Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Load the translation pipeline from Hugging Face
+translator = pipeline("translation_en_to_fr")  # Default to French translation
+
+# Available languages and their corresponding models
+available_languages = {
+    "French": "translation_en_to_fr",
+    "German": "translation_en_to_de",
+    "Spanish": "translation_en_to_es",
+    "Chinese": "Helsinki-NLP/opus-mt-en-zh",  # For Chinese, we use a specific model from Hugging Face
+    "Japanese": "Helsinki-NLP/opus-mt-en-jap",
+    "Russian": "Helsinki-NLP/opus-mt-en-ru",
+    "Arabic": "Helsinki-NLP/opus-mt-en-ar",
+}
+
+# Streamlit app title
+st.title("Language Translator")
+
+# User input for text to translate
+text_to_translate = st.text_area("Enter text in English:", "")
+
+# Language selection
+target_language = st.selectbox("Select the target language:", list(available_languages.keys()))
+
+# Change the translation model based on the selected language
+translator = pipeline("translation", model=available_languages[target_language])
+
+# Translate button
+if st.button("Translate"):
+    if text_to_translate:
+        # Perform the translation
+        translation = translator(text_to_translate)
+        # Display the translated text
+        st.write(f"**Translated text in {target_language}:**")
+        st.write(translation[0]['translation_text'])
+    else:
+        st.warning("Please enter some text to translate.")
+
+# Footer
+st.markdown("Powered by [Hugging Face Transformers](https://huggingface.co/transformers/).")