Update app.py

app.py

@@ -174,37 +174,38 @@ def main():
         for label, query, color in cloud_buttons:
             cloud_button(label, query, color=color)
 
+        # Handle button click from cloud buttons
         if st.session_state['button_clicked']:
             query = st.session_state['button_clicked']['query']
             st.session_state['chat_history'].append(("User", query, "new"))
             st.session_state['button_clicked'] = None
-            
+            handle_response(query, pdf_path)
+
+        # Handle text input submission
         if st.button("Ask") or (query and query != st.session_state.get('last_query')):
             st.session_state['chat_history'].append(("User", query, "new"))
             st.session_state['last_query'] = query
-
-        if st.session_state['chat_history']:
-            loading_message = st.empty()
-            loading_message.text('Bot is thinking...')
-
-            VectorStore = load_pdf(pdf_path)
-            chain = load_chatbot()
-            docs = VectorStore.similarity_search(query=query, k=3)
-            with get_openai_callback() as cb:
-                response = chain.run(input_documents=docs, question=query)
-
-            st.session_state['chat_history'].append(("Bot", response, "new"))
-
-            new_messages = st.session_state['chat_history'][-2:]
-            for chat in new_messages:
-                background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
-                st.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
-
-            st.write("<script>document.getElementById('response').scrollIntoView();</script>", unsafe_allow_html=True)
-
-            loading_message.empty()
-
-        st.session_state['chat_history'] = [(sender, msg, "old") for sender, msg, _ in st.session_state['chat_history']]
+            handle_response(query, pdf_path)
+
+def handle_response(query, pdf_path):
+    loading_message = st.empty()
+    loading_message.text('Bot is thinking...')
+
+    VectorStore = load_pdf(pdf_path)
+    chain = load_chatbot()
+    docs = VectorStore.similarity_search(query=query, k=3)
+    with get_openai_callback() as cb:
+        response = chain.run(input_documents=docs, question=query)
+
+    st.session_state['chat_history'].append(("Bot", response, "new"))
+    new_messages = st.session_state['chat_history'][-2:]
+    for chat in new_messages:
+        background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
+        st.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
+
+    st.write("<script>document.getElementById('response').scrollIntoView();</script>", unsafe_allow_html=True)
+    loading_message.empty()
+    st.session_state['chat_history'] = [(sender, msg, "old") for sender, msg, _ in st.session_state['chat_history']]
 
 if __name__ == "__main__":
     main()