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import whisper | |
import gradio as gr | |
import openai # all the required libraries are installed & imported | |
model = whisper.load_model("medium") | |
openai.api_key='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' | |
from whisper.transcribe import LANGUAGES | |
def voice_chat(ERDoctor_Input): | |
messages = [ | |
{"role": "system", "content": "You are a kind helpful assistant."}, | |
] | |
user_message = model.transcribe(ERDoctor_Input)["text"] | |
#reply = user_message | |
messages.append( | |
{"role": "user", "content": user_message}, | |
) | |
chat = openai.ChatCompletion.create( | |
model="gpt-3.5-turbo", messages=messages | |
) | |
reply = chat.choices[0].message.content | |
messages.append({"role": "assistant", "content": reply}) | |
return(reply) | |
text_reply = gr.Textbox(label="ChatGPT Text") | |
gr.Interface( | |
title = 'Open AI Whisper Speech Recognition V2', | |
fn=voice_chat, | |
inputs=[ | |
gr.Audio(source="microphone", type="filepath") | |
], | |
outputs=[ | |
text_reply | |
], live = True, | |
flagging_options= ["Incorrect Response"] | |
).launch() | |