Update app.py

app.py

@@ -148,6 +148,8 @@ if uploaded_files:
         classification = classifier(user_input, 
                                   ["financial", "other"],
                                   multi_label=False)
+        print(f"-- Guard rail check is completed for query with prob:{classification['scores'][0]}")
+        
         if classification['scores'][0] < 0.2:
             st.error("Query not related to financial. Ask about financial related queries")
             st.stop()
@@ -163,6 +165,7 @@ if uploaded_files:
             ranked_docs = [initial_docs[i] for i in sorted_indices]
             filtered_docs = [d for d, s in zip(ranked_docs, rerank_scores) 
                            if s > rerank_threshold][:7]
+            print(f"-- Retrieved chunks:{filtered_docs}")
             
             # Confidence Calculation
             confidence_score = np.mean(rerank_scores[sorted_indices][:3]) * 100
@@ -170,6 +173,8 @@ if uploaded_files:
 
             # Response Generation
             context = "\n".join([doc.page_content for doc in filtered_docs])
+            print(f"-- Retrieved context:{context}")
+            
             analysis = llm_chain.run(
                 context=context, 
                 question=user_input