import os
import warnings
import gradio as gr
import re


HF_TOKEN = os.getenv('HW_TOKEN')
hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "save_audio")


cur_line=0

def readFile():
    f=open('prompt.txt')
    line_num=0
    lines=f.readlines()
    line_num = len(lines)
    return  line_num,lines

totlines,file_content=readFile()

#callback = gr.CSVLogger()
def recordAndsave(text,audio):
    #print (next)
    print (text)
    global totlines
    print(totlines)
    global cur_line
    if cur_line<totlines-1:
        cur_line+=1
        global file_content
        print (cur_line)
    return file_content[cur_line].strip()
    #return None

    #print (previous)
    
def readPromt():
    global cur_line
    cur_line+=1
    global file_content
    print (cur_line)
    return file_content[cur_line]
    
def readNext():
    
    global totlines
    print(totlines)
    global cur_line
    if cur_line<totlines-1:
        cur_line+=1
        global file_content
        print (cur_line)
    return [file_content[cur_line],None]

def readPrevious():
    global cur_line
    if cur_line>=0:
        cur_line-=1
    #cur_line=current_line
        global file_content
        print (cur_line)
    return [file_content[cur_line],None]



demo=gr.Interface(
    fn=recordAndsave, 
   

    inputs=[
        gr.Audio(sources=["microphone","upload"], type="filepath"),
       
    ],
    outputs=[
        gr.Textbox(readPromt(),label="Prompt")
    ],
        
        allow_flagging="manual",
        flagging_callback=hf_writer
    ).launch()