Create app.py

app.py

@@ -0,0 +1,37 @@
+import streamlit as st
+import requests
+import os
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import pipeline
+
+st.title("Translation App")
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
+model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
+
+def translate(text, src_lang, tgt_lang):
+    translator = pipeline(
+        "translation",
+        model=model,
+        tokenizer=tokenizer,
+        src_lang=src_lang,
+        tgt_lang=tgt_lang,
+    )
+    output = translator(text, max_length=400)
+    return output[0]["translation_text"]
+
+def main():
+    src_lang = st.text_input("Enter source language code (e.g., en):")
+    tgt_lang = st.text_input("Enter target language code (e.g., fr):")
+    text = st.text_area("Enter text to translate:")
+    
+    if st.button("Translate"):
+        if src_lang and tgt_lang and text:
+            result = translate(text, src_lang, tgt_lang)
+            st.write("Translated Text:", result)
+        else:
+            st.warning("Please provide source language, target language, and text to translate.")
+
+if __name__ == "__main__":
+    main()