app.py

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

def fetch_languages(url):
    response = requests.get(url)
    if response.status_code == 200:
        df = pd.read_csv(BytesIO(response.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)
    total_subs = len(subs)
    translated_subs = []
    progress_text = "Operation in progress. For information, the progress bar start when the translation begin."
    progress_bar = st.progress(0, text=progress_text)  # Initialize the progress bar
    
    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) / total_subs)  # Update progress bar

    translated_file = pysrt.SubRipFile(items=translated_subs)
    return translated_file

st.title("SRT Translation")
st.write("We use model from [Language Technology Research Group at the University of Helsinki](https://huggingface.co/Helsinki-NLP). For API use please visit [this space](https://huggingface.co/spaces/Lenylvt/SRT_Translation-API)")

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

source_language_code, target_language_code = None, None

if language_options:
    source_language_code = st.selectbox("1️⃣ Select Source Language", options=language_options, format_func=lambda x: x[1])[0]
    target_language_code = st.selectbox("2️⃣ Select Target Language", options=language_options, format_func=lambda x: x[1])[0]

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

if file_input is not None and source_language_code and target_language_code:
    with tempfile.NamedTemporaryFile(delete=False, suffix=".srt") as temp_file:
        temp_file.write(file_input.getvalue())
        temp_file.flush()
        translated_srt = translate_srt(temp_file.name, source_language_code, target_language_code)
        os.unlink(temp_file.name)  # Delete the temp file
    
    # Save the translated subtitles to a temporary file and then read it into BytesIO
    with tempfile.NamedTemporaryFile(delete=False, suffix=".srt") as temp_file:
        translated_srt.save(temp_file.name, encoding='utf-8')
        temp_file.seek(0)
        translated_srt_bytes = open(temp_file.name, 'rb').read()
        os.unlink(temp_file.name)  # Delete the temp file after reading

    st.download_button(
        label="⬇️ Download Translated SRT",
        data=translated_srt_bytes,
        file_name="translated_subtitles.srt",
        mime="text/plain",
    )

    st.markdown("""
    ### Some Error you can have:
    - **If into your file your have** : Failed to load model for aa to ab: Helsinki-NLP/opus-mt-aa-ab is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with huggingface-cli loginor by passingtoken=<your_token>` **its because the translation is currently not supported**.
    - **If into your file your have** : Translation between the same languages is not supported, **just change your language**.
    """)