Update app.py

app.py

@@ -56,8 +56,45 @@ sql_chain = SQLDatabaseChain(llm=llm, database=engine, verbose=True)
 
 # Step 4: Define the callback function
 def process_input():
-    # (Use the updated process_input function provided earlier)
-    # ...
+    user_prompt = st.session_state['user_input']
+
+    if user_prompt:
+        try:
+            # Append user message to history
+            st.session_state.history.append({"role": "user", "content": user_prompt})
+
+            # Use the SQLDatabaseChain to get the response
+            with st.spinner("Processing..."):
+                response = sql_chain.run(user_prompt)
+
+            # Append the assistant's response to the history
+            st.session_state.history.append({"role": "assistant", "content": response})
+
+            # Generate insights based on the response
+            insights_template = """
+            You are an expert data analyst. Based on the user's question and the response provided below, generate a concise analysis that includes key data insights and actionable recommendations. Limit the response to a maximum of 150 words.
+
+            User's Question: {question}
+
+            Response:
+            {response}
+
+            Concise Analysis:
+            """
+            insights_prompt = PromptTemplate(template=insights_template, input_variables=['question', 'response'])
+            insights_chain = LLMChain(llm=llm, prompt=insights_prompt)
+
+            insights = insights_chain.run({'question': user_prompt, 'response': response})
+
+            # Append the assistant's insights to the history
+            st.session_state.history.append({"role": "assistant", "content": insights})
+        except Exception as e:
+            logging.error(f"An error occurred: {e}")
+            assistant_response = f"Error: {e}"
+            st.session_state.history.append({"role": "assistant", "content": assistant_response})
+
+        # Reset user input
+        st.session_state['user_input'] = ''
 
 # Step 5: Display conversation history
 for message in st.session_state.history: