diff --git a/querybook/server/const/ai_assistant.py b/querybook/server/const/ai_assistant.py
index 486a11442..1db8b888f 100644
--- a/querybook/server/const/ai_assistant.py
+++ b/querybook/server/const/ai_assistant.py
@@ -25,6 +25,6 @@ class AICommandType(Enum):
 # how many docs to fetch from vector store, it may include both table and query summary docs and they need additional processing.
 DEFAULT_VECTOR_STORE_FETCH_LIMIT = 30
 # how many tables to return from vector table search eventually
-DEFAUTL_TABLE_SEARCH_LIMIT = 10
+DEFAULT_TABLE_SEARCH_LIMIT = 10
 # how many tables to select for text-to-sql
-DEFAUTL_TABLE_SELECT_LIMIT = 3
+DEFAULT_TABLE_SELECT_LIMIT = 3
diff --git a/querybook/server/lib/ai_assistant/base_ai_assistant.py b/querybook/server/lib/ai_assistant/base_ai_assistant.py
index 0096c107a..b5b1ae3f1 100644
--- a/querybook/server/lib/ai_assistant/base_ai_assistant.py
+++ b/querybook/server/lib/ai_assistant/base_ai_assistant.py
@@ -7,7 +7,7 @@
 
 from app.db import with_session
 from const.ai_assistant import (
-    DEFAUTL_TABLE_SELECT_LIMIT,
+    DEFAULT_TABLE_SELECT_LIMIT,
     MAX_SAMPLE_QUERY_COUNT_FOR_TABLE_SUMMARY,
     AICommandType,
 )
@@ -403,7 +403,7 @@ def summarize_query(
     def find_tables(self, metastore_id, question, session=None):
         """Search similar tables from vector store first, and then ask LLM to select most suitable tables for the question.
 
-        It will return at most `DEFAUTL_TABLE_SELECT_LIMIT` tables by default.
+        It will return at most `DEFAULT_TABLE_SELECT_LIMIT` tables by default.
         """
         try:
             tables = get_vector_store().search_tables(
@@ -443,7 +443,7 @@ def find_tables(self, metastore_id, question, session=None):
                 table_docs[full_table_name] = summary
 
             prompt = self._get_table_select_prompt(
-                top_n=DEFAUTL_TABLE_SELECT_LIMIT,
+                top_n=DEFAULT_TABLE_SELECT_LIMIT,
                 table_schemas=table_docs,
                 question=question,
             )
diff --git a/querybook/server/lib/vector_store/base_vector_store.py b/querybook/server/lib/vector_store/base_vector_store.py
index 333d5ead7..a2f82a506 100644
--- a/querybook/server/lib/vector_store/base_vector_store.py
+++ b/querybook/server/lib/vector_store/base_vector_store.py
@@ -3,7 +3,7 @@
 from typing import Literal, Optional
 
 from const.ai_assistant import (
-    DEFAUTL_TABLE_SEARCH_LIMIT,
+    DEFAULT_TABLE_SEARCH_LIMIT,
     DEFAULT_VECTOR_STORE_FETCH_LIMIT,
     DEFAULT_SIMILARITY_SCORE_THRESHOLD,
     DEFAULT_SIMILARITY_SCORE_THRESHOLD_GREAT_MATCH,
@@ -60,7 +60,7 @@ def search_tables(
         text: str,
         search_type: Optional[Literal["table", "query"]] = None,
         threshold=DEFAULT_SIMILARITY_SCORE_THRESHOLD,
-        k=DEFAUTL_TABLE_SEARCH_LIMIT,
+        k=DEFAULT_TABLE_SEARCH_LIMIT,
         fetch_k=DEFAULT_VECTOR_STORE_FETCH_LIMIT,
     ) -> list[tuple[str, int]]:
         """Find tables using embedding based table search.
diff --git a/querybook/server/logic/vector_store.py b/querybook/server/logic/vector_store.py
index 88b94c48e..29669cd08 100644
--- a/querybook/server/logic/vector_store.py
+++ b/querybook/server/logic/vector_store.py
@@ -1,6 +1,6 @@
 from app.db import with_session
 from const.ai_assistant import (
-    DEFAUTL_TABLE_SEARCH_LIMIT,
+    DEFAULT_TABLE_SEARCH_LIMIT,
     MAX_SAMPLE_QUERY_COUNT_FOR_TABLE_SUMMARY,
 )
 from langchain.docstore.document import Document
@@ -154,7 +154,7 @@ def delete_table_doc(table_id: int):
 
 
 def search_tables(
-    metastore_id, keywords, filters=None, limit=DEFAUTL_TABLE_SEARCH_LIMIT
+    metastore_id, keywords, filters=None, limit=DEFAULT_TABLE_SEARCH_LIMIT
 ):
     """search tables from vector store and get the table details from elastic search."""