Create app.py

app.py

@@ -0,0 +1,42 @@
+import streamlit as st
+from transformers import pipeline
+
+# Load the translation pipeline from Hugging Face
+@st.cache_resource
+def load_translation_pipeline(model_name):
+    return pipeline("translation", model=model_name)
+
+# Dictionary of available models and target languages
+models = {
+    "French": "Helsinki-NLP/opus-mt-en-fr",
+    "Spanish": "Helsinki-NLP/opus-mt-en-es",
+    "German": "Helsinki-NLP/opus-mt-en-de",
+    "Chinese": "Helsinki-NLP/opus-mt-en-zh",
+    "Hindi": "Helsinki-NLP/opus-mt-en-hi",
+}
+
+# Streamlit app
+def main():
+    st.title("Language Translator")
+
+    # Input text from the user
+    text_to_translate = st.text_area("Enter the text in English:")
+
+    # Select the target language
+    target_language = st.selectbox("Select the target language:", list(models.keys()))
+
+    # Translate button
+    if st.button("Translate"):
+        # Load the appropriate translation model
+        translation_pipeline = load_translation_pipeline(models[target_language])
+
+        # Translate the text
+        if text_to_translate.strip():
+            translated_text = translation_pipeline(text_to_translate)[0]['translation_text']
+            st.success(f"Translated Text ({target_language}):")
+            st.write(translated_text)
+        else:
+            st.error("Please enter some text to translate.")
+
+if __name__ == "__main__":
+    main()