markdown, radio buttons

interfaces/cap_minor_media.py

@@ -139,10 +139,26 @@ def predict_cap(text, language, domain):
         
     return predict(text, major_model_id, minor_model_id, tokenizer_id)
 
+description = """
+You can choose between two approaches for making predictions:
+
+1. **Hierarchical Classification**  
+   First, the model predicts a **major topic**. Then, a second model selects the most probable **subtopic** from within that major topic's category.
+
+2. **Flat Classification (single model)**  
+   A single model directly predicts the most relevant label from all available classes, without distinguishing between major and subtopics.
+"""
+
 demo = gr.Interface(
     title="CAP Media/Minor Topics Babel Demo",
     fn=predict_cap,
-    inputs=[gr.Textbox(lines=6, label="Input"),
+    inputs=[gr.Markdown(description)
+            gr.Radio(
+                choices=["Hierarchical Classification", "Flat Classification"],
+                label="Prediction Mode",
+                value="Hierarchical Classification"
+            )
+            gr.Textbox(lines=6, label="Input"),
             gr.Dropdown(languages, label="Language"),
             gr.Dropdown(domains.keys(), label="Domain")],
     outputs=[gr.Label(num_top_classes=5, label="Output"), gr.Markdown()])