string += orig_string
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return string
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@ -85,9 +170,36 @@ def bot_prefix_modifier(string):
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def ui():
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# Gradio elements
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activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
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voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
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with gr.Accordion("Silero TTS"):
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with gr.Row():
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activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
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autoplay = gr.Checkbox(value=params['autoplay'], label='Play TTS automatically')
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show_text = gr.Checkbox(value=params['show_text'], label='Show message text under audio player')
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voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
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with gr.Row():
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v_pitch = gr.Dropdown(value=params['voice_pitch'], choices=voice_pitches, label='Voice pitch')
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v_speed = gr.Dropdown(value=params['voice_speed'], choices=voice_speeds, label='Voice speed')
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with gr.Row():
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convert = gr.Button('Permanently replace chat history audio with message text')
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convert_confirm = gr.Button('Confirm (cannot be undone)', variant="stop", visible=False)
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convert_cancel = gr.Button('Cancel', visible=False)
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# Convert history with confirmation
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convert_arr = [convert_confirm, convert, convert_cancel]
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convert.click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, convert_arr)
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convert_confirm.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
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convert_confirm.click(remove_tts_from_history, [], shared.gradio['display'])
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convert_confirm.click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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convert_cancel.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
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# Toggle message text in history
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show_text.change(lambda x: params.update({"show_text": x}), show_text, None)
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show_text.change(toggle_text_in_history, [], shared.gradio['display'])
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show_text.change(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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# Event functions to update the parameters in the backend
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activate.change(lambda x: params.update({"activate": x}), activate, None)
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autoplay.change(lambda x: params.update({"autoplay": x}), autoplay, None)
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voice.change(lambda x: params.update({"speaker": x}), voice, None)
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v_pitch.change(lambda x: params.update({"voice_pitch": x}), v_pitch, None)
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v_speed.change(lambda x: params.update({"voice_speed": x}), v_speed, None)
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@ -11,6 +11,7 @@ is_RWKV = False
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history = {'internal': [], 'visible': []}
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character = 'None'
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stop_everything = False
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still_streaming = False
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# UI elements (buttons, sliders, HTML, etc)
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gradio = {}
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@ -187,6 +187,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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def generate_with_streaming(**kwargs):
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return Iteratorize(generate_with_callback, kwargs, callback=None)
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shared.still_streaming = True
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yield formatted_outputs(original_question, shared.model_name)
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with eval(f"generate_with_streaming({', '.join(generate_params)})") as generator:
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for output in generator:
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@ -196,13 +197,17 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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if not (shared.args.chat or shared.args.cai_chat):
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reply = original_question + apply_extensions(reply[len(question):], "output")
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yield formatted_outputs(reply, shared.model_name)
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if output[-1] == n:
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break
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yield formatted_outputs(reply, shared.model_name)
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shared.still_streaming = False
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yield formatted_outputs(reply, shared.model_name)
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# Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
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else:
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shared.still_streaming = True
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for i in range(max_new_tokens//8+1):
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clear_torch_cache()
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with torch.no_grad():
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@ -213,15 +218,18 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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if not (shared.args.chat or shared.args.cai_chat):
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reply = original_question + apply_extensions(reply[len(question):], "output")
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yield formatted_outputs(reply, shared.model_name)
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if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
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break
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yield formatted_outputs(reply, shared.model_name)
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input_ids = np.reshape(output, (1, output.shape[0]))
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if shared.soft_prompt:
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inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)
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shared.still_streaming = False
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yield formatted_outputs(reply, shared.model_name)
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finally:
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t1 = time.time()
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print(f"Output generated in {(t1-t0):.2f} seconds ({(len(output)-len(original_input_ids[0]))/(t1-t0):.2f} tokens/s, {len(output)-len(original_input_ids[0])} tokens)")
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