Update app.py

app.py

@@ -1,27 +1,23 @@
 import gradio as gr
 from transformers import pipeline
 
-# Define the translation pipeline
-translator = pipeline("translation", model="facebook/m2m100_418M")
+# Define the text classification pipeline
+classifier = pipeline("text-classification", model="bert-base-multilingual-uncased")
 
 # Define the Gradio interface
-def translate_text(text, target_language):
-    translated_text = translator(text, target_language)[0]['translation_text']
-    return translated_text
+def classify_text(text):
+    results = classifier(text)
+    label = results[0]['label']
+    score = results[0]['score']
+    return f"Label: {label}, Score: {score}"
 
 iface = gr.Interface(
-    fn=translate_text,
-    inputs=[
-        gr.inputs.Textbox(label="Input Text"),
-        gr.inputs.Dropdown(
-            label="Target Language",
-            choices=["es", "fr", "de", "it"],  # Add more languages as needed
-        ),
-    ],
-    outputs=gr.outputs.Textbox(label="Translated Text"),
+    fn=classify_text,
+    inputs=gr.inputs.Textbox(label="Input Text"),
+    outputs=gr.outputs.Textbox(label="Classification Result"),
     live=True,
-    title="Multilingual Translation Tool",
-    description="Translate text into multiple languages.",
+    title="Multilingual Text Classification",
+    description="Classify text into categories using BERT-based model.",
 )
 
 # Start the Gradio interface