Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import requests
+from transformers import MarianMTModel, MarianTokenizer
+
+# Function to fetch and parse language options
+def fetch_languages(url):
+    response = requests.get(url)
+    if response.status_code == 200:
+        df = pd.read_csv(response.content.decode('utf-8'), 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 []
+
+# Fetching language options
+url = "https://huggingface.co/Lenylvt/LanguageISO/resolve/main/iso.md"
+language_options = fetch_languages(url)
+
+# Streamlit UI components
+st.title("Text Translator with Dynamic Language Options")
+st.write("Select source and target languages to translate text.")
+
+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])
+text = st.text_area("Enter text to translate...", height=150)
+
+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)
+        translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512))
+        translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+        return translated_text
+    except Exception as e:
+        return f"Failed to load model for {source_language_code} to {target_language_code}: {str(e)}"
+
+if st.button("Translate"):
+    source_language_code, _ = source_language
+    target_language_code, _ = target_language
+    translation = translate_text(text, source_language_code, target_language_code)
+    st.text_area("Translated Text", value=translation, height=150, key="translation_output")