import openai
import gradio
#import pyttsx3


openai.api_key = "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"

messages = [{"role": "system", "content": "You are a medical experts that specializes in psycoterapist"}]
engine = pyttsx3.init()
def CustomChatGPT(user_input, command):
    messages.append({"role": "user", "content": user_input+command})
    response = openai.ChatCompletion.create(
        model = "gpt-3.5-turbo",
        messages = messages
    )
    ChatGPT_reply = response["choices"][0]["message"]["content"]
    messages.append({"role": "assistant", "content": ChatGPT_reply})
        # Set the engine properties
    engine.setProperty('rate', 150)
    engine.setProperty('volume', 1)

    # Convert text to speech
    #engine.say(ChatGPT_reply)
    #engine.runAndWait()
    return ChatGPT_reply

demo = gradio.Interface(
    fn=CustomChatGPT, 
    inputs = ["text", gradio.Radio(["Provide source of the information", "subtract", "multiply", "divide"])],
    outputs = "text", 
   
    title = "Psycology consultation")
    

demo.launch()