Update app.py

app.py

@@ -19,7 +19,8 @@ def load_model(model_name):
         loaded_models[model_name] = pipeline("question-answering", model=models[model_name])
     return loaded_models[model_name]
 
-def answer_question(model_name, file, question):
+def answer_question(model_name, file, question, status):
+    status = "Loading model..."
     model = load_model(model_name)
     
     if file is not None:
@@ -43,7 +44,8 @@ def answer_question(model_name, file, question):
     # Explain score
     score_explanation = f"The confidence score ranges from 0 to 1, where a higher score indicates higher confidence in the answer's correctness. In this case, the score is {score:.2f}. A score closer to 1 implies the model is very confident about the answer."
     
-    return answer, f"{score:.2f}", score_explanation
+    status = "Model loaded"
+    return answer, f"{score:.2f}", score_explanation, status
 
 # Define the Gradio interface
 with gr.Blocks() as interface:
@@ -74,19 +76,15 @@ with gr.Blocks() as interface:
     with gr.Row():
         submit_button = gr.Button("Submit")
     
-    # Define a status area for progress
-    status = gr.Markdown(value="")
+    status_output = gr.Markdown(value="")
 
     def on_submit(model_name, file, question):
-        status.update(value="Loading model...")
-        answer, score, explanation = answer_question(model_name, file, question)
-        status.update(value="Model loaded")
-        return answer, score, explanation
+        return answer_question(model_name, file, question, status="Loading model...")
 
     submit_button.click(
         on_submit,
         inputs=[model_dropdown, file_input, question_input],
-        outputs=[answer_output, score_output, explanation_output]
+        outputs=[answer_output, score_output, explanation_output, status_output]
     )
 
 if __name__ == "__main__":