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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() |