app.py

import gradio as gr
import json
import re
import string
import pandas as pd
import os
import requests
from textwrap import wrap
import uuid
import gspread
import ast



def download_and_save_file(URL, audio_dir):
    headers = {
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.121 Safari/537.36',
        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
        'referer': 'https://www.google.com/',
        'accept-encoding': 'gzip, deflate, br',
        'accept-language': 'en-US,en;q=0.9,',
        'cookie': 'prov=6bb44cc9-dfe4-1b95-a65d-5250b3b4c9fb; _ga=GA1.2.1363624981.1550767314; __qca=P0-1074700243-1550767314392; notice-ctt=4%3B1550784035760; _gid=GA1.2.1415061800.1552935051; acct=t=4CnQ70qSwPMzOe6jigQlAR28TSW%2fMxzx&s=32zlYt1%2b3TBwWVaCHxH%2bl5aDhLjmq4Xr',
    }
    doc = requests.get(URL, headers=headers)
    file_name = URL.split('/')[-1].split('?')[0]
    audio_path = f'{audio_dir}/{file_name}'
    with open(audio_path, 'wb') as f:
        f.write(doc.content)  
    return audio_path



credentials = os.environ['CREDENTIALS']
data = json.loads(credentials, strict=False)
with open('credentials.json', 'w') as f:
    json.dump(data, f)




title = '🎵 Annotate audio'
description = '''Choose a sentence (or sentences) that describes audio the best.'''

audio_dir = 'AUDIO'
os.makedirs(audio_dir, exist_ok=True)

def sample_df():

    gc = gspread.service_account(filename='credentials.json')
    sh = gc.open('Annotated CC Audio')
    worksheet = sh.sheet1
    df = pd.DataFrame(worksheet.get_all_records())
    sample_df = df[df['caption']==''].sample(1)

    audio_url, audio_meta, page_title, img_metadata, sibling_elems = sample_df[['audio_url', 'audio_meta', 'page_title', 'imgs_metadata', 'sibling_elems']].values[0]
    audio_path = download_and_save_file(audio_url, audio_dir)
    sibling_elems = ast.literal_eval(sibling_elems)
    sibling_elems = [s.replace('\n', '') for s in sibling_elems]
    sibling_elems = [s for s in sibling_elems if len(s) > 0]
    sibling_elems = list(set(sibling_elems))
    img_metadata = ast.literal_eval(img_metadata)
    if len(img_metadata) > 0:
      img_metadata = [[f'{k}: {meta[k]}' for k in meta] for meta in img_metadata]
    audio_meta = ast.literal_eval(audio_meta).get('tags', None)
    if audio_meta:
      audio_meta = [f'{k}: {audio_meta[k]}' for k in audio_meta.keys() if k.lower() in ['title', 'album', 'artist', 'genre', 'date', 'language']]
      audio_meta = '; '.join(audio_meta)
    return audio_path, audio_url, sibling_elems, audio_meta, page_title, df, worksheet

def audio_demo(siblings, page_title, audio_meta, audio, annotator, audio_url):
    annotator = annotator if annotator else str(uuid.uuid4())
    siblings.extend(page_title)
    siblings.extend(audio_meta)
    siblings = [s for s in siblings if s!=[]]
    cap = '\n'.join(siblings)
    df['caption'].loc[df['audio_url'] == audio_url] = cap
    df['annotator'].loc[df['audio_url'] == audio_url] = annotator
    worksheet.update([df.columns.values.tolist()] + df.values.tolist())
    return 'success!'

audio_path, audio_url, sibling_elems, audio_meta, page_title, df, worksheet = sample_df()

iface = gr.Interface(
    audio_demo,  
    inputs=[
        gr.CheckboxGroup(sibling_elems, label='sibling elements text'), 
        gr.CheckboxGroup(label='page title', choices=[page_title]), 
        gr.CheckboxGroup([audio_meta], label='audio metadata'), 
        gr.Audio(audio_path, type="filepath", interactive=False), 
        gr.Textbox(label='please enter your name'), 
        gr.Textbox(value=audio_url, visible=False)
        ],
    outputs=[gr.Textbox(label="output")],
    allow_flagging="never",
    title=title,
    description=description,
    )

if __name__ == "__main__":
  iface.launch(show_error=True, debug=True)