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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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