diff --git a/memgpt/agent_store/db.py b/memgpt/agent_store/db.py
index 8b0e3a85d1..728c81ac5d 100644
--- a/memgpt/agent_store/db.py
+++ b/memgpt/agent_store/db.py
@@ -145,12 +145,14 @@ class PassageModel(Base):
     source_id = Column(String)
 
     # vector storage
-    if config.archival_storage_type == "postgres":
+    if settings.memgpt_pg_uri_no_default:
         from pgvector.sqlalchemy import Vector
 
         embedding = mapped_column(Vector(MAX_EMBEDDING_DIM))
-    else:
+    elif config.archival_storage_type == "sqlite" or config.archival_storage_type == "chroma":
         embedding = Column(CommonVector)
+    else:
+        raise ValueError(f"Unsupported archival_storage_type: {config.archival_storage_type}")
     embedding_config = Column(EmbeddingConfigColumn)
     metadata_ = Column(MutableJson)
 
@@ -177,40 +179,6 @@ def to_record(self):
         )
 
 
-# def get_db_model(
-#    config: MemGPTConfig,
-#    table_name: str,
-#    table_type: TableType,
-#    #user_id: str,
-#    #agent_id: Optional[str] = None,
-#    dialect="postgresql",
-# ):
-#    # Define a helper function to create or get the model class
-#    def create_or_get_model(class_name, base_model, table_name):
-#        if class_name in globals():
-#            return globals()[class_name]
-#        Model = type(class_name, (base_model,), {"__tablename__": table_name, "__table_args__": {"extend_existing": True}})
-#        globals()[class_name] = Model
-#        return Model
-#
-#    if table_type == TableType.ARCHIVAL_MEMORY or table_type == TableType.PASSAGES:
-#        # create schema for archival memory
-#
-#        """Create database model for table_name"""
-#        #class_name = f"{table_name.capitalize()}Model" + dialect
-#        return create_or_get_model(class_name, PassageModel, table_name)
-#
-#    elif table_type == TableType.RECALL_MEMORY:
-#
-#        """Create database model for table_name"""
-#        class_name = f"{table_name.capitalize()}Model" + dialect
-#        return create_or_get_model(class_name, MessageModel, table_name)
-#
-#    else:
-#        raise ValueError(f"Table type {table_type} not implemented")
-#
-
-
 class SQLStorageConnector(StorageConnector):
     def __init__(self, table_type: str, config: MemGPTConfig, user_id, agent_id=None):
         super().__init__(table_type=table_type, config=config, user_id=user_id, agent_id=agent_id)
@@ -386,9 +354,6 @@ def __init__(self, table_type: str, config: MemGPTConfig, user_id, agent_id=None
 
         super().__init__(table_type=table_type, config=config, user_id=user_id, agent_id=agent_id)
 
-        # create table
-        # self.db_model = get_db_model(config, self.table_name, table_type, user_id, agent_id)
-
         # construct URI from enviornment variables
         if settings.pg_uri:
             self.uri = settings.pg_uri
@@ -419,8 +384,8 @@ def __init__(self, table_type: str, config: MemGPTConfig, user_id, agent_id=None
 
         self.session_maker = db_context
         # self.session_maker = sessionmaker(bind=self.engine)
-        # with self.session_maker() as session:
-        #   session.execute(text("CREATE EXTENSION IF NOT EXISTS vector"))  # Enables the vector extension
+        with self.session_maker() as session:
+            session.execute(text("CREATE EXTENSION IF NOT EXISTS vector"))  # Enables the vector extension
 
         ## create table
         # Base.metadata.create_all(self.engine, tables=[self.db_model.__table__])  # Create the table if it doesn't exist
@@ -527,7 +492,6 @@ def __init__(self, table_type: str, config: MemGPTConfig, user_id, agent_id=None
         self.path = os.path.join(self.path, f"sqlite.db")
 
         # Create the SQLAlchemy engine
-        # self.db_model = get_db_model(config, self.table_name, table_type, user_id, agent_id, dialect="sqlite")
         # self.engine = create_engine(f"sqlite:///{self.path}")
         # Base.metadata.create_all(self.engine, tables=[self.db_model.__table__])  # Create the table if it doesn't exist
         # self.session_maker = sessionmaker(bind=self.engine)