chore: import upstream snapshot with attribution
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from google.adk.agents.llm_agent import LlmAgent
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from google.adk.auth.auth_credential import AuthCredentialTypes
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from google.adk.tools.bigquery.bigquery_credentials import BigQueryCredentialsConfig
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from google.adk.tools.bigquery.bigquery_toolset import BigQueryToolset
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from google.adk.tools.bigquery.config import BigQueryToolConfig
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from google.adk.tools.bigquery.config import WriteMode
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import google.auth
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import google.auth.transport.requests
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# Define the desired credential type.
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# By default use Application Default Credentials (ADC) from the local
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# environment, which can be set up by following
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# https://cloud.google.com/docs/authentication/provide-credentials-adc.
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CREDENTIALS_TYPE = None
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# Define an appropriate application name
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BIGQUERY_AGENT_NAME = "adk_sample_bigquery_agent"
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# Define BigQuery tool config with write mode set to allowed. Note that this is
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# only to demonstrate the full capability of the BigQuery tools. In production
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# you may want to change to BLOCKED (default write mode, effectively makes the
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# tool read-only) or PROTECTED (only allows writes in the anonymous dataset of a
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# BigQuery session) write mode.
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tool_config = BigQueryToolConfig(
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write_mode=WriteMode.ALLOWED,
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application_name=BIGQUERY_AGENT_NAME,
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max_query_result_rows=50,
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)
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if CREDENTIALS_TYPE == AuthCredentialTypes.OAUTH2:
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# Initialize the tools to do interactive OAuth
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# The environment variables OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET
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# must be set
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credentials_config = BigQueryCredentialsConfig(
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client_id=os.getenv("OAUTH_CLIENT_ID"),
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client_secret=os.getenv("OAUTH_CLIENT_SECRET"),
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)
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elif CREDENTIALS_TYPE == AuthCredentialTypes.SERVICE_ACCOUNT:
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# Initialize the tools to use the credentials in the service account key.
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# If this flow is enabled, make sure to replace the file path with your own
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# service account key file
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# https://cloud.google.com/iam/docs/service-account-creds#user-managed-keys
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creds, _ = google.auth.load_credentials_from_file("service_account_key.json")
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if not creds.valid:
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creds.refresh(google.auth.transport.requests.Request())
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credentials_config = BigQueryCredentialsConfig(credentials=creds)
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elif CREDENTIALS_TYPE == AuthCredentialTypes.HTTP:
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# Initialize the tools to use the externally provided access token. One such
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# use case is creating an authorization resource `AUTH_ID` in Gemini
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# Enterprise and using it to register an ADK agent deployed to Vertex AI
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# Agent Engine with Gemini Enterprise. See for more details:
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# https://docs.cloud.google.com/gemini/enterprise/docs/register-and-manage-an-adk-agent.
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# This access token will be passed to the agent via the tool context, with
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# the key `AUTH_ID`.
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credentials_config = BigQueryCredentialsConfig(
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external_access_token_key="AUTH_ID"
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)
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else:
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# Initialize the tools to use the application default credentials.
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# https://cloud.google.com/docs/authentication/provide-credentials-adc
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application_default_credentials, _ = google.auth.default()
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if not application_default_credentials.valid:
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application_default_credentials.refresh(
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google.auth.transport.requests.Request()
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)
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credentials_config = BigQueryCredentialsConfig(
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credentials=application_default_credentials
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)
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bigquery_toolset = BigQueryToolset(
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credentials_config=credentials_config, bigquery_tool_config=tool_config
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)
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# The variable name `root_agent` determines what your root agent is for the
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# debug CLI
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root_agent = LlmAgent(
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name=BIGQUERY_AGENT_NAME,
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description=(
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"Agent to answer questions about BigQuery data and models and execute"
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" SQL queries."
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),
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instruction="""\
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You are a data science agent with access to several BigQuery tools.
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Make use of those tools to answer the user's questions.
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""",
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tools=[bigquery_toolset],
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)
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