Spaces:
Running
Running
Working spaces: xVASynth, MetaVoice, CoquiTTS
Browse files
app.py
CHANGED
@@ -31,12 +31,26 @@ with open('harvard_sentences.txt') as f:
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# Constants
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####################################
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AVAILABLE_MODELS = {
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'XTTSv2': 'xtts',
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'WhisperSpeech': 'whisperspeech',
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'ElevenLabs': 'eleven',
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'OpenVoice': 'openvoice',
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'Pheme': 'pheme',
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'MetaVoice': 'metavoice'
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}
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SPACE_ID = os.getenv('SPACE_ID')
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@@ -118,6 +132,7 @@ if not os.path.isfile(DB_PATH):
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# Create DB table (if doesn't exist)
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create_db_if_missing()
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# Sync local DB with remote repo every 5 minute (only if a change is detected)
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scheduler = CommitScheduler(
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repo_id=DB_DATASET_ID,
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@@ -133,7 +148,7 @@ scheduler = CommitScheduler(
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####################################
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# Router API
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####################################
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router = Client("TTS-AGI/tts-router", hf_token=
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####################################
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# Gradio app
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####################################
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@@ -291,6 +306,9 @@ model_licenses = {
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'metavoice': 'Apache 2.0',
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'elevenlabs': 'Proprietary',
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'whisperspeech': 'MIT',
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}
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model_links = {
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'styletts2': 'https://github.com/yl4579/StyleTTS2',
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@@ -564,7 +582,50 @@ def synthandreturn(text):
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def predict_and_update_result(text, model, result_storage):
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try:
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if model in AVAILABLE_MODELS:
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-
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else:
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result = router.predict(text, model.lower(), api_name="/synthesize")
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except:
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@@ -593,6 +654,30 @@ def synthandreturn(text):
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# doloudnorm(result)
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# except:
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# pass
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results = {}
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thread1 = threading.Thread(target=predict_and_update_result, args=(text, mdl1, results))
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thread2 = threading.Thread(target=predict_and_update_result, args=(text, mdl2, results))
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# Constants
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####################################
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AVAILABLE_MODELS = {
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# 'XTTSv2': 'xtts',
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# 'WhisperSpeech': 'whisperspeech',
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# 'ElevenLabs': 'eleven',
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# 'OpenVoice': 'openvoice',
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# 'Pheme': 'pheme',
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# 'MetaVoice': 'metavoice'
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# '<Space>': func#<return-index-of-audio-param>
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# 'coqui/xtts': '1#1', #FIXME: Space defaults
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# 'collabora/WhisperSpeech': '/whisper_speech_demo#0', #FIXME: invalid url for third param
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# 'myshell-ai/OpenVoice': '1#1', #FIXME: example audio path
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# 'PolyAI/pheme': 'PolyAI/pheme', #FIXME
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'mrfakename/MetaVoice-1B-v0.1': '/tts#0',
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# xVASynth (CPU)
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'Pendrokar/xVASynth': '/predict#0',
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# CoquiTTS (CPU)
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'coqui/CoquiTTS': '0#0',
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# 'pytorch/Tacotron2': '0#0', #old gradio
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}
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SPACE_ID = os.getenv('SPACE_ID')
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# Create DB table (if doesn't exist)
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create_db_if_missing()
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hf_token = os.getenv('HF_TOKEN')
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# Sync local DB with remote repo every 5 minute (only if a change is detected)
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scheduler = CommitScheduler(
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repo_id=DB_DATASET_ID,
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####################################
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# Router API
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####################################
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# router = Client("TTS-AGI/tts-router", hf_token=hf_token)
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####################################
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# Gradio app
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####################################
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'metavoice': 'Apache 2.0',
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'elevenlabs': 'Proprietary',
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'whisperspeech': 'MIT',
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'Pendrokar/xVASynth': 'GPT3',
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'Pendrokar/xVASynthStreaming': 'GPT3',
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}
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model_links = {
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'styletts2': 'https://github.com/yl4579/StyleTTS2',
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def predict_and_update_result(text, model, result_storage):
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try:
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if model in AVAILABLE_MODELS:
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if '/' in model:
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# Use public HF Space
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mdl_space = Client(model, hf_token=hf_token)
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# assume the index is one of the first 9 return params
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return_audio_index = int(AVAILABLE_MODELS[model][-1])
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endpoints = mdl_space.view_api(all_endpoints=True, print_info=False, return_format='dict')
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# has named endpoint
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if '/' == AVAILABLE_MODELS[model][:1]:
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# assume the index is one of the first 9 params
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api_name = AVAILABLE_MODELS[model][:-2]
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space_inputs = _get_param_examples(
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endpoints['named_endpoints'][api_name]['parameters']
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)
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# force text to the text input
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space_inputs[0] = text
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# print(space_inputs)
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results = mdl_space.predict(*space_inputs, api_name=api_name)
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# has unnamed endpoint
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else:
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# endpoint index is the first character
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fn_index = int(AVAILABLE_MODELS[model][0])
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space_inputs = _get_param_examples(
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endpoints['unnamed_endpoints'][str(fn_index)]['parameters']
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)
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# force text
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space_inputs[0] = text
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# OpenVoice
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# space_inputs[2] = "examples/speaker2.mp3"
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results = mdl_space.predict(*space_inputs, fn_index=fn_index)
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# return path to audio
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result = results[return_audio_index] if (not isinstance(results, str)) else results
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else:
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# Use the private HF Space
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result = router.predict(text, AVAILABLE_MODELS[model].lower(), api_name="/synthesize")
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else:
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result = router.predict(text, model.lower(), api_name="/synthesize")
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except:
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# doloudnorm(result)
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# except:
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# pass
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def _get_param_examples(parameters):
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example_inputs = []
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for param_info in parameters:
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if (
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param_info['component'] == 'Radio'
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or param_info['component'] == 'Dropdown'
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or param_info['component'] == 'Audio'
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or param_info['python_type']['type'] == 'str'
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):
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example_inputs.append(str(param_info['example_input']))
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continue
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if param_info['python_type']['type'] == 'int':
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example_inputs.append(int(param_info['example_input']))
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continue
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if param_info['python_type']['type'] == 'float':
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example_inputs.append(float(param_info['example_input']))
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continue
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if param_info['python_type']['type'] == 'bool':
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example_inputs.append(bool(param_info['example_input']))
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continue
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return example_inputs
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results = {}
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thread1 = threading.Thread(target=predict_and_update_result, args=(text, mdl1, results))
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thread2 = threading.Thread(target=predict_and_update_result, args=(text, mdl2, results))
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