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app.py

@@ -603,17 +603,12 @@ def filter_input_with_llama_guard(user_input, model="llama-guard-3-8b"):
 
 class NutritionBot:
     def __init__(self):
-        """
-        Initialize the NutritionBot class, setting up memory, the LLM client, tools, and the agent executor.
-        """
-
-        # Initialize a memory client to store and retrieve customer interactions
-        #self.memory = MemoryClient(api_key=userdata.get("mem0"))  # Complete the code to define the memory client API key
-        self.memory = MemoryClient(api_key = os.environ["mem0"]) # Complete the code to define the memory client API key
-        client = AsyncMemoryClient()
-
-        # Initialize the Azure OpenAI client using the provided credentials
-        self.client = AzureChatOpenAI(
+      # Initialize a memory client to store and retrieve customer interactions
+      self..memory = MemoryClient(api_key = os.environ["mem0"]) # Complete the code to define the memory client API key
+      client = AsyncMemoryClient()
+      #self.memory = MemoryClient(api_key=userdata.get("mem0"))  # Complete the code to define the memory client API key
+      # Initialize the Azure OpenAI client using the provided credentials
+      self.client = AzureChatOpenAI(
             # model_name="_____",  # Specify the model to use (e.g., GPT-4 optimized version)
             # api_key=config['_____'],  # API key for authentication
             # azure_endpoint=config['_____'],  # Endpoint URL for Azure OpenAI
@@ -624,9 +619,11 @@ class NutritionBot:
             azure_endpoint=config['AZURE_OPENAI_ENDPOINT'],  # Endpoint URL for Azure OpenAI
             api_version=config['AZURE_OPENAI_APIVERSION'],  # API version being used
             temperature=0  # Controls randomness in responses; 0 ensures deterministic results
-        )
-
-        # Define tools available to the chatbot, such as web search
+      )
+      """
+      Initialize the NutritionBot class, setting up memory, the LLM client, tools, and the agent executor.
+      """
+      # Define tools available to the chatbot, such as web search
         tools = [agentic_rag]
 
         # Define the system prompt to set the behavior of the chatbot
@@ -645,7 +642,7 @@ class NutritionBot:
 
         # Wrap the agent in an executor to manage tool interactions and execution flow
         self.agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
-
+        
 
     def store_customer_interaction(self, user_id: str, message: str, response: str, metadata: Dict = None):
         """