Update app.py

app.py

@@ -21,7 +21,41 @@ output_json_component_description = { "breakdown": """
 This box presents a detailed breakdown of the evaluation for each model.
 """}
 
+model_list = [
+    "knowhate/HateBERTimbau",
+    "knowhate/HateBERTimbau-youtube",
+    "knowhate/HateBERTimbau-twitter",
+    "knowhate/HateBERTimbau-yt-tt",
+]
+
+user_friendly_name = {
+    "knowhate/HateBERTimbau": "HateBERTimbau (Original)",
+    "knowhate/HateBERTimbau-youtube": "HateBERTimbau (YouTube)",
+    "knowhate/HateBERTimbau-twitter": "HateBERTimbau (Twitter)",
+    "knowhate/HateBERTimbau-yt-tt": "HateBERTimbau (YouTube + Twitter)"
+}
+
+reverse_user_friendly_name = { v:k for k,v in user_friendly_name.items() }
+
+user_friendly_name_list = list(user_friendly_name.values())
 
 pipe = pipeline("text-classification", model="knowhate/HateBERTimbau")
 demo = gr.Interface.from_pipeline(pipe)
-demo.launch()
+demo.launch()
+
+
+
+inputs = [
+    gr.Textbox(label="Text", value=app_examples[0][0]),
+    gr.Dropdown(label="Model", choices=user_friendly_name_list, value=user_friendly_name_list[0])
+]
+
+outputs = [
+ gr.Label(label="Result"),
+ gr.Markdown(),
+]
+
+
+gr.Interface(fn=predict, inputs=inputs, outputs=outputs, title=app_title, 
+             description=app_description,
+             examples=app_examples).launch()