Update my_memory_logic.py

my_memory_logic.py

@@ -12,46 +12,30 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
 ###############################################################################
 # 1) In-memory store: session_id -> ChatMessageHistory
 ###############################################################################
-store = {}  # e.g., { "abc123": ChatMessageHistory(...) }
+store = {}  # e.g. { "abc123": ChatMessageHistory() }
 
 def get_session_history(session_id: str) -> BaseChatMessageHistory:
-    """
-    Retrieve or create a ChatMessageHistory object for the given session_id.
-    This ensures each session_id has its own conversation history.
-    """
     if session_id not in store:
         store[session_id] = ChatMessageHistory()
     return store[session_id]
 
 ###############################################################################
-# 2) Create the RunnableWithMessageHistory (session-based chain)
+# 2) Create RunnableWithMessageHistory
 ###############################################################################
-# This wraps your `pipeline_runnable` so it automatically reads/writes
-# conversation history from get_session_history for each session.
 conversational_rag_chain = RunnableWithMessageHistory(
-    pipeline_runnable,               # the Runnable from pipeline.py
-    get_session_history,             # fetches or creates ChatMessageHistory by session_id
-    input_messages_key="input",      # key in the dict for user's new query
-    history_messages_key="chat_history",  # key for existing chat logs
-    output_messages_key="answer"      # key for final output
+    pipeline_runnable,
+    get_session_history,
+    input_messages_key="input",
+    history_messages_key="chat_history",
+    output_messages_key="answer"
 )
 
 ###############################################################################
-# 3) A convenience function to run a query with session-based memory
+# 3) Convenience function for session-based memory
 ###############################################################################
 def run_with_session_memory(user_query: str, session_id: str) -> str:
-    """
-    A helper that calls our `conversational_rag_chain` 
-    with a given session_id. Returns the final 'answer'.
-    """
-    # We invoke the chain with the user query; 
-    # the chain automatically updates the session’s chat history.
     response = conversational_rag_chain.invoke(
         {"input": user_query},
-        config={
-            "configurable": {
-                "session_id": session_id
-            }
-        }
+        config={"configurable": {"session_id": session_id}}
     )
-    return response["answer"]
+    return response["answer"]