cheremnm commited on
Commit
4dcf026
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verified ·
1 Parent(s): c62f3f1

Update app.py

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Files changed (1) hide show
  1. app.py +6 -6
app.py CHANGED
@@ -168,11 +168,11 @@ def retrieve_context(state):
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  """
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  print("---------retrieve_context---------")
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  query = state['expanded_query'] # Complete the code to define the key for the expanded query
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- print("Query used for retrieval:", query) # Debugging: Print the query
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  # Retrieve documents from the vector store
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  docs = retriever.invoke(query)
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- print("Retrieved documents:", docs) # Debugging: Print the raw docs object
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  # Extract both page_content and metadata from each document
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  context = [
@@ -221,7 +221,7 @@ If the context does not contain enough information to answer accurately, clearly
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  "feedback": state.get('feedback', 'No feedback provided') # add feedback to the prompt
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  })
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  state['response'] = response
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- print("intermediate response: ", response) #uncomment this line to see intermediate response
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  return state
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@@ -337,7 +337,7 @@ Focus on biblical coherence, faith-based reasoning, and alignment with the theme
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  # Store response suggestions in a structured format
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  feedback = f"Previous Response: {state['response']}\nSuggestions: {chain.invoke({'query': state['query'], 'response': state['response']})}"
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- print("feedback: ", feedback) #uncomment this line to see feedback
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  print(f"State: {state}")
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  state['feedback'] = feedback
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  return state
@@ -370,7 +370,7 @@ Focus on biblical coherence, faith-based reasoning, and alignment with the theme
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  # Store refinement suggestions without modifying the original expanded query
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  query_feedback = f"Previous Expanded Query: {state['expanded_query']}\nSuggestions: {chain.invoke({'query': state['query'], 'expanded_query': state['expanded_query']})}"
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- print("query_feedback: ", query_feedback)
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  print(f"Groundedness loop count: {state['groundedness_loop_count']}")
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  state['query_feedback'] = query_feedback
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  return state
@@ -659,7 +659,7 @@ Your goal is to walk alongside users on their spiritual journey, offering encour
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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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  """
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  print("---------retrieve_context---------")
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  query = state['expanded_query'] # Complete the code to define the key for the expanded query
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+ #print("Query used for retrieval:", query) # Debugging: Print the query
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  # Retrieve documents from the vector store
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  docs = retriever.invoke(query)
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+ #print("Retrieved documents:", docs) # Debugging: Print the raw docs object
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  # Extract both page_content and metadata from each document
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  context = [
 
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  "feedback": state.get('feedback', 'No feedback provided') # add feedback to the prompt
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  })
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  state['response'] = response
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+ #print("intermediate response: ", response) #uncomment this line to see intermediate response
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  return state
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  # Store response suggestions in a structured format
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  feedback = f"Previous Response: {state['response']}\nSuggestions: {chain.invoke({'query': state['query'], 'response': state['response']})}"
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+ #print("feedback: ", feedback) #uncomment this line to see feedback
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  print(f"State: {state}")
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  state['feedback'] = feedback
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  return state
 
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  # Store refinement suggestions without modifying the original expanded query
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  query_feedback = f"Previous Expanded Query: {state['expanded_query']}\nSuggestions: {chain.invoke({'query': state['query'], 'expanded_query': state['expanded_query']})}"
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+ #print("query_feedback: ", query_feedback)
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  print(f"Groundedness loop count: {state['groundedness_loop_count']}")
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  state['query_feedback'] = query_feedback
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  return state
 
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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"""