Create app.py

app.py

@@ -0,0 +1,51 @@
+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Function to perform translation
+def translate(text, src_lang, tgt_lang):
+    model_name = f'Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}'
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+
+    # Tokenize and translate
+    inputs = tokenizer.encode(text, return_tensors="pt", max_length=512, truncation=True)
+    translated_tokens = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
+    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+
+    return translated_text
+
+# Streamlit app layout
+st.title("Language Translator App")
+
+# Input and output language options
+languages = [
+    "en",  # English
+    "fr",  # French
+    "de",  # German
+    "es",  # Spanish
+    "it",  # Italian
+    "nl",  # Dutch
+    "zh",  # Chinese
+    "hi"   # Hindi
+]
+
+src_lang = st.selectbox("Select input language:", languages, index=0)
+tgt_lang = st.selectbox("Select output language:", languages, index=1)
+
+# Text input
+text_to_translate = st.text_area("Enter text to translate:")
+
+# Translate button
+if st.button("Translate"):
+    if src_lang == tgt_lang:
+        st.warning("Input and output languages must be different.")
+    elif text_to_translate.strip() == "":
+        st.warning("Please enter text to translate.")
+    else:
+        with st.spinner("Translating..."):
+            try:
+                translation = translate(text_to_translate, src_lang, tgt_lang)
+                st.success("Translation completed!")
+                st.text_area("Translated text:", value=translation, height=200)
+            except Exception as e:
+                st.error(f"An error occurred: {e}")