Create app.py

app.py

@@ -0,0 +1,44 @@
+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define supported language pairs (source-target)
+LANGUAGES = {
+    "en": "English",
+    "fr": "French",
+    "de": "German",
+    "es": "Spanish",
+    "it": "Italian",
+    "pt": "Portuguese",
+    "ru": "Russian",
+    "zh": "Chinese",
+}
+
+def get_model_and_tokenizer(src_lang: str, tgt_lang: str):
+    model_name = f"Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}"
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    return model, tokenizer
+
+def translate_text(text: str, source_lang: str, target_lang: str):
+    model, tokenizer = get_model_and_tokenizer(source_lang, target_lang)
+    translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True))
+    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return translated_text
+
+# Streamlit app
+st.title("Text Translation App")
+
+st.write("Translate text from one language to another using a Hugging Face model.")
+
+source_lang = st.selectbox("Select the source language", list(LANGUAGES.keys()), format_func=lambda x: LANGUAGES[x])
+target_lang = st.selectbox("Select the target language", list(LANGUAGES.keys()), format_func=lambda x: LANGUAGES[x])
+
+text = st.text_area("Enter the text you want to translate")
+
+if st.button("Translate"):
+    if source_lang == target_lang:
+        st.warning("Source and target languages are the same. Please select different languages.")
+    else:
+        translated_text = translate_text(text, source_lang, target_lang)
+        st.write("**Translated Text:**")
+        st.write(translated_text)