Update app.py

app.py

@@ -2,28 +2,26 @@ from transformers import pipeline
 import gradio as gr
 
 # Load translation pipelines once
-t5_translator = pipeline("translation_en_to_de", model="t5-small")
-
-# ✅ Correct and public model for English → Tamil
-ta_translator = pipeline("translation_en_to_ta", model="Helsinki-NLP/opus-mt-en-tam")
+de_translator = pipeline("translation_en_to_de", model="Helsinki-NLP/opus-mt-en-de")
+hi_translator = pipeline("translation_en_to_hi", model="Helsinki-NLP/opus-mt-en-hi")
 
 def translate_text(text):
-    # Translate using T5-small (English → German)
-    result_t5 = t5_translator(text, max_length=40)[0]['translation_text']
-    # Translate using Helsinki-NLP (English → Tamil)
-    result_ta = ta_translator(text, max_length=40)[0]['translation_text']
-    return result_t5, result_ta
+    # Translate English → German
+    result_de = de_translator(text, max_length=40)[0]['translation_text']
+    # Translate English → Hindi
+    result_hi = hi_translator(text, max_length=40)[0]['translation_text']
+    return result_de, result_hi
 
-# Create Gradio interface
+# Gradio interface
 demo = gr.Interface(
     fn=translate_text,
     inputs=gr.Textbox(lines=2, placeholder="Enter English text here..."),
     outputs=[
-        gr.Textbox(label="T5-small Translation (English → German)"),
-        gr.Textbox(label="Helsinki-NLP Translation (English → Tamil)")
+        gr.Textbox(label="Helsinki-NLP Translation (English → German)"),
+        gr.Textbox(label="Helsinki-NLP Translation (English → Hindi)")
     ],
     title="📝 Text Translator",
-    description="Enter English text and get translations using T5-small (English → German) and Helsinki-NLP (English → Tamil)"
+    description="Enter English text and get translations into German and Hindi using public Helsinki-NLP models"
 )
 
 if __name__ == "__main__":