app.py

import io
import requests
import streamlit as st
import pandas as pd
import pysrt
from transformers import MarianMTModel, MarianTokenizer
import tempfile

def fetch_languages(url):
    response = requests.get(url)
    if response.status_code == 200:
        # Convert bytes to a string using decode, then create a file-like object with io.StringIO
        csv_content = response.content.decode('utf-8')
        df = pd.read_csv(io.StringIO(csv_content), delimiter="|", skiprows=2, header=None).dropna(axis=1, how='all')
        df.columns = ['ISO 639-1', 'ISO 639-2', 'Language Name', 'Native Name']
        df['ISO 639-1'] = df['ISO 639-1'].str.strip()
        language_options = [(row['ISO 639-1'], f"{row['ISO 639-1']} - {row['Language Name']}") for index, row in df.iterrows()]
        return language_options
    else:
        return []

def translate_text(text, source_language_code, target_language_code):
    model_name = f"Helsinki-NLP/opus-mt-{source_language_code}-{target_language_code}"
    if source_language_code == target_language_code:
        return "Translation between the same languages is not supported."
    try:
        tokenizer = MarianTokenizer.from_pretrained(model_name)
        model = MarianMTModel.from_pretrained(model_name)
    except Exception as e:
        return f"Failed to load model for {source_language_code} to {target_language_code}: {str(e)}"
    
    translated_texts = []
    for sentence in text.split("\n"):
        translated = model.generate(**tokenizer(sentence, return_tensors="pt", padding=True, truncation=True, max_length=512))
        translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
        translated_texts.append(translated_text)
    return "\n".join(translated_texts)

def translate_srt(input_file, source_language_code, target_language_code):
    subs = pysrt.open(input_file)
    translated_subs = []
    progress_bar = st.progress(0)
    for idx, sub in enumerate(subs):
        translated_text = translate_text(sub.text, source_language_code, target_language_code)
        translated_sub = pysrt.SubRipItem(index=idx+1, start=sub.start, end=sub.end, text=translated_text)
        translated_subs.append(translated_sub)
        progress_bar.progress((idx + 1) / len(subs))
    translated_file = pysrt.SubRipFile(translated_subs)
    # Use tempfile to create a temporary file path
    with tempfile.NamedTemporaryFile(suffix=".srt", delete=False) as tmp_file:
        translated_file.save(tmp_file.name)
        translated_srt_path = tmp_file.name
    progress_bar.empty()
    return translated_srt_path

st.title("SRT Translator")
st.write("Translate subtitles from one language to another.")

# Fetch language options
url = "https://huggingface.co/Lenylvt/LanguageISO/resolve/main/iso.md"
language_options = fetch_languages(url)

source_language = st.selectbox("Select Source Language", options=language_options, format_func=lambda x: x[1])
target_language = st.selectbox("Select Target Language", options=language_options, format_func=lambda x: x[1])

file_input = st.file_uploader("Upload SRT File", type=["srt"])

if file_input is not None:
    with tempfile.NamedTemporaryFile(suffix=".srt", delete=False) as temp_file:
        temp_file.write(file_input.read())
        temp_file.seek(0)
        translated_srt_path = translate_srt(temp_file.name, source_language_code, target_language_code)
        st.success(f"Translation complete! You can download the translated SRT file from [here]({translated_srt_path})")