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app.py

@@ -572,19 +572,22 @@ class NutritionBot:
         """
         Initialize the NutritionBot class, setting up memory, the LLM client, tools, and the agent executor.
         """
-
+        print("Entered NutritionBot...")
         # Initialize a memory client to store and retrieve customer interactions
         self.memory = MemoryClient(api_key=MEM0_api_key) # userdata.get("mem0"))  # Complete the code to define the memory client API key
+        print("Got memory...")
 
         # Initialize the OpenAI client using the provided credentials
         self.client = ChatOpenAI(
             model_name="gpt-4o",  # Used gpt-4o to get improved results; Specify the model to use (e.g., GPT-4 optimized version)
-            api_key=api_key, # API key for authentication
+            api_key=my_api_key, # API key for authentication
             temperature=0  # Controls randomness in responses; 0 ensures deterministic results
         )
+        print("Got client...")
 
         # Define tools available to the chatbot, such as web search
         tools = [agentic_rag]
+        print("Got tools...")
 
         # Define the system prompt to set the behavior of the chatbot
         system_prompt = """You are a caring and knowledgeable Medical Support Agent, specializing in nutrition disorder-related guidance. Your goal is to provide accurate, empathetic, and tailored nutritional recommendations while ensuring a seamless customer experience.
@@ -600,6 +603,7 @@ class NutritionBot:
                           Your primary goal is to help customers make informed nutrition decisions that align with their health conditions and personal preferences.
 
         """
+        print("Got system prompt...")
 
         # Build the prompt template for the agent
         prompt = ChatPromptTemplate.from_messages([
@@ -607,12 +611,15 @@ class NutritionBot:
             ("human", "{input}"),  # Placeholder for human input
             ("placeholder", "{agent_scratchpad}")  # Placeholder for intermediate reasoning steps
         ])
+        print("Got user prompt...")
 
         # Create an agent capable of interacting with tools and executing tasks
         agent = create_tool_calling_agent(self.client, tools, prompt)
+        print("Got agent...")
 
         # Wrap the agent in an executor to manage tool interactions and execution flow
         self.agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
+        print("Got executor...")
 
 
     def store_customer_interaction(self, user_id: str, message: str, response: str, metadata: Dict = None):
@@ -678,6 +685,7 @@ class NutritionBot:
 
         # Retrieve relevant past interactions for context
         relevant_history = self.get_relevant_history(user_id, query)
+        print("Got history...")
 
         # Build a context string from the relevant history
         context = "Previous relevant interactions:\n"
@@ -698,9 +706,11 @@ class NutritionBot:
 
         Provide a helpful response that takes into account any relevant past interactions.
         """
+        print("Got prepare for invoke...")
 
         # Generate a response using the agent
         response = self.agent_executor.invoke({"input": prompt})
+        print("Got response...")
 
         # Store the current interaction for future reference
         self.store_customer_interaction(
@@ -709,6 +719,8 @@ class NutritionBot:
             response=response["output"],
             metadata={"type": "support_query"}
         )
+        print("Got output...")
+
 
         # Return the chatbot's response
         return response['output']
@@ -775,10 +787,17 @@ def nutrition_disorder_streamlit():
 
             # Check if input is safe based on allowed statuses
             if filtered_result in ["safe", "safe S7", "safe S6"]: # Blanks #3, #4, #5: Fill in with allowed safe statuses (e.g., "safe", "unsafe S7", "unsafe S6")
+                print("Got a safe input...")
                 try:
                     if 'chatbot' not in st.session_state:
+                        print("In not in st.session_state...")
                         st.session_state.chatbot = NutritionBot() # Blank #6: Fill in with the chatbot class initialization (e.g., NutritionBot)
+                    else:
+                        print("In st.session_state...")
+
+                    print("Getting response...")
                     response = st.session_state.chatbot.handle_customer_query(st.session_state.user_id, user_query) 
+                    print(f"Got response: {response}")
                     # Blank #7: Fill in with the method to handle queries (e.g., handle_customer_query)
                     st.write(response)
                     st.session_state.chat_history.append({"role": "assistant", "content": response})
@@ -787,9 +806,13 @@ def nutrition_disorder_streamlit():
                     st.write(error_msg)
                     st.session_state.chat_history.append({"role": "assistant", "content": error_msg})
             else:
-                inappropriate_msg = "I apologize, but I cannot process that input as it may be inappropriate. Please try again."
-                st.write(inappropriate_msg)
-                st.session_state.chat_history.append({"role": "assistant", "content": inappropriate_msg})
+                try:
+                  inappropriate_msg = "I apologize, but I cannot process that input as it may be inappropriate. Please try again."
+                  st.write(inappropriate_msg)
+                  st.session_state.chat_history.append({"role": "assistant", "content": inappropriate_msg})
+                except Exception as e:
+                  st.write(str(e))
+                  st.session_state.chat_history.append({"role": "assistant", "content": str(e)})
 
 if __name__ == "__main__":
     nutrition_disorder_streamlit()