jenngang commited on
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0636e10
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1 Parent(s): 13b7412

Upload app.py with huggingface_hub

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  1. app.py +13 -5
app.py CHANGED
@@ -677,7 +677,7 @@ class NutritionBot:
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  context += "---\n"
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  # Print context for debugging purposes
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- #st.write("Context: ", context)
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  # Prepare a prompt combining past context and the current query
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  prompt = f"""
@@ -691,7 +691,7 @@ class NutritionBot:
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  #st.write("Context: ", prompt)
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  # Generate a response using the agent
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- response = self.agent_executor.invoke({"input": prompt, "agent_scratchpad": ''})
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  st.write("Context: ", response)
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  # Store the current interaction for future reference
@@ -763,7 +763,13 @@ def nutrition_disorder_streamlit():
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  # Filter input using Llama Guard
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  filtered_result = filter_input_with_llama_guard(user_query) # Blank #2: Fill in with the function name for filtering input (e.g., filter_input_with_llama_guard)
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- filtered_result = filtered_result.replace("\n", " ") # Normalize the result
 
 
 
 
 
 
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  # Check if input is safe based on allowed statuses
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  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")
@@ -771,11 +777,13 @@ def nutrition_disorder_streamlit():
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  try:
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  if 'chatbot' not in st.session_state:
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  st.session_state.chatbot = NutritionBot() # Blank #6: Fill in with the chatbot class initialization (e.g., NutritionBot)
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- #st.write("chatbot instantiated - calling handle_customer_query...")
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-
 
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  response = st.session_state.chatbot.handle_customer_query(st.session_state.user_id, user_query)
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  #st.write("response is returned.")
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  # Blank #7: Fill in with the method to handle queries (e.g., handle_customer_query)
 
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  st.write(response)
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  st.session_state.chat_history.append({"role": "assistant", "content": response})
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  except Exception as e:
 
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  context += "---\n"
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  # Print context for debugging purposes
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+ print("Context: ", context)
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  # Prepare a prompt combining past context and the current query
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  prompt = f"""
 
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  #st.write("Context: ", prompt)
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  # Generate a response using the agent
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+ response = self.agent_executor.invoke({"input": prompt})
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  st.write("Context: ", response)
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  # Store the current interaction for future reference
 
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  # Filter input using Llama Guard
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  filtered_result = filter_input_with_llama_guard(user_query) # Blank #2: Fill in with the function name for filtering input (e.g., filter_input_with_llama_guard)
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+ #filtered_result = filtered_result.replace("\n", " ") # Normalize the result
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+ if filtered_result is None:
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+ print("Agent: Sorry, I encountered an error while filtering your input. Please try again.")
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+ continue
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+ else:
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+ filtered_result = filtered_result.replace("\n", " ") # Normalize the result
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+ print(f"filtered_result (2): {filtered_result}")
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  # Check if input is safe based on allowed statuses
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  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")
 
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  try:
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  if 'chatbot' not in st.session_state:
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  st.session_state.chatbot = NutritionBot() # Blank #6: Fill in with the chatbot class initialization (e.g., NutritionBot)
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+ #st.write("chatbot is calling handle_customer_query...")
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+ #st.write("user_id: ", st.session_state.user_id)
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+ #st.write("user_query: ", user_query)
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  response = st.session_state.chatbot.handle_customer_query(st.session_state.user_id, user_query)
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  #st.write("response is returned.")
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  # Blank #7: Fill in with the method to handle queries (e.g., handle_customer_query)
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+
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  st.write(response)
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  st.session_state.chat_history.append({"role": "assistant", "content": response})
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  except Exception as e: