Update app.py

app.py

@@ -64,15 +64,12 @@ def process_classification(text, model1, model2, tokenizer1):
 
     return f"{round(prediction1, 1)}", f"{round(prediction2, 1)}", f"{round(score, 2)}"
 
+def all():
+    return process_ner(text, pipe_ext), process_ner(text, pipe_ais), process_classification(text, model1, model2, tokenizer1)[0], process_classification(text, model1, model2, tokenizer1)[1], process_classification(text, model1, model2, tokenizer1)[2]
+
 # Define Gradio interface
 iface = gr.Interface(
-    fn={
-        "NER - Extended Sequence Classification": lambda text: process_ner(text, pipe_ext),
-        "NER - Autobiographical Interview Scoring": lambda text: process_ner(text, pipe_ais),
-        "Internal Detail Count": lambda text: process_classification(text, model1, model2, tokenizer1)[0],
-        "External Detail Count": lambda text: process_classification(text, model1, model2, tokenizer1)[1],
-        "Approximated Internal Detail Ratio": lambda text: process_classification(text, model1, model2, tokenizer1)[2]
-    },
+    fn=all,
     inputs=gr.Textbox(placeholder="Enter sentence here..."),
     outputs=[
         gr.HighlightedText(label="NER - Extended Sequence Classification"),