Update app.py

app.py

@@ -191,11 +191,29 @@ else:
     documents = st.session_state["documents"]
     vector_db = st.session_state["vector_db"]
 
-end_time = time.time()
-print(f"Loading and processing PDFs & vector database took {end_time - start_time:.4f} seconds")
-
-start_time = time.time()
 retriever = vector_db.as_retriever()
+with st.sidebar:
+    st.title("Conversation History")
+    
+    if st.button("New Session 🔄"):
+        # Clear all conversation related session states
+        st.session_state.messages = []
+        st.session_state.messages.append({
+            "role": "assistant",
+            "content": "👋 Hello! I'm Dr. Radha, your AI-powered Organic Farming Consultant. How can I assist you today?"
+        })
+        st.session_state.conversation_memory.clear()
+        st.session_state.session_id = str(uuid.uuid4())
+        st.rerun()
+        # Display conversation history
+    st.subheader("Previous Conversations")
+    for message in st.session_state.messages[1:]:  # Skip the initial greeting
+        if message["role"] == "user":
+            st.text("You:")
+            st.text_area("", message["content"], height=50, disabled=True, key=f"hist_{uuid.uuid4()}")
+        else:
+            st.text("Dr. Radha:")
+            st.text_area("", message["content"], height=100, disabled=True, key=f"hist_{uuid.uuid4()}")
 
 prompt_template = """As an expert organic farming consultant with specialization in Agro-Homeopathy, analyze the following context and question to provide a clear, structured response.
 Context: {context}
@@ -286,28 +304,6 @@ fallback_chain = LLMChain(
     memory=st.session_state.conversation_memory
 )
 
-with st.sidebar:
-    st.title("Conversation History")
-    
-    if st.button("New Session 🔄"):
-        # Clear all conversation related session states
-        st.session_state.messages = []
-        st.session_state.messages.append({
-            "role": "assistant",
-            "content": "👋 Hello! I'm Dr. Radha, your AI-powered Organic Farming Consultant. How can I assist you today?"
-        })
-        st.session_state.conversation_memory.clear()
-        st.session_state.session_id = str(uuid.uuid4())
-        st.rerun()
-        # Display conversation history
-    st.subheader("Previous Conversations")
-    for message in st.session_state.messages[1:]:  # Skip the initial greeting
-        if message["role"] == "user":
-            st.text("You:")
-            st.text_area("", message["content"], height=50, disabled=True, key=f"hist_{uuid.uuid4()}")
-        else:
-            st.text("Dr. Radha:")
-            st.text_area("", message["content"], height=100, disabled=True, key=f"hist_{uuid.uuid4()}")
 
 # Replace your existing chat container and form section with this:
 chat_container = st.container()