import gradio as gr
from openai import OpenAI
import threading as th
import os
import json
from transcription_service import transcribe_speech_local,translation_service



def translateoutput(text,language):
    if text=="" or text is None:
        return ""
    language=language_info[language]
    return translation_service(text,language)
    
    

# Initialize a global variable to hold previous output
language_info=json.load(open("languages_info.json","r"))['wispher_language']


   

    

def transcription(audio_file,input_lang):
    global language_info

    return transcribe_speech_local(audio_file,language_info[input_lang])
    





def func(audio_file,input_lang,lan,state="",state1=""):
    
    text_transcription=transcription(audio_file,input_lang)
    text_translation=translateoutput(text_transcription,lan)
    if text_transcription is None:
        text_transcription=""
        
    state+=str(text_transcription)+" "
    state1+=str(text_translation)+" "
    state=state.replace(".","\n")
    state1=state1.replace(".","\n")
    
    

    
    return state,state1


def gpt_api(text,language):
    if text=="" or text is None:
        return ""
    client = OpenAI()

    response = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": f"You will be provided with a text data, and your task is to make very concise summery it into {language}."},
        {"role": "user", "content": text},
    ])
    message=response.choices[0].message.content
    th.current_thread().return_value=message


def make_summery(text,text1,input_lan,output_lan):
    t1=th.Thread(target=gpt_api, args=(text,input_lan,))
    t2=th.Thread(target=gpt_api, args=(text1,output_lan,))
    t1.start()
    t2.start()
    t1.join()
    t2.join()
    return t1.return_value,t2.return_value
  

    



def clear_output_data():
    return "","","",""

def switch(input_lan,lan):
    return lan,input_lan



with gr.Blocks(theme=gr.themes.Soft(),css="css.txt") as app:
    
    gr.Markdown("## Mufin Real-Time Audio Transcription And Translation",elem_id="heading")
    gr.Markdown("### say any language we are here to translate it for team!!",elem_classes="heading")
    
    with gr.Row():
            mic = gr.Audio(sources="microphone",streaming=True,type='filepath',label='Speak')
            
            input_lan=gr.Dropdown(choices=language_info.keys(),label="Choose Input Language please",value="English",interactive=True)
            switchbutton=gr.Button(value='\u21C6',variant="secondary",elem_id="switchbtn")
            lan=gr.Dropdown(choices=language_info.keys(),label="Choose a language for translation",value="Korean",interactive=True)
            summery=gr.Button(value="Summery",variant="secondary",size="small",elem_id="summery")
            clear_output = gr.ClearButton(value="Clear Output",variant="stop",size="small",elem_id="clear")
    with gr.Row():
        with gr.Column():
        
            text=gr.Textbox(interactive=False,label="Transcription",lines=10,max_lines=10)
            
        with gr.Column():   
            text1 = gr.Textbox(interactive=False,label="Translation",lines=10,max_lines=10,)
            st=mic.stream(func, [mic,input_lan,lan,text,text1], [text,text1],show_progress=False,)
    with gr.Row():
        sumer_ts=gr.Textbox(label="Summery of Transcription",interactive=False,lines=4,max_lines=4)
        sumer_tr=gr.Textbox(label="Summery of Translation",interactive=False,lines=4,max_lines=4)
        
        # pass
        summery.click(make_summery,[text,text1,input_lan,lan],[sumer_ts,sumer_tr],cancels=[st],queue=False)
        clear_output.click(clear_output_data,[],[text,text1,sumer_tr,sumer_ts],cancels=[st],queue=False)
        switchbutton.click(switch,[input_lan,lan],[input_lan,lan],cancels=[st],queue=False)
        # gr.update(visible=True)

app.queue()
app.launch()