Update app.py

app.py

@@ -5,6 +5,10 @@ import chromadb  # High-performance vector database for storing/querying dense v
 from dotenv import load_dotenv  # Loading environment variables from a .env file
 import json  # Parsing and handling JSON data
 
+# Supressing logging to langchain. Remove or comment this block to see logs when debugging
+import logging
+logging.getLogger("langchain").setLevel(logging.ERROR)
+
 # LangChain imports
 from langchain_openai import ChatOpenAI
 from langchain_core.documents import Document  # Document data structures
@@ -137,7 +141,7 @@ Examples:
 
     chain = expand_prompt | llm | StrOutputParser()
     expanded_query = chain.invoke({"query": state['query'], "query_feedback":state["query_feedback"]})
-    print("expanded_query", expanded_query)
+    # print("expanded_query", expanded_query) #uncomment this line to see expanded query
     state["expanded_query"] = expanded_query
     return state
 
@@ -185,7 +189,7 @@ 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("Extracted context with metadata:", context)  # Debugging: Print the extracted context
     #print(f"Groundedness loop count: {state['groundedness_loop_count']}")
     return state
 
@@ -221,7 +225,7 @@ 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)
+    #print("intermediate response: ", response) #uncomment this line to see intermediate response
 
     return state
 
@@ -337,7 +341,7 @@ 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)
+    #print("feedback: ", feedback) #uncomment this line to see feedback
     print(f"State: {state}")
     state['feedback'] = feedback
     return state
@@ -370,7 +374,7 @@ 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