import os
import gradio as gr
import openai
from gtts import gTTS


openai.api_key = os.environ["OPEN_AI_KEY"]



def transcribe(audio):    
    audio_file = open(audio, "rb")    
    # Call the transcribe method with the file-like object
    transcript = openai.Audio.transcribe("whisper-1", audio_file)
    
    return transcript["text"]

def botResponse(user_input):    
    response = openai.ChatCompletion.create(
      model="gpt-3.5-turbo",
      #messages=user_input)
      messages=[
                {"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."},
                {"role": "user", "content": user_input}
               ]
    )
  
    system_message = response["choices"][0]["message"]["content"]

    return system_message

def giveVoice(bot_message):
    myobj = gTTS(text=bot_message)
    myobj.save("temp.mp3")

    dir = os.getcwd()
    new_path = os.path.join(dir, "temp.mp3")

    return new_path

def keepLog(gpt):
    

    return "gpt"



with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            user_audio = gr.Audio(source="microphone", type="filepath", label="Input Phrase")
            submit_btn = gr.Button(value="Transcribe")
        with gr.Column():
            user_transcript = gr.Text(label="User Transcript")
            gpt_transcript = gr.Text(label="GPT Transcript")
            gpt_voice = gr.Audio(label="Voice Response")
            chat_log = gr.Text(label="Chat Log")
    submit_btn.click(transcribe, inputs=user_audio, outputs=user_transcript)
    user_transcript.change(botResponse, inputs=user_transcript, outputs=gpt_transcript)
    gpt_transcript.change(giveVoice, inputs=gpt_transcript, outputs=gpt_voice)
    user_audio.change(keepLog, inputs=user_transcript, outputs=chat_log)
    
    

demo.launch(share=False)