chore: import upstream snapshot with attribution

contributing/samples/integrations/data_agent/README.md

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+# Data Agent Sample
+
+This sample agent demonstrates ADK's first-party tools for interacting with
+Data Agents powered by [Conversational Analytics API](https://docs.cloud.google.com/gemini/docs/conversational-analytics-api/overview).
+These tools are distributed via
+the `google.adk.tools.data_agent` module and allow you to list,
+inspect, and
+chat with Data Agents using natural language.
+
+These tools leverage stateful conversations, meaning you can ask follow-up
+questions in the same session, and the agent will maintain context.
+
+## Prerequisites
+
+1. An active Google Cloud project with BigQuery and Gemini APIs enabled.
+1. Google Cloud authentication configured for Application Default Credentials:
+   ```bash
+   gcloud auth application-default login
+   ```
+1. At least one Data Agent created. You could create data agents via
+   [Conversational API](https://docs.cloud.google.com/gemini/docs/conversational-analytics-api/overview),
+   its
+   [Python SDK](https://docs.cloud.google.com/gemini/docs/conversational-analytics-api/build-agent-sdk),
+   or for BigQuery data
+   [BigQuery Studio](https://docs.cloud.google.com/bigquery/docs/create-data-agents#create_a_data_agent).
+   These agents are created and configured in the Google Cloud console and
+   point to your BigQuery tables or other data sources.
+1. Follow the official
+   [Setup and prerequisites](https://docs.cloud.google.com/gemini/docs/conversational-analytics-api/overview#setup)
+   guide to enable the API and configure IAM permissions and authentication for
+   your data sources.
+
+## Tools Used
+
+- `list_accessible_data_agents`: Lists Data Agents you have permission to
+  access in the configured GCP project.
+- `get_data_agent_info`: Retrieves details about a specific Data Agent given
+  its full resource name.
+- `ask_data_agent`: Chats with a specific Data Agent using natural language.
+
+## How to Run
+
+1. Navigate to the root of the ADK repository.
+1. Run the agent using the ADK CLI:
+   ```bash
+   adk run --agent-path contributing/samples/data_agent
+   ```
+1. The CLI will prompt you for input. You can ask questions like the examples
+   below.
+
+## Sample prompts
+
+- "List accessible data agents."
+- "Using agent
+  `projects/my-project/locations/global/dataAgents/sales-agent-123`, who were
+  my top 3 customers last quarter?"
+- "How does that compare to the quarter before?"

contributing/samples/integrations/data_agent/__init__.py

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+# 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 . import agent

contributing/samples/integrations/data_agent/agent.py

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+# 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 asyncio
+import os
+from typing import Any
+
+from google.adk.agents import Agent
+from google.adk.auth.auth_credential import AuthCredentialTypes
+from google.adk.tools import load_artifacts
+from google.adk.tools.data_agent.config import DataAgentToolConfig
+from google.adk.tools.data_agent.credentials import DataAgentCredentialsConfig
+from google.adk.tools.data_agent.data_agent_toolset import DataAgentToolset
+from google.adk.tools.tool_context import ToolContext
+import google.auth
+import google.auth.transport.requests
+from google.genai import types
+
+# 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
+
+if CREDENTIALS_TYPE == AuthCredentialTypes.OAUTH2:
+  # Initiaze the tools to do interactive OAuth
+  # The environment variables OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET
+  # must be set
+  credentials_config = DataAgentCredentialsConfig(
+      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",
+      scopes=["https://www.googleapis.com/auth/cloud-platform"],
+  )
+  creds.refresh(google.auth.transport.requests.Request())
+  credentials_config = DataAgentCredentialsConfig(credentials=creds)
+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 = DataAgentCredentialsConfig(
+      credentials=application_default_credentials
+  )
+
+tool_config = DataAgentToolConfig(
+    max_query_result_rows=100,
+)
+da_toolset = DataAgentToolset(
+    credentials_config=credentials_config,
+    data_agent_tool_config=tool_config,
+    tool_filter=[
+        "list_accessible_data_agents",
+        "get_data_agent_info",
+        "ask_data_agent",
+    ],
+)
+
+
+# NOTE: The generate_chart tool requires 'altair' and 'vl-convert-python' to be
+# installed in your environment. You can install them using:
+# pip install altair vl-convert-python
+async def generate_chart(
+    chart_spec: dict[str, Any], tool_context: ToolContext
+) -> dict[str, str]:
+  """Generates a professional chart using Altair based on a Vega-Lite spec.
+
+  Args:
+    chart_spec: A dictionary defining a Vega-Lite chart.
+    tool_context: The tool context.
+
+  Returns:
+    A dictionary containing the status of the chart generation ("success" or
+    "error"), a detail message, and the filename if successful.
+  """
+  import altair as alt
+  import vl_convert as vlc
+
+  try:
+    # Altair can take a Vega-Lite dict directly and render it.
+    # We use vl-convert to transform the spec into a high-quality PNG.
+    png_data = await asyncio.to_thread(vlc.vegalite_to_png, chart_spec, scale=2)
+
+    # Save as artifact
+    await tool_context.save_artifact(
+        "chart.png",
+        types.Part.from_bytes(data=png_data, mime_type="image/png"),
+    )
+    title = chart_spec.get("title", "Chart")
+    return {
+        "status": "success",
+        "detail": (
+            f"Professional chart '{title}' rendered using Altair/Vega-Lite."
+        ),
+        "filename": "chart.png",
+    }
+  except Exception as e:  # pylint: disable=broad-exception-caught
+    return {"status": "error", "detail": f"Failed to render chart: {str(e)}"}
+
+
+root_agent = Agent(
+    name="data_agent",
+    description=(
+        "Agent to answer user questions using Data Agents and generate charts."
+    ),
+    instruction=(
+        "## Persona\nYou are a helpful assistant that uses Data Agents"
+        " to answer user questions about their data.\n\n## Tools\n- You can"
+        " list available data agents using `list_accessible_data_agents`.\n-"
+        " You can get information about a specific data agent using"
+        " `get_data_agent_info`.\n- You can chat with a specific data"
+        " agent using `ask_data_agent`.\n- `generate_chart` renders"
+        " professional charts from a `chart_spec` (Vega-Lite JSON). Use this"
+        " whenever you need to visualize data; do not show raw JSON to the"
+        " user.\n- You can load artifacts using `load_artifacts`.\n"
+    ),
+    tools=[da_toolset, generate_chart, load_artifacts],
+)