Update app.py

app.py

@@ -19,7 +19,7 @@ from langchain.schema import AIMessage, HumanMessage, SystemMessage
 embeddings = OpenAIEmbeddings()
 
 # Loads database from persisted directory
-db_directory = "./docs/2023_12_06_chroma_db"
+db_directory = "./docs/2023_12_05_chroma_db_v2"
 db = Chroma(persist_directory=db_directory, embedding_function=embeddings)
 
 # This is code that retrieves relevant documents based on a similarity search (in this case, it grabs the top 2 relevant documents or chunks)
@@ -74,11 +74,11 @@ def predict(history, input):
     global is_first_run  # Use the global flag
     if is_first_run:
         context = get_full_context(input)
-        print(context)  # For debugging
+        print(f"Context is as follows: {context}")  # For debugging
         is_first_run = False  # Set the flag to False after the first run
     else:
         context = ""
-
+    
     history_langchain_format = []
     history_langchain_format.append(SystemMessage(content=f"{ORIG_SYSTEM_MESSAGE_PROMPT}, here is the user information: {user_info_simulated}"))
     for human, ai in history: