Create app.py

app.py

@@ -0,0 +1,55 @@
+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define a dictionary of available languages and their corresponding Hugging Face models
+LANGUAGE_MODELS = {
+    "French": "Helsinki-NLP/opus-mt-en-fr",
+    "German": "Helsinki-NLP/opus-mt-en-de",
+    "Spanish": "Helsinki-NLP/opus-mt-en-es",
+    "Italian": "Helsinki-NLP/opus-mt-en-it",
+    "Portuguese": "Helsinki-NLP/opus-mt-en-pt",
+    # Add more languages and their models here
+}
+
+def load_model(language):
+    model_name = LANGUAGE_MODELS.get(language)
+    if model_name is None:
+        st.error("Selected language not supported.")
+        return None, None
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    return tokenizer, model
+
+def translate_text(text, tokenizer, model):
+    inputs = tokenizer(text, return_tensors="pt", padding=True)
+    translated = model.generate(**inputs)
+    translation = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return translation
+
+def main():
+    st.title("Language Translator")
+
+    st.write("This app translates English text into selected languages using Hugging Face models.")
+
+    # Select target language
+    target_language = st.selectbox("Select target language", list(LANGUAGE_MODELS.keys()))
+
+    # Input text
+    input_text = st.text_area("Enter text in English")
+
+    if st.button("Translate"):
+        if not input_text:
+            st.error("Please enter text to translate.")
+        else:
+            # Load the model and tokenizer for the selected language
+            tokenizer, model = load_model(target_language)
+            if tokenizer and model:
+                # Translate the text
+                translated_text = translate_text(input_text, tokenizer, model)
+                st.subheader("Translated Text")
+                st.write(translated_text)
+
+if __name__ == "__main__":
+    main()
+
+streamlit run app.py