Update app.py

app.py

@@ -4,7 +4,7 @@ import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 
-def summarize(inputs,model=model,summary_length=200):
+def summarize(inputs,model,summary_length):
   if model=="T5-base":
         tokenizer = AutoTokenizer.from_pretrained("Einmalumdiewelt/T5-Base_GNAD")
         model = AutoModelForSeq2SeqLM.from_pretrained("Einmalumdiewelt/T5-Base_GNAD")
@@ -43,17 +43,23 @@ examples = [["summarize: Maschinelles Lernen ist ein Oberbegriff für die „kü
 #            title=title,
 #            description=description,
 #            examples=examples)
+
+# text input box
 txt=gr.Textbox(lines=15, label="I want to summarize this:", placeholder="Paste your German text in here. Don't forget to add the prefix \"summarize: \" for T5-base architecture.")
+# dropdown model selection
+drop=gr.Dropdown(["T5-base", "Google pegasus", "Facebook bart-large"],label="Choose a fine-tuned architecture.")
+# slider summary length selection
+slide=gr.Slider(50, 250, step=50, label="Select preferred summary length.", value=150)
+# text output box
 out=gr.Textbox(lines=5, label="Here's your summary:")
             
 interface = gr.Interface(summarize,
             inputs=[
             txt,
             # Selection of models for inference
-            gr.Dropdown(["T5-base", "Google pegasus", "Facebook bart-large"],label="Choose a fine-tuned architecture."),
+            drop,
             # Length of summaries
-            gr.Slider(50, 250, step=50, label="Select preferred summary length.", value=150)
-            ],
+            slide],
             # ouptut
             outputs=out,
             title=title,