Update app.py

app.py

@@ -1,5 +1,3 @@
-
-
 import gradio as gr
 from PIL import Image
 import torch
@@ -123,6 +121,7 @@ def predict_xray(image):
             <h4>Summary:</h4>
             <p><b>Diagnosis:</b> {top_condition}</p>
             <p><b>Confidence Level:</b> {confidence:.2f}%</p>
+            <p><b>Recommendation:</b> {info['recommendation']}</p>
         </div>
         """
 
@@ -165,18 +164,16 @@ def create_interface():
                     img_input = gr.Image(label="Upload Chest X-ray", type="pil")
                     img_output = gr.HTML()
                     summary_output = gr.HTML(label="Summary Result")
-                gr.Button("Analyze X-ray").click(predict_xray, inputs=img_input, outputs=[img_output, summary_output])
+                gr.Button("Analyze X-ray", elem_id="analyze_button").style(width=200).click(predict_xray, inputs=img_input, outputs=[img_output, summary_output])
 
             with gr.TabItem("Report Analysis"):
                 pdf_input = gr.File(label="Upload PDF Report", file_types=[".pdf"])
                 pdf_output = gr.Textbox(label="Extracted Summary", lines=10)
                 summary_output_report = gr.Textbox(label="Summary Result", lines=5)
-                gr.Button("Analyze Report").click(analyze_report, inputs=pdf_input, outputs=[pdf_output, summary_output_report])
+                gr.Button("Analyze Report", elem_id="analyze_button").style(width=200).click(analyze_report, inputs=pdf_input, outputs=[pdf_output, summary_output_report])
 
     return demo
 
 if __name__ == "__main__":
     demo = create_interface()
     demo.launch(server_port=7860, ssr_mode=False)
-
-