Create app.py

app.py

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+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Function to load models dynamically
+def load_translation_model(model_name):
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    return pipeline("translation", model=model, tokenizer=tokenizer)
+
+# Streamlit UI
+st.title("Language Translator")
+
+# User section on the left
+st.sidebar.title("User Section")
+input_lang = st.sidebar.selectbox("Select Input Language", ["English", "Urdu", "French", "Spanish", "German"])
+output_lang = st.sidebar.selectbox("Select Output Language", ["Urdu", "English", "French", "Spanish", "German"])
+
+# Text input
+input_text = st.text_area("Enter Text to Translate", "Type here...")
+
+# Translation logic
+translator = None
+if st.button("Translate"):
+    if input_lang == "English" and output_lang == "Urdu":
+        translator = load_translation_model("Helsinki-NLP/opus-mt-en-ur")
+    elif input_lang == "Urdu" and output_lang == "English":
+        translator = load_translation_model("Helsinki-NLP/opus-mt-ur-en")
+    elif input_lang == "English" and output_lang == "French":
+        translator = pipeline("translation_en_to_fr")
+    elif input_lang == "French" and output_lang == "English":
+        translator = pipeline("translation_fr_to_en")
+    elif input_lang == "English" and output_lang == "German":
+        translator = pipeline("translation_en_to_de")
+    elif input_lang == "German" and output_lang == "English":
+        translator = pipeline("translation_de_to_en")
+
+    if translator:
+        translation = translator(input_text)
+        st.write("Translated Text:")
+        st.write(translation[0]['translation_text'])
+    else:
+        st.write("Translation for the selected languages is not available yet.")