Create app.py

app.py

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+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define a list of supported language pairs
+languages = {
+    'English': 'en',
+    'Urdu': 'ur',
+    'French': 'fr',
+    'Spanish': 'es',
+    'German': 'de',
+    'Chinese': 'zh',
+    'Italian': 'it',
+    'Russian': 'ru',
+    'Japanese': 'ja',
+    'Arabic': 'ar',
+    'Hindi': 'hi',
+}
+
+# Define supported language pairs
+language_pairs = {
+    ('en', 'ur'): 'Helsinki-NLP/opus-mt-en-ur',
+    ('ur', 'en'): 'Helsinki-NLP/opus-mt-ur-en',
+    ('en', 'fr'): 'Helsinki-NLP/opus-mt-en-fr',
+    ('fr', 'en'): 'Helsinki-NLP/opus-mt-fr-en',
+    ('en', 'es'): 'Helsinki-NLP/opus-mt-en-es',
+    ('es', 'en'): 'Helsinki-NLP/opus-mt-es-en',
+    ('en', 'de'): 'Helsinki-NLP/opus-mt-en-de',
+    ('de', 'en'): 'Helsinki-NLP/opus-mt-de-en',
+    ('en', 'zh'): 'Helsinki-NLP/opus-mt-en-zh',
+    ('zh', 'en'): 'Helsinki-NLP/opus-mt-zh-en',
+    ('en', 'it'): 'Helsinki-NLP/opus-mt-en-it',
+    ('it', 'en'): 'Helsinki-NLP/opus-mt-it-en',
+    ('en', 'ru'): 'Helsinki-NLP/opus-mt-en-ru',
+    ('ru', 'en'): 'Helsinki-NLP/opus-mt-ru-en',
+    ('en', 'ja'): 'Helsinki-NLP/opus-mt-en-ja',
+    ('ja', 'en'): 'Helsinki-NLP/opus-mt-ja-en',
+    ('en', 'ar'): 'Helsinki-NLP/opus-mt-en-ar',
+    ('ar', 'en'): 'Helsinki-NLP/opus-mt-ar-en',
+    ('en', 'hi'): 'Helsinki-NLP/opus-mt-en-hi',
+    ('hi', 'en'): 'Helsinki-NLP/opus-mt-hi-en',
+    # Add more pairs as available
+}
+
+def load_model(src_lang, tgt_lang):
+    model_name = language_pairs.get((src_lang, tgt_lang))
+    if not model_name:
+        raise ValueError(f"No available model for {src_lang} to {tgt_lang}")
+    
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    return model, tokenizer
+
+def translate(text, src_lang, tgt_lang):
+    model, tokenizer = load_model(src_lang, tgt_lang)
+    inputs = tokenizer.encode(text, return_tensors="pt", padding=True)
+    translated = model.generate(inputs)
+    return tokenizer.decode(translated[0], skip_special_tokens=True)
+
+def translate_chain(text, src_lang, tgt_lang):
+    if src_lang != 'en':
+        text = translate(text, src_lang, 'en')
+    if tgt_lang != 'en':
+        text = translate(text, 'en', tgt_lang)
+    return text
+
+def translate_ui(text, source_language, target_language):
+    src_lang = languages[source_language]
+    tgt_lang = languages[target_language]
+    
+    try:
+        return translate(text, src_lang, tgt_lang)
+    except ValueError:
+        return translate_chain(text, src_lang, tgt_lang)
+
+# Streamlit App UI
+st.title("Multilingual Translator")
+st.write("Translate text between various languages including Urdu, French, Spanish, and more.")
+
+# Input text
+text = st.text_area("Enter text to translate", height=100)
+
+# Source and Target Languages
+source_language = st.selectbox("Select Source Language", list(languages.keys()))
+target_language = st.selectbox("Select Target Language", list(languages.keys()))
+
+# Translate Button
+if st.button("Translate"):
+    if text.strip():
+        translation = translate_ui(text, source_language, target_language)
+        st.text_area("Translated Text", translation, height=100)
+    else:
+        st.warning("Please enter text to translate.")
+
+# About Section
+st.sidebar.title("About")
+st.sidebar.info(
+    """
+    This app allows you to translate text between multiple languages using the MarianMT model from Hugging Face's Helsinki-NLP collection.
+    """
+)