Update app.py

app.py

@@ -29,19 +29,19 @@ collection_name_qna = 'report_10K_db'
 persisted_vectordb_location = 'report_10K_db'
 
 # Load the persisted vectorDB
-print("before")
+
 vectorstore_persisted = Chroma(
     collection_name='report_10K_db',
     persist_directory='./report_10K_db',
     embedding_function=embedding_model
 )
-print(vectorstore_persisted.similarity_search("aws AI presence",k=4))
+
 vectorstore_retriever = vectorstore_persisted.as_retriever(
     search_type='similarity',
     search_kwargs={'k': 5}
 )
 
-print("after")
+
 # Prepare the logging functionality
 
 log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
@@ -107,7 +107,7 @@ def predict(user_input,company):
     # Create context_for_query
     user_input = user_input
     relevant_document_chunks = vectorstore_retriever.get_relevant_documents(user_input,k=5,filter={"source":filter_company})
-    print("relevant_document_chunks",relevant_document_chunks)
+    
     context_list = [d.page_content for d in relevant_document_chunks]
     context_for_query = ". ".join(context_list)
     print("context_for_query",context_for_query)