# 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.

import os

from google.adk.agents.llm_agent import LlmAgent
from google.adk.auth.auth_credential import AuthCredentialTypes
from google.adk.tools.bigquery.bigquery_credentials import BigQueryCredentialsConfig
from google.adk.tools.bigquery.bigquery_toolset import BigQueryToolset
from google.adk.tools.bigquery.config import BigQueryToolConfig
from google.adk.tools.bigquery.config import WriteMode
import google.auth
import google.auth.transport.requests

# Define the desired credential type.
# By default use Application Default Credentials (ADC) from the local
# environment, which can be set up by following
# https://cloud.google.com/docs/authentication/provide-credentials-adc.
CREDENTIALS_TYPE = None

# Define an appropriate application name
BIGQUERY_AGENT_NAME = "adk_sample_bigquery_agent"


# Define BigQuery tool config with write mode set to allowed. Note that this is
# only to demonstrate the full capability of the BigQuery tools. In production
# you may want to change to BLOCKED (default write mode, effectively makes the
# tool read-only) or PROTECTED (only allows writes in the anonymous dataset of a
# BigQuery session) write mode.
tool_config = BigQueryToolConfig(
    write_mode=WriteMode.ALLOWED,
    application_name=BIGQUERY_AGENT_NAME,
    max_query_result_rows=50,
)

if CREDENTIALS_TYPE == AuthCredentialTypes.OAUTH2:
  # Initialize the tools to do interactive OAuth
  # The environment variables OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET
  # must be set
  credentials_config = BigQueryCredentialsConfig(
      client_id=os.getenv("OAUTH_CLIENT_ID"),
      client_secret=os.getenv("OAUTH_CLIENT_SECRET"),
  )
elif CREDENTIALS_TYPE == AuthCredentialTypes.SERVICE_ACCOUNT:
  # Initialize the tools to use the credentials in the service account key.
  # If this flow is enabled, make sure to replace the file path with your own
  # service account key file
  # https://cloud.google.com/iam/docs/service-account-creds#user-managed-keys
  creds, _ = google.auth.load_credentials_from_file("service_account_key.json")
  if not creds.valid:
    creds.refresh(google.auth.transport.requests.Request())
  credentials_config = BigQueryCredentialsConfig(credentials=creds)
elif CREDENTIALS_TYPE == AuthCredentialTypes.HTTP:
  # Initialize the tools to use the externally provided access token. One such
  # use case is creating an authorization resource `AUTH_ID` in Gemini
  # Enterprise and using it to register an ADK agent deployed to Vertex AI
  # Agent Engine with Gemini Enterprise. See for more details:
  # https://docs.cloud.google.com/gemini/enterprise/docs/register-and-manage-an-adk-agent.
  # This access token will be passed to the agent via the tool context, with
  # the key `AUTH_ID`.
  credentials_config = BigQueryCredentialsConfig(
      external_access_token_key="AUTH_ID"
  )
else:
  # Initialize the tools to use the application default credentials.
  # https://cloud.google.com/docs/authentication/provide-credentials-adc
  application_default_credentials, _ = google.auth.default()
  if not application_default_credentials.valid:
    application_default_credentials.refresh(
        google.auth.transport.requests.Request()
    )
  credentials_config = BigQueryCredentialsConfig(
      credentials=application_default_credentials
  )

bigquery_toolset = BigQueryToolset(
    credentials_config=credentials_config, bigquery_tool_config=tool_config
)

# The variable name `root_agent` determines what your root agent is for the
# debug CLI
root_agent = LlmAgent(
    name=BIGQUERY_AGENT_NAME,
    description=(
        "Agent to answer questions about BigQuery data and models and execute"
        " SQL queries."
    ),
    instruction="""\
        You are a data science agent with access to several BigQuery tools.
        Make use of those tools to answer the user's questions.
    """,
    tools=[bigquery_toolset],
)
