Update app.py

app.py

@@ -131,10 +131,12 @@ def predict_sdg(text):
     return {top_prediction[0]: round(top_prediction[1], 3)}, fig
 
 # Create Gradio interface for single text
-iface2 = gr.Interface(fn=predict_sdg, 
+iface2 = gr.Interface(fn=predict_sdg,
                       inputs=gr.Textbox(lines=7, label="Paste or type text here"), 
                       outputs=[gr.Label(label="Top SDG Predicted", show_label=True), gr.Plot(label="Likelihood of all SDG", show_label=True)], 
-                      title="Single Text Prediction")
+                      title="Single Text Prediction",
+                      article="**Note:** The quality of model predictions may depend on the quality of information provided."
+                     )
 
 # UPLOAD CSV
 # Define the prediction function
@@ -211,9 +213,13 @@ iface3 = gr.Interface(fn=predict_sdg_from_csv,
                       inputs= file_input, 
                       outputs=[gr.Plot(label='Frequency of SDGs', show_label=True), gr.File(label='Download output CSV', show_label=True)], 
                       title="Multi-text Prediction (CVS)",
-                      description='NOTE: Column to be analysed must be titled ***text_inputs***')
+                      description='**NOTE:** The column to be analysed must be titled ***text_inputs***')
 
-demo = gr.TabbedInterface([iface1, iface2, iface3], ["General-App-Info", "Single-Text-Prediction", "Multi-Text-Prediction (CSV)"])
+demo = gr.TabbedInterface(interface_list = [iface1, iface2, iface3], 
+                          tab_names = ["General-App-Info", "Single-Text-Prediction", "Multi-Text-Prediction (CSV)"],
+                          title = "Sustainble Development Goals (SDG) Text Classifier App",
+                          theme = 'soft'
+                         )
 
 # Run the interface
 demo.launch()