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app.py

@@ -57,7 +57,8 @@ from datetime import datetime
 api_key = config.get("API_KEY")
 endpoint = config.get("OPENAI_API_BASE")
 groq_api_key = config.get('LLAMA_API_KEY') # llama_api_key = os.environ['GROQ_API_KEY']
-MEM0_api_key = config.get('mem0') # MEM0_api_key = os.environ['mem0']
+MEM0_api_key = config.get('MEM0_API_KEY') # MEM0_api_key = os.environ['mem0']
+my_api_key = config.get("MY_API_KEY")
 
 # Initialize the OpenAI embedding function for Chroma
 embedding_function = chromadb.utils.embedding_functions.OpenAIEmbeddingFunction(
@@ -480,7 +481,7 @@ def create_workflow() -> StateGraph:
         should_continue_precision, # ___________,  # Use the conditional function
         {
             "pass": END, # ___________,              # If precise, complete the workflow.
-            "refine_query": "refine_query" # ___________,  # If imprecise, refine the query.
+            "refine_query": "refine_query", # ___________,  # If imprecise, refine the query.
             "max_iterations_reached": "max_iterations_reached" # ___________  # If max loops reached, exit.
         }
     )
@@ -514,8 +515,8 @@ def agentic_rag(query: str):
         "context": [],  # Retrieved documents (initially empty)
         "response": "", # "_____",  # Complete the code to define the AI-generated response
         "precision_score": 0.0, # _____,  # Complete the code to define the precision score of the response
-        "groundedness_score": 0.0 # _____,  # Complete the code to define the groundedness score of the response
-        "groundedness_loop_count": 0 # _____,  # Complete the code to define the counter for groundedness loops
+        "groundedness_score": 0.0, # _____,  # Complete the code to define the groundedness score of the response
+        "groundedness_loop_count": 0, # _____,  # Complete the code to define the counter for groundedness loops
         "precision_loop_count": 0, # _____,  # Complete the code to define the counter for precision loops
         "feedback": "", # "_____",  # Complete the code to define the feedback
         "query_feedback": "", # "_____",  # Complete the code to define the query feedback
@@ -767,7 +768,7 @@ def nutrition_disorder_streamlit():
             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")
                 try:
                     if 'chatbot' not in st.session_state:
-                        st.session_state.chatbot = NutritionBot # () __________()  # Blank #6: Fill in with the chatbot class initialization (e.g., NutritionBot)
+                        st.session_state.chatbot = NutritionBot() # __________()  # Blank #6: Fill in with the chatbot class initialization (e.g., NutritionBot)
                     response = st.session_state.chatbot.handle_customer_query(st.session_state.user_id, user_query) # __________(st.session_state.user_id, user_query)
                     # Blank #7: Fill in with the method to handle queries (e.g., handle_customer_query)
                     st.write(response)