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import gradio as gr import openai import pyttsx3 from dotenv import load_dotenv import os load_dotenv()

openai.api_key = os.getenv("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")

messages=[ {"role": "system", "content": "You are a teacher"} ] def transcribe(audio): global messages file = open(audio, "rb") transcription = openai.Audio.transcribe("whisper-1", file) print(transcription) messages.append({"role": "user", "content": transcription["text"]}) response = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=messages )

AImessage = response["choices"][0]["message"]["content"]
engine = pyttsx3.init()
engine.say(AImessage)
engine.runAndWait()
messages.append({"role": "assistant", "content": AImessage})
chat = ''
for message in messages:
    if message["role"] != 'system':
        chat += message["role"] + ':' + message["content"] + "\n\n"
return chat

ui = gr.Interface(fn=transcribe ,inputs=gr.Audio(source='microphone',type='filepath'), outputs='text')

ui.launch()

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