Update app.py

app.py

@@ -1,23 +1,27 @@
 import gradio as gr
 from transformers import pipeline
 
-# Define the text classification pipeline
-classifier = pipeline("text-classification", model="bert-base-multilingual-uncased")
+# Define the translation pipeline
+translator = pipeline("translation", model="facebook/mbart-large-50-many-to-many-mmt")
 
 # Define the Gradio interface
-def classify_text(text):
-    results = classifier(text)
-    label = results[0]['label']
-    score = results[0]['score']
-    return f"Label: {label}, Score: {score}"
+def translate_text(text, target_language):
+    translated_text = translator(text, target_language)[0]['translation_text']
+    return translated_text
 
 iface = gr.Interface(
-    fn=classify_text,
-    inputs=gr.components.Textbox(label="Input Text"),
-    outputs=gr.components.Textbox(label="Classification Result"),
+    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"),
     live=True,
-    title="Multilingual Text Classification",
-    description="Classify text into categories using BERT-based model.",
+    title="Multilingual Translation Tool",
+    description="Translate text into multiple languages using facebook/mbart-large-50-many-to-many-mmt model.",
 )
 
 # Start the Gradio interface