Skip to content

Function Declaration error caused by None, returning schema error - O… #5557

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Chris-Jones-Qodea wants to merge 2 commits into
base: main
Choose a base branch
from
+5 −5
Open

Function Declaration error caused by None, returning schema error - O… #5557

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
75c3bfa
Function Declaration error caused by None, returning schema error - O…
Chris-Jones-Qodea Apr 30, 2026
2b85933
Merge branch 'main' into main
rohityan Apr 30, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 5 additions & 5 deletions src/google/adk/tools/bigquery/search_tool.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
from __future__ import annotations

import logging
from typing import Any
from typing import Any, Optional

from google.api_core import exceptions as api_exceptions
from google.auth.credentials import Credentials
Expand All @@ -42,11 +42,11 @@ def search_catalog(
*,
credentials: Credentials,
settings: BigQueryToolConfig,
location: str | None = None,
location: Optional[str] = None,
page_size: int = 10,
project_ids_filter: list[str] | None = None,
dataset_ids_filter: list[str] | None = None,
types_filter: list[str] | None = None,
project_ids_filter: Optional[list[str]] = None,
dataset_ids_filter: Optional[list[str]] = None,
types_filter: Optional[list[str]] = None,
) -> dict[str, Any]:
"""Finds BigQuery datasets and tables using natural language semantic search via Dataplex.

Expand Down
Loading