feat: add BigQuery first-party tools.

These tools support getting BigQuery dataset/table metadata and query results.

PiperOrigin-RevId: 764139132

src/google/adk/tools/bigquery/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""BigQuery Tools. (Experimental)
+"""BigQuery Tools (Experimental).
 
 BigQuery Tools under this module are hand crafted and customized while the tools
 under google.adk.tools.google_api_tool are auto generated based on API
@@ -26,3 +26,13 @@ definition. The rationales to have customized tool are:
 4. We want to provide extra access guardrails in those tools. For example,
  execute_sql can't arbitrarily mutate existing data.
 """
+
+from .bigquery_credentials import BigQueryCredentialsConfig
+from .bigquery_tool import BigQueryTool
+from .bigquery_toolset import BigQueryToolset
+
+__all__ = [
+    "BigQueryTool",
+    "BigQueryToolset",
+    "BigQueryCredentialsConfig",
+]

src/google/adk/tools/bigquery/bigquery_credentials.py

@@ -14,6 +14,7 @@
 
 from __future__ import annotations
 
+import json
 from typing import List
 from typing import Optional
 
@@ -121,7 +122,7 @@ class BigQueryCredentialsManager:
     creds_json = tool_context.state.get(BIGQUERY_TOKEN_CACHE_KEY, None)
     creds = (
         Credentials.from_authorized_user_info(
-            creds_json, self.credentials_config.scopes
+            json.loads(creds_json), self.credentials_config.scopes
         )
         if creds_json
         else None

src/google/adk/tools/bigquery/bigquery_toolset.py

@@ -0,0 +1,86 @@
+# Copyright 2025 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
+
+from typing import List
+from typing import Optional
+from typing import Union
+
+from google.adk.agents.readonly_context import ReadonlyContext
+from typing_extensions import override
+
+from . import metadata_tool
+from . import query_tool
+from ...tools.base_tool import BaseTool
+from ...tools.base_toolset import BaseToolset
+from ...tools.base_toolset import ToolPredicate
+from .bigquery_credentials import BigQueryCredentialsConfig
+from .bigquery_tool import BigQueryTool
+
+
+class BigQueryToolset(BaseToolset):
+  """BigQuery Toolset contains tools for interacting with BigQuery data and metadata."""
+
+  def __init__(
+      self,
+      *,
+      tool_filter: Optional[Union[ToolPredicate, List[str]]] = None,
+      credentials_config: Optional[BigQueryCredentialsConfig] = None,
+  ):
+    self._credentials_config = credentials_config
+    self.tool_filter = tool_filter
+
+  def _is_tool_selected(
+      self, tool: BaseTool, readonly_context: ReadonlyContext
+  ) -> bool:
+    if self.tool_filter is None:
+      return True
+
+    if isinstance(self.tool_filter, ToolPredicate):
+      return self.tool_filter(tool, readonly_context)
+
+    if isinstance(self.tool_filter, list):
+      return tool.name in self.tool_filter
+
+    return False
+
+  @override
+  async def get_tools(
+      self, readonly_context: Optional[ReadonlyContext] = None
+  ) -> List[BaseTool]:
+    """Get tools from the toolset."""
+    all_tools = [
+        BigQueryTool(
+            func=func,
+            credentials=self._credentials_config,
+        )
+        for func in [
+            metadata_tool.get_dataset_info,
+            metadata_tool.get_table_info,
+            metadata_tool.list_dataset_ids,
+            metadata_tool.list_table_ids,
+            query_tool.execute_sql,
+        ]
+    ]
+
+    return [
+        tool
+        for tool in all_tools
+        if self._is_tool_selected(tool, readonly_context)
+    ]
+
+  @override
+  async def close(self):
+    pass

src/google/adk/tools/bigquery/client.py

@@ -0,0 +1,33 @@
+# Copyright 2025 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 google.api_core.client_info
+from google.cloud import bigquery
+from google.oauth2.credentials import Credentials
+
+USER_AGENT = "adk-bigquery-tool"
+
+
+def get_bigquery_client(*, credentials: Credentials) -> bigquery.Client:
+  """Get a BigQuery client."""
+
+  client_info = google.api_core.client_info.ClientInfo(user_agent=USER_AGENT)
+
+  bigquery_client = bigquery.Client(
+      credentials=credentials, client_info=client_info
+  )
+
+  return bigquery_client

