Update app.py

app.py

@@ -136,18 +136,18 @@ For document-related questions, search and retrieve information from the uploade
 For SQL database-related questions, only use the fields available in the collegedb schema, which includes tables such as buildings, classrooms, college, course, faculty, interns, person, section, student, and textbook.
 {{agent_scratchpad}}
 Question: {{input}}
-
+{memory.buffer}
 """
 
-#{memory.buffer}
+
 prompt = ChatPromptTemplate.from_template(prompt_template)
 
 # Initialize the agent with memory
-#llm_with_memory = llm.bind(memory=memory)
-llm_with_memory = llm.bind()
+llm_with_memory = llm.bind(memory=memory)
+#llm_with_memory = llm.bind()
 agent = create_tool_calling_agent(llm_with_memory, tools, prompt)
-agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
-#agent_executor = AgentExecutor(agent=agent, tools=tools, memory= memory, verbose=True)
+#agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
+agent_executor = AgentExecutor(agent=agent, tools=tools, memory= memory, verbose=True)
 
 # Define the interface function
 max_iterations = 5
@@ -171,9 +171,9 @@ def answer_question(user_question, city="United Arab Emirates"):
         return "The agent could not generate a valid response within the iteration limit."
 
     # Print memory buffer for debugging
-    #print("Memory Buffer:", memory.buffer)
+    print("Memory Buffer:", memory.buffer)
     # Print memory buffer for debugging
-    #print("Memory Buffer11:", memory.load_memory_variables({}))
+    print("Memory Buffer11:", memory.load_memory_variables({}))
 
 
     # Format the response text