new label field

app.py

@@ -14,8 +14,9 @@ def upload_file(files):
     return file_paths
 
 def predict_topic(input_text):
-    reframed_text = pipeline_classification_topics(input_text)
-    return reframed_text
+    prediction = pipeline_classification_topics(input_text)
+    # predicted_label = prediction[0]['label']
+    return prediction
 
 # Build Gradio interface
 with gr.Blocks() as demo:
@@ -24,7 +25,8 @@ with gr.Blocks() as demo:
 
     # Input text to be reframed
     text = gr.Textbox(label="Text")
-    predictions = gr.outputs.Textbox(label="Topic")
+    #predictions = gr.outputs.Textbox(label="Topic")
+    predictions = gr.Label("Topic")
 
     # Trigger button for topic prediction
     greet_btn = gr.Button("Predict Topic")
@@ -43,7 +45,7 @@ with gr.Blocks() as demo:
     # Upload file
     # file_output = gr.File()
     # upload_button = gr.UploadButton("Click to Upload a File", type="file", accept=".csv", label="File", outputs=[file_output])
-    
+
     # Link to paper and Github repo
     gr.Markdown('''For more details: You can read our [paper]() or access our [code]().''')