Update app.py

assigned PCI and SPA to a different container

app.py

@@ -33,9 +33,9 @@ def run_app(feedback_file, adoption_file, num_participants, target_population, h
     pai_1, pai_2 = pai_calculator.compute_pai(participants_by_group)
 
     # Step 4: Interpret results
-    typology = assign_typology(pai_1, pai_2, high_th, th)
+    typology = assign_typology(pai_1, high_th, th)
 
-    return sentiment_metrics, typology
+    return sentiment_metrics, typology, pai_2
 
 # ========== GRADIO INTERFACE ==========
 with gr.Blocks() as demo:
@@ -86,17 +86,19 @@ with gr.Blocks() as demo:
 
     # ----- OUTPUTS -----
     with gr.Row():
-        with gr.Column(scale=4):
+        with gr.Column(scale=1):
             gr.Markdown("## 🗨️📈Public Sentiment Analytics")
             sentiment_metrics_output = gr.JSON(label="Sentiment Metrics")
-        with gr.Column(scale=3):
-            gr.Markdown("## 📃🩺Program Diagnosis")
-            typology_output = gr.JSON(label="Typology Assignment") 
+            gr.Markdown("## 📃🩺Program Diagnosis Pt.1")
+            pai_2_output = gr.JSON(label="Typology Assignment Pt.1")
+        with gr.Column(scale=1):
+            gr.Markdown("## 📃🩺Program Diagnosis Pt.2")
+            typology_output = gr.JSON(label="Typology Assignment Pt.2") 
 
     btn.click(
         fn=run_app,
         inputs=[feedback_file_input, adoption_file_input, num_participants_input, target_population_input, high_th_input, th_input],
-        outputs=[sentiment_metrics_output, typology_output]
+        outputs=[sentiment_metrics_output, typology_output, pai_2_output]
     )
     
 demo.launch()