src/google/adk/tools/bigquery/metadata_tool.py

@@ -0,0 +1,249 @@
+# Copyright 2025 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 google.cloud import bigquery
+from google.oauth2.credentials import Credentials
+
+from ...tools.bigquery import client
+
+
+def list_dataset_ids(project_id: str, credentials: Credentials) -> list[str]:
+  """List BigQuery dataset ids in a Google Cloud project.
+
+  Args:
+      project_id (str): The Google Cloud project id.
+      credentials (Credentials): The credentials to use for the request.
+
+  Returns:
+      list[str]: List of the BigQuery dataset ids present in the project.
+
+  Examples:
+      >>> list_dataset_ids("bigquery-public-data")
+      ['america_health_rankings',
+       'american_community_survey',
+       'aml_ai_input_dataset',
+       'austin_311',
+       'austin_bikeshare',
+       'austin_crime',
+       'austin_incidents',
+       'austin_waste',
+       'baseball',
+       'bbc_news']
+  """
+  try:
+    bq_client = client.get_bigquery_client(credentials=credentials)
+
+    datasets = []
+    for dataset in bq_client.list_datasets(project_id):
+      datasets.append(dataset.dataset_id)
+    return datasets
+  except Exception as ex:
+    return {
+        "status": "ERROR",
+        "error_details": str(ex),
+    }
+
+
+def get_dataset_info(
+    project_id: str, dataset_id: str, credentials: Credentials
+) -> dict:
+  """Get metadata information about a BigQuery dataset.
+
+  Args:
+      project_id (str): The Google Cloud project id containing the dataset.
+      dataset_id (str): The BigQuery dataset id.
+      credentials (Credentials): The credentials to use for the request.
+
+  Returns:
+      dict: Dictionary representing the properties of the dataset.
+
+  Examples:
+      >>> get_dataset_info("bigquery-public-data", "penguins")
+      {
+        "kind": "bigquery#dataset",
+        "etag": "PNC5907iQbzeVcAru/2L3A==",
+        "id": "bigquery-public-data:ml_datasets",
+        "selfLink":
+          "https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets/ml_datasets",
+        "datasetReference": {
+            "datasetId": "ml_datasets",
+            "projectId": "bigquery-public-data"
+        },
+        "access": [
+            {
+                "role": "OWNER",
+                "groupByEmail": "cloud-datasets-eng@google.com"
+            },
+            {
+                "role": "READER",
+                "iamMember": "allUsers"
+            },
+            {
+                "role": "READER",
+                "groupByEmail": "bqml-eng@google.com"
+            }
+        ],
+        "creationTime": "1553208775542",
+        "lastModifiedTime": "1686338918114",
+        "location": "US",
+        "type": "DEFAULT",
+        "maxTimeTravelHours": "168"
+      }
+  """
+  try:
+    bq_client = client.get_bigquery_client(credentials=credentials)
+    dataset = bq_client.get_dataset(
+        bigquery.DatasetReference(project_id, dataset_id)
+    )
+    return dataset.to_api_repr()
+  except Exception as ex:
+    return {
+        "status": "ERROR",
+        "error_details": str(ex),
+    }
+
+
+def list_table_ids(
+    project_id: str, dataset_id: str, credentials: Credentials
+) -> list[str]:
+  """List table ids in a BigQuery dataset.
+
+  Args:
+      project_id (str): The Google Cloud project id containing the dataset.
+      dataset_id (str): The BigQuery dataset id.
+      credentials (Credentials): The credentials to use for the request.
+
+  Returns:
+      list[str]: List of the tables ids present in the dataset.
+
+  Examples:
+      >>> list_table_ids("bigquery-public-data", "ml_datasets")
+      ['census_adult_income',
+       'credit_card_default',
+       'holidays_and_events_for_forecasting',
+       'iris',
+       'penguins',
+       'ulb_fraud_detection']
+  """
+  try:
+    bq_client = client.get_bigquery_client(credentials=credentials)
+
+    tables = []
+    for table in bq_client.list_tables(
+        bigquery.DatasetReference(project_id, dataset_id)
+    ):
+      tables.append(table.table_id)
+    return tables
+  except Exception as ex:
+    return {
+        "status": "ERROR",
+        "error_details": str(ex),
+    }
+
+
+def get_table_info(
+    project_id: str, dataset_id: str, table_id: str, credentials: Credentials
+) -> dict:
+  """Get metadata information about a BigQuery table.
+
+  Args:
+      project_id (str): The Google Cloud project id containing the dataset.
+      dataset_id (str): The BigQuery dataset id containing the table.
+      table_id (str): The BigQuery table id.
+      credentials (Credentials): The credentials to use for the request.
+
+  Returns:
+      dict: Dictionary representing the properties of the table.
+
+  Examples:
+      >>> get_table_info("bigquery-public-data", "ml_datasets", "penguins")
+      {
+        "kind": "bigquery#table",
+        "etag": "X0ZkRohSGoYvWemRYEgOHA==",
+        "id": "bigquery-public-data:ml_datasets.penguins",
+        "selfLink":
+        "https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets/ml_datasets/tables/penguins",
+        "tableReference": {
+            "projectId": "bigquery-public-data",
+            "datasetId": "ml_datasets",
+            "tableId": "penguins"
+        },
+        "schema": {
+            "fields": [
+                {
+                    "name": "species",
+                    "type": "STRING",
+                    "mode": "REQUIRED"
+                },
+                {
+                    "name": "island",
+                    "type": "STRING",
+                    "mode": "NULLABLE"
+                },
+                {
+                    "name": "culmen_length_mm",
+                    "type": "FLOAT",
+                    "mode": "NULLABLE"
+                },
+                {
+                    "name": "culmen_depth_mm",
+                    "type": "FLOAT",
+                    "mode": "NULLABLE"
+                },
+                {
+                    "name": "flipper_length_mm",
+                    "type": "FLOAT",
+                    "mode": "NULLABLE"
+                },
+                {
+                    "name": "body_mass_g",
+                    "type": "FLOAT",
+                    "mode": "NULLABLE"
+                },
+                {
+                    "name": "sex",
+                    "type": "STRING",
+                    "mode": "NULLABLE"
+                }
+            ]
+        },
+        "numBytes": "28947",
+        "numLongTermBytes": "28947",
+        "numRows": "344",
+        "creationTime": "1619804743188",
+        "lastModifiedTime": "1634584675234",
+        "type": "TABLE",
+        "location": "US",
+        "numTimeTravelPhysicalBytes": "0",
+        "numTotalLogicalBytes": "28947",
+        "numActiveLogicalBytes": "0",
+        "numLongTermLogicalBytes": "28947",
+        "numTotalPhysicalBytes": "5350",
+        "numActivePhysicalBytes": "0",
+        "numLongTermPhysicalBytes": "5350",
+        "numCurrentPhysicalBytes": "5350"
+      }
+  """
+  try:
+    bq_client = client.get_bigquery_client(credentials=credentials)
+    return bq_client.get_table(
+        bigquery.TableReference(
+            bigquery.DatasetReference(project_id, dataset_id), table_id
+        )
+    ).to_api_repr()
+  except Exception as ex:
+    return {
+        "status": "ERROR",
+        "error_details": str(ex),
+    }

