Update app.py

app.py

@@ -2,18 +2,23 @@ import gradio as gr
 import os
 from setfit import SetFitModel
 
+model_names = ['java-summary', 'java-pointer', 'java-deprecation', 'java-rational', 'java-ownership', 'java-usage', 'java-expand', 
+          'pharo-example', 'pharo-key-implementation', 'pharo-responsibilities', 'pharo-collaborators'
+          'python-summary', 'pharo-parameters', 'pharo-usage', 'pharo-development-notes', 'pharo-expand']
+
+models = {}
+for model_name in model_names
+    models[f'AISE-TUDelft/{model_name}'] = SetFitModel.from_pretrained("dvilasuero/setfit-mini-imdb")#f'AISE-TUDelft/{model_name}'
 
-def greet(name):
-    return "Hello " + name + "!!"
 
 # model = SetFitModel.from_pretrained("AISE-TUDelft/java-ownership-classifier")
 model = SetFitModel.from_pretrained("dvilasuero/setfit-mini-imdb")
 
-def classify(text):
+def classify(text, model):
     if model([text])[0]:
         return 'True'
     else:
         return 'False'
     
-iface = gr.Interface(fn=classify, inputs=["text", gr.inputs.Dropdown(["gpt2", "gpt-j-6B"])], outputs="text")
+iface = gr.Interface(fn=classify, inputs=["text", gr.inputs.Dropdown(model_names, label='class')], outputs="text")
 iface.launch()