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mrolando
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56cf024
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Parent(s):
17295b2
added state
Browse files- __pycache__/tts.cpython-310.pyc +0 -0
- app.py +25 -11
__pycache__/tts.cpython-310.pyc
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Binary files a/__pycache__/tts.cpython-310.pyc and b/__pycache__/tts.cpython-310.pyc differ
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app.py
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@@ -28,17 +28,24 @@ def transcribe_speech(filepath):
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load_dotenv()
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openai.api_key = os.environ['OPENAI_API_KEY']
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=
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temperature=0.5,
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max_tokens=256
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).choices[0].message.content
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@@ -65,22 +72,29 @@ from tts import synthesize
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# wav,rate = TTSHubInterface.get_prediction(task, model, generator, sample)
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# return wav,rate
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def answer_question(filepath):
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transcription = transcribe_speech(filepath)
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response = query_chatgpt(transcription)
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# audio = synthesise(response)
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print(response)
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# audio, rate = syn_facebookmms(response)
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rate,audio = synthesize(response,1,"spa")
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print(audio)
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return rate,audio
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import gradio as gr
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with gr.Blocks() as demo:
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entrada = gr.Audio(source="microphone",type="filepath")
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boton = gr.Button("Responder")
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salida = gr.Audio()
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boton.click(answer_question,entrada,salida)
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demo.launch(debug=True)
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load_dotenv()
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openai.api_key = os.environ['OPENAI_API_KEY']
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def clear_chat():
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global chat_history
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chat_history=[]
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def query_chatgpt(message,chat_history):
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chat_history.append({'role': 'user', 'content': '{}'.format(message)})
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print("Preguntando "+message)
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print("historial", chat_history)
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages= chat_history,
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temperature=0.5,
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max_tokens=256
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).choices[0].message.content
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chat_history.append({'role': 'assistant', 'content': '{}'.format(response)})
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return response, chat_history
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# wav,rate = TTSHubInterface.get_prediction(task, model, generator, sample)
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# return wav,rate
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def answer_question(filepath,chat_history):
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transcription = transcribe_speech(filepath)
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response,chat_history = query_chatgpt(transcription,chat_history)
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print("historial",chat_history)
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# audio = synthesise(response)
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# audio, rate = syn_facebookmms(response)
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rate,audio = synthesize(response,1,"spa")
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print(audio)
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return rate,audio
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def reset_state(chat_history):
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chat_history = []
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return chat_history
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import gradio as gr
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with gr.Blocks() as demo:
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chat_history = gr.State([])
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entrada = gr.Audio(source="microphone",type="filepath")
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boton = gr.Button("Responder")
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button = gr.Button("Reset State")
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salida = gr.Audio()
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boton.click(answer_question,[entrada,chat_history],salida)
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button.click(reset_state,chat_history,chat_history)
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demo.launch(debug=True)
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