src/google/adk/tools/bigquery/query_tool.py

@@ -0,0 +1,76 @@
+# Copyright 2025 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 google.oauth2.credentials import Credentials
+
+from ...tools.bigquery import client
+
+MAX_DOWNLOADED_QUERY_RESULT_ROWS = 50
+
+
+def execute_sql(project_id: str, query: str, credentials: Credentials) -> dict:
+  """Run a BigQuery SQL query in the project and return the result.
+
+  Args:
+      project_id (str): The GCP project id in which the query should be
+        executed.
+      query (str): The BigQuery SQL query to be executed.
+      credentials (Credentials): The credentials to use for the request.
+
+  Returns:
+      dict: Dictionary representing 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:
+      >>> execute_sql("bigframes-dev",
+      ... "SELECT island, COUNT(*) AS population "
+      ... "FROM bigquery-public-data.ml_datasets.penguins GROUP BY island")
+      {
+        "rows": [
+            {
+                "island": "Dream",
+                "population": 124
+            },
+            {
+                "island": "Biscoe",
+                "population": 168
+            },
+            {
+                "island": "Torgersen",
+                "population": 52
+            }
+        ]
+      }
+  """
+
+  try:
+    bq_client = client.get_bigquery_client(credentials=credentials)
+    row_iterator = bq_client.query_and_wait(
+        query, project=project_id, max_results=MAX_DOWNLOADED_QUERY_RESULT_ROWS
+    )
+    rows = [{key: val for key, val in row.items()} for row in row_iterator]
+    result = {"rows": rows}
+    if (
+        MAX_DOWNLOADED_QUERY_RESULT_ROWS is not None
+        and len(rows) == MAX_DOWNLOADED_QUERY_RESULT_ROWS
+    ):
+      result["result_is_likely_truncated"] = True
+    return result
+  except Exception as ex:
+    return {
+        "status": "ERROR",
+        "error_details": str(ex),
+    }