Update app.py

app.py

@@ -104,7 +104,7 @@ if not st.session_state.chunked:  # Ensure chunking only happens once
         st.session_state.documents = cached_chunks
         st.session_state.chunked = True
 
-# Step 3: Chunking 
+# Step 3: Chunking (Only Happens Once)
 if st.session_state.pdf_loaded and not st.session_state.chunked:
     with st.spinner("Chunking the document..."):
         try:
@@ -188,9 +188,9 @@ if query:
         #st.write("Extracted Context (page_content):", context)
         #st.write("Number of Extracted Contexts:", len(context))
         
-        #st.write("📄 **Relevant Passages Retrieved:**")
-        #for idx, doc in enumerate(contexts):
-            #st.write(f"**Excerpt {idx+1}:** {doc.page_content}")
+        st.write("📄 **Relevant Passages Retrieved:**")
+        for idx, doc in enumerate(contexts):
+            st.write(f"**Excerpt {idx+1}:** {doc.page_content}")
 
         
         relevancy_prompt = """You are an expert judge tasked with evaluating whether the  EACH OF THE CONTEXT provided in the CONTEXT LIST is self sufficient to answer the QUERY asked.
@@ -316,30 +316,24 @@ if query:
 
         #st.subheader('final_output["relevancy_response"]')
         #st.write(final_output["relevancy_response"] )
-        
-        
-        st.markdown("## 💡 **Final Answer:**")
-        st.success(final_output["final_response"] if final_output["final_response"] else "⚠️ No clear answer found based on retrieved content.")
-
-        # 📂 Expand for Details
-        with st.expander("📖 **View Detailed Processing (Relevance, Retrieved Contexts, Analysis)**"):
-            # 📌 Relevance Analysis
-            st.markdown("### 📌 **Relevance Analysis**")
-            if isinstance(final_output["relevancy_response"], list):
-                for item in final_output["relevancy_response"]:
-                    st.write(f"✅ **Context {item.get('content', 'N/A')} - Score: {item.get('score', 'N/A')}**")
-                    st.write(f"**Reasoning:** {item.get('Reasoning', 'No explanation provided.')}")
-            else:
-                st.warning("⚠️ No relevance analysis available.")
-
-            # 📚 Retrieved Contexts
-            st.markdown("### 📚 **Retrieved Contexts**")
-            if isinstance(final_output["relevant_contexts"], list):
-                for idx, doc in enumerate(final_output["relevant_contexts"], 1):
-                    st.write(f"🔹 **Context {idx}:** {doc}")
-            else:
-                st.warning("⚠️ No retrieved context available.")
-
-            # 🔍 Retrieved Context Numbers
-            st.markdown("### 🔍 **Relevant Context Numbers**")
-            st.write(final_output["context_number"])
+
+        st.write("📌 **Relevance Analysis:**")
+        if isinstance(final_output["relevancy_response"], list):
+            for item in final_output["relevancy_response"]:
+                st.write(f"✅ **Context {item.get('content', 'N/A')} - Score: {item.get('score', 'N/A')}**")
+                st.write(f"**Reasoning:** {item.get('Reasoning', 'No explanation provided.')}")
+        else:
+            st.write("⚠️ No relevance analysis available.")
+
+
+        st.subheader('final_output["context_number"]')
+        st.write(final_output["context_number"])
+
+        st.subheader('final_output["relevant_contexts"]')
+        st.write(final_output["relevant_contexts"])
+
+        #st.subheader('final_output["final_response"]')
+        #st.write(final_output["final_response"])
+
+        st.subheader("📢 **Final Answer:**")
+        st.write(final_output["final_response"] if final_output["final_response"] else "⚠️ No clear answer found based on retrieved content.")