import gradio as gr
import openai, subprocess
import os
# import config
# openai.api_key = config.OPENAI_API_KEY

messages = [{"role": "system", "content": 'You are a therapist. Respond to all input in 25 words or less.'}]

def transcribe(key, audio):
    openai.api_key = key
    global messages

    audio_filename_with_extension = audio + '.wav'
    os.rename(audio, audio_filename_with_extension)
    
    audio_file = open(audio_filename_with_extension, "rb")
    transcript = openai.Audio.transcribe("whisper-1", audio_file)

    messages.append({"role": "user", "content": transcript["text"]})

    response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages)

    system_message = response["choices"][0]["message"]
    messages.append(system_message)

    #subprocess.call(["say", system_message['content']])
    print("output: " + system_message['content'] + "\n")
    
    chat_transcript = ""
    for message in messages:
        if message['role'] != 'system':
            chat_transcript += message['role'] + ": " + message['content'] + "\n\n"

    return chat_transcript

# ui = gr.Interface(fn=transcribe, inputs=["text", gr.Audio(source="microphone", type="filepath")], outputs="text").launch()
keyTxt = gr.Textbox(
                        show_label=True,
                        placeholder=f"Your API-key...",
                        type="password",
                        visible=True,
                        label="API-Key",
                    )
ui = gr.Interface(fn=transcribe, inputs=[keyTxt, gr.Audio(source="microphone", type="filepath")], outputs="text").launch()

ui.launch()