Updating files based on reviewer comments

GoogleCloudPlatform · Aug 20, 2024 · eb9ab02 · eb9ab02
1 parent e9beeef
commit eb9ab02
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Showing 2 changed files with 15 additions and 15 deletions.
diff --git a/applications/rag/frontend/container/application/rag_langchain/rag_chain.py b/applications/rag/frontend/container/application/rag_langchain/rag_chain.py
@@ -60,15 +60,18 @@
 
 
 def get_chat_history(session_id: str) -> PostgresChatMessageHistory:
-    history = PostgresChatMessageHistory.create_sync(
-        engine, session_id=session_id, table_name=CHAT_HISTORY_TABLE_NAME
-    )
-
-    logging.info(
-        f"Retrieving history for session {session_id} with {len(history.messages)}"
-    )
-    return history
+    try:
+        history = PostgresChatMessageHistory.create_sync(
+            engine, session_id=session_id, table_name=CHAT_HISTORY_TABLE_NAME
+        )
 
+        logging.info(
+            f"Retrieving history for session {session_id} with {len(history.messages)}"
+        )
+        return history
+    except Exception as e:
+        logging.error(e)
+        return None
 
 def clear_chat_history(session_id: str):
     history = PostgresChatMessageHistory.create_sync(
@@ -104,7 +107,7 @@ def create_chain() -> RunnableWithMessageHistory:
         )
         return chain_with_history
     except Exception as e:
-        logging.info(e)
+        logging.error(e)
         raise e
 
 def take_chat_turn(
@@ -115,5 +118,5 @@ def take_chat_turn(
         result = chain.invoke({"input": query_text}, config=config)
         return result
     except Exception as e:
-        logging.info(e)
+        logging.error(e)
         raise e
diff --git a/applications/rag/frontend/container/application/vector_storages/cloud_sql.py b/applications/rag/frontend/container/application/vector_storages/cloud_sql.py
@@ -70,15 +70,12 @@ def add_texts(
             raise Exception(f"Error adding texts: {err}")
 
     def similarity_search(
-        self, query_input: dict, k: int = 4, **kwargs: Any
+        self, query: dict, k: int = 4, **kwargs: Any
     ) -> List[Document]:
         try:
+            query_input = query.get("input")
             query_vector = self.embeddings_service.embed_query(query_input)
-<<<<<<< HEAD
             docs = self.vector_store.similarity_search_by_vector(query_vector, k=k)
-=======
-            docs = self.vector_store.similarity_search_by_vector(query_vector, k=4)
->>>>>>> 2d652e30 (Rag langchain chat history (#755))
             return docs
 
         except Exception as err: