Update app.py

app.py

@@ -1,31 +1,30 @@
-# 📦 Install required libraries first (in your Hugging Face Space or Colab, use !pip install ...)
-# !pip install transformers sentencepiece
-
 from transformers import pipeline
-
-def main():
-    # ✅ Create translation pipeline for t5-small (English → German)
-    t5_translator = pipeline("translation_en_to_de", model="t5-small")
-
-    # ✅ Create translation pipeline for Helsinki-NLP/opus-mt-en-ta (English → Tamil)
-    ta_translator = pipeline("translation_en_to_ta", model="Helsinki-NLP/opus-mt-en-ta")
-
-    # Example text to translate
-    text_en1 = "This is a simple text to translate."
-    text_en2 = "Nature is beautiful and full of wonders."
-
-    # Translate using t5-small
-    result_t5 = t5_translator(text_en1, max_length=40)
-    print("🔹 T5-small translation (English → German):")
-    print(result_t5[0]['translation_text'])
-
-    print()  # blank line
-
-    # Translate using Helsinki-NLP/opus-mt-en-ta
-    result_ta = ta_translator(text_en2, max_length=40)
-    print("🔹 Helsinki-NLP English → Tamil translation:")
-    print(result_ta[0]['translation_text'])
-
+import gradio as gr
+
+# Load translation pipelines once
+t5_translator = pipeline("translation_en_to_de", model="t5-small")
+
+# ✅ Correct model name for English → Tamil
+ta_translator = pipeline("translation_en_to_ta", model="Helsinki-NLP/opus-mt-en-tam")
+
+def translate_text(text):
+    # Translate using T5-small
+    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
+
+# 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)")
+    ],
+    title="📝 Text Translator",
+    description="Enter English text and get translations using T5-small (English → German) and Helsinki-NLP (English → Tamil)"
+)
 
 if __name__ == "__main__":
-    main()
+    demo.launch()