Update app.py

app.py

@@ -137,7 +137,7 @@ Examples:
 
     chain = expand_prompt | llm | StrOutputParser()
     expanded_query = chain.invoke({"query": state['query'], "query_feedback":state["query_feedback"]})
-    # print("expanded_query", expanded_query) #uncomment this line to see expanded query
+    print("expanded_query", expanded_query) #uncomment this line to see expanded query
     state["expanded_query"] = expanded_query
     return state
 
@@ -168,11 +168,11 @@ def retrieve_context(state):
     """
     print("---------retrieve_context---------")
     query = state['expanded_query']  # Complete the code to define the key for the expanded query
-    #print("Query used for retrieval:", query)  # Debugging: Print the query
+    print("Query used for retrieval:", query)  # Debugging: Print the query
 
     # Retrieve documents from the vector store
     docs = retriever.invoke(query)
-    #print("Retrieved documents:", docs)  # Debugging: Print the raw docs object
+    print("Retrieved documents:", docs)  # Debugging: Print the raw docs object
 
     # Extract both page_content and metadata from each document
     context = [
@@ -186,7 +186,7 @@ def retrieve_context(state):
     ]
     state['context'] = context  # Complete the code to define the key for storing the context
     #print("Extracted context with metadata:", context)  # Debugging: Print the extracted context
-    #print(f"Groundedness loop count: {state['groundedness_loop_count']}")
+    print(f"Groundedness loop count: {state['groundedness_loop_count']}")
     return state
 
 
@@ -221,7 +221,7 @@ If the context does not contain enough information to answer accurately, clearly
         "feedback": state.get('feedback', 'No feedback provided') # add feedback to the prompt
     })
     state['response'] = response
-    #print("intermediate response: ", response) #uncomment this line to see intermediate response
+    print("intermediate response: ", response) #uncomment this line to see intermediate response
 
     return state
 
@@ -337,7 +337,7 @@ Focus on biblical coherence, faith-based reasoning, and alignment with the theme
 
     # Store response suggestions in a structured format
     feedback = f"Previous Response: {state['response']}\nSuggestions: {chain.invoke({'query': state['query'], 'response': state['response']})}"
-    #print("feedback: ", feedback) #uncomment this line to see feedback
+    print("feedback: ", feedback) #uncomment this line to see feedback
     print(f"State: {state}")
     state['feedback'] = feedback
     return state
@@ -370,7 +370,7 @@ Focus on biblical coherence, faith-based reasoning, and alignment with the theme
 
     # Store refinement suggestions without modifying the original expanded query
     query_feedback = f"Previous Expanded Query: {state['expanded_query']}\nSuggestions: {chain.invoke({'query': state['query'], 'expanded_query': state['expanded_query']})}"
-    #print("query_feedback: ", query_feedback)
+    print("query_feedback: ", query_feedback)
     print(f"Groundedness loop count: {state['groundedness_loop_count']}")
     state['query_feedback'] = query_feedback
     return state
@@ -710,7 +710,7 @@ def spritual_assistant_streamlit():
                 st.session_state.user_id = user_id
                 st.session_state.chat_history.append({
                     "role": "assistant",
-                    "content": f"Welcome ようこそ , {user_id}! How can I guide you in your spiritual path today?"
+                    "content": f"Welcome ようこそ , {user_id}! How can I guide you in your spiritual path today? 今日、あなたの精神的な道をどのように導くことができるでしょうか? "
                 })
                 st.session_state.login_submitted = True
         if st.session_state.get("login_submitted", False):