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chore: import upstream snapshot with attribution
2026-07-13 13:25:13 +08:00

226 lines
7.1 KiB
Python

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations
import textwrap
from unittest import mock
from google.adk.tools.base_tool import BaseTool
from google.adk.tools.spanner import query_tool
from google.adk.tools.spanner import settings
from google.adk.tools.spanner.settings import QueryResultMode
from google.adk.tools.spanner.settings import SpannerToolSettings
from google.adk.tools.spanner.spanner_credentials import SpannerCredentialsConfig
from google.adk.tools.spanner.spanner_toolset import SpannerToolset
from google.adk.tools.tool_context import ToolContext
from google.auth.credentials import Credentials
import pytest
async def get_tool(
name: str, tool_settings: SpannerToolSettings | None = None
) -> BaseTool:
"""Get a tool from Spanner toolset."""
credentials_config = SpannerCredentialsConfig(
client_id="abc", client_secret="def"
)
toolset = SpannerToolset(
credentials_config=credentials_config,
tool_filter=[name],
spanner_tool_settings=tool_settings,
)
tools = await toolset.get_tools()
assert tools is not None
assert len(tools) == 1
return tools[0]
@pytest.mark.asyncio
@pytest.mark.parametrize(
"query_result_mode, expected_description",
[
(
QueryResultMode.DEFAULT,
textwrap.dedent(
"""\
Run a Spanner Read-Only query in the spanner database and return the result.
Args:
project_id (str): The GCP project id in which the spanner database
resides.
instance_id (str): The instance id of the spanner database.
database_id (str): The database id of the spanner database.
query (str): The Spanner SQL query to be executed.
credentials (Credentials): The credentials to use for the request.
settings (SpannerToolSettings): The settings for the tool.
tool_context (ToolContext): The context for the tool.
Returns:
dict: Dictionary with the result of the query.
If the result contains the key "result_is_likely_truncated" with
value True, it means that there may be additional rows matching the
query not returned in the result.
Examples:
<Example>
>>> execute_sql("my_project", "my_instance", "my_database",
... "SELECT COUNT(*) AS count FROM my_table")
{
"status": "SUCCESS",
"rows": [
[100]
]
}
</Example>
<Example>
>>> execute_sql("my_project", "my_instance", "my_database",
... "SELECT name, rating, description FROM hotels_table")
{
"status": "SUCCESS",
"rows": [
["The Hotel", 4.1, "Modern hotel."],
["Park Inn", 4.5, "Cozy hotel."],
...
]
}
</Example>
Note:
This is running with Read-Only Transaction for query that only read data."""
),
),
(
QueryResultMode.DICT_LIST,
textwrap.dedent(
"""\
Run a Spanner Read-Only query in the spanner database and return the result.
Args:
project_id (str): The GCP project id in which the spanner database
resides.
instance_id (str): The instance id of the spanner database.
database_id (str): The database id of the spanner database.
query (str): The Spanner SQL query to be executed.
credentials (Credentials): The credentials to use for the request.
settings (SpannerToolSettings): The settings for the tool.
tool_context (ToolContext): The context for the tool.
Returns:
dict: Dictionary with the result of the query.
If the result contains the key "result_is_likely_truncated" with
value True, it means that there may be additional rows matching the
query not returned in the result.
Examples:
<Example>
>>> execute_sql("my_project", "my_instance", "my_database",
... "SELECT COUNT(*) AS count FROM my_table")
{
"status": "SUCCESS",
"rows": [
{
"count": 100
}
]
}
</Example>
<Example>
>>> execute_sql("my_project", "my_instance", "my_database",
... "SELECT COUNT(*) FROM my_table")
{
"status": "SUCCESS",
"rows": [
{
"": 100
}
]
}
</Example>
<Example>
>>> execute_sql("my_project", "my_instance", "my_database",
... "SELECT name, rating, description FROM hotels_table")
{
"status": "SUCCESS",
"rows": [
{
"name": "The Hotel",
"rating": 4.1,
"description": "Modern hotel."
},
{
"name": "Park Inn",
"rating": 4.5,
"description": "Cozy hotel."
},
...
]
}
</Example>
Note:
This is running with Read-Only Transaction for query that only read data."""
),
),
],
)
async def test_execute_sql_query_result(
query_result_mode, expected_description
):
"""Test Spanner execute_sql tool query result in different modes."""
tool_name = "execute_sql"
tool_settings = SpannerToolSettings(query_result_mode=query_result_mode)
tool = await get_tool(tool_name, tool_settings)
assert tool.name == tool_name
assert tool.description == expected_description
@pytest.mark.asyncio
@mock.patch.object(query_tool.utils, "execute_sql", spec_set=True)
async def test_execute_sql(mock_utils_execute_sql):
"""Test execute_sql function in query result default mode."""
mock_credentials = mock.create_autospec(
Credentials, instance=True, spec_set=True
)
mock_tool_context = mock.create_autospec(
ToolContext, instance=True, spec_set=True
)
mock_utils_execute_sql.return_value = {"status": "SUCCESS", "rows": [[1]]}
result = await query_tool.execute_sql(
project_id="test-project",
instance_id="test-instance",
database_id="test-database",
query="SELECT 1",
credentials=mock_credentials,
settings=settings.SpannerToolSettings(),
tool_context=mock_tool_context,
)
mock_utils_execute_sql.assert_called_once_with(
"test-project",
"test-instance",
"test-database",
"SELECT 1",
mock_credentials,
settings.SpannerToolSettings(),
mock_tool_context,
)
assert result == {"status": "SUCCESS", "rows": [[1]]}