[pull] main from google:main

contributing/samples/data_agent/README.md

@@ -0,0 +1,61 @@
+# 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.
+2.  Google Cloud authentication configured for Application Default Credentials:
+    ```bash
+    gcloud auth application-default login
+    ```
+3.  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.
+4.  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.
+    This tool maintains conversation state: if you ask multiple
+    questions to the same agent in one session, it will use the same
+    conversation, allowing for follow-ups. If you switch agents, a new
+    conversation will be started for the new agent.
+
+## How to Run
+
+1.  Navigate to the root of the ADK repository.
+2.  Run the agent using the ADK CLI:
+    ```bash
+    adk run --agent-path contributing/samples/data_agent
+    ```
+3.  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/data_agent/__init__.py

@@ -0,0 +1,15 @@
+# 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/data_agent/agent.py

@@ -0,0 +1,84 @@
+# 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 import Agent
+from google.adk.auth.auth_credential import AuthCredentialTypes
+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
+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
+
+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()
+  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",
+    ],
+)
+
+root_agent = Agent(
+    name="data_agent",
+    model="gemini-2.0-flash",
+    description="Agent to answer user questions using Data Agents.",
+    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"
+    ),
+    tools=[da_toolset],
+)

src/google/adk/features/_feature_registry.py

@@ -33,6 +33,8 @@ class FeatureName(str, Enum):
   BIGTABLE_TOOL_SETTINGS = "BIGTABLE_TOOL_SETTINGS"
   BIGTABLE_TOOLSET = "BIGTABLE_TOOLSET"
   COMPUTER_USE = "COMPUTER_USE"
+  DATA_AGENT_TOOL_CONFIG = "DATA_AGENT_TOOL_CONFIG"
+  DATA_AGENT_TOOLSET = "DATA_AGENT_TOOLSET"
   GOOGLE_CREDENTIALS_CONFIG = "GOOGLE_CREDENTIALS_CONFIG"
   GOOGLE_TOOL = "GOOGLE_TOOL"
   JSON_SCHEMA_FOR_FUNC_DECL = "JSON_SCHEMA_FOR_FUNC_DECL"
@@ -97,6 +99,12 @@ class FeatureConfig:
     FeatureName.COMPUTER_USE: FeatureConfig(
         FeatureStage.EXPERIMENTAL, default_on=True
     ),
+    FeatureName.DATA_AGENT_TOOL_CONFIG: FeatureConfig(
+        FeatureStage.EXPERIMENTAL, default_on=True
+    ),
+    FeatureName.DATA_AGENT_TOOLSET: FeatureConfig(
+        FeatureStage.EXPERIMENTAL, default_on=True
+    ),
     FeatureName.GOOGLE_CREDENTIALS_CONFIG: FeatureConfig(
         FeatureStage.EXPERIMENTAL, default_on=True
     ),

src/google/adk/tools/agent_tool.py

@@ -15,9 +15,11 @@
 from __future__ import annotations
 
 from typing import Any
+from typing import Optional
 from typing import TYPE_CHECKING
 
 from google.genai import types
+from pydantic import BaseModel
 from pydantic import model_validator
 from typing_extensions import override
 
@@ -37,6 +39,56 @@
   from ..agents.base_agent import BaseAgent
 
 
+def _get_input_schema(agent: BaseAgent) -> Optional[type[BaseModel]]:
+  """Extracts the input_schema from an agent.
+
+  For LlmAgent, returns its input_schema directly.
+  For agents with sub_agents, recursively searches the first sub-agent for an
+  input_schema.
+
+  Args:
+    agent: The agent to extract input_schema from.
+
+  Returns:
+    The input_schema if found, None otherwise.
+  """
+  from ..agents.llm_agent import LlmAgent
+
+  if isinstance(agent, LlmAgent):
+    return agent.input_schema
+
+  # For composite agents, check the first sub-agent
+  if agent.sub_agents:
+    return _get_input_schema(agent.sub_agents[0])
+
+  return None
+
+
+def _get_output_schema(agent: BaseAgent) -> Optional[type[BaseModel]]:
+  """Extracts the output_schema from an agent.
+
+  For LlmAgent, returns its output_schema directly.
+  For agents with sub_agents, recursively searches the last sub-agent for an
+  output_schema.
+
+  Args:
+    agent: The agent to extract output_schema from.
+
+  Returns:
+    The output_schema if found, None otherwise.
+  """
+  from ..agents.llm_agent import LlmAgent
+
+  if isinstance(agent, LlmAgent):
+    return agent.output_schema
+
+  # For composite agents, check the last sub-agent
+  if agent.sub_agents:
+    return _get_output_schema(agent.sub_agents[-1])
+
+  return None
+
+
 class AgentTool(BaseTool):
   """A tool that wraps an agent.
 
@@ -74,12 +126,14 @@ def populate_name(cls, data: Any) -> Any:
 
   @override
   def _get_declaration(self) -> types.FunctionDeclaration:
-    from ..agents.llm_agent import LlmAgent
     from ..utils.variant_utils import GoogleLLMVariant
 
-    if isinstance(self.agent, LlmAgent) and self.agent.input_schema:
+    input_schema = _get_input_schema(self.agent)
+    output_schema = _get_output_schema(self.agent)
+
+    if input_schema:
       result = _automatic_function_calling_util.build_function_declaration(
-          func=self.agent.input_schema, variant=self._api_variant
+          func=input_schema, variant=self._api_variant
       )
       # Override the description with the agent's description
       result.description = self.agent.description
@@ -114,7 +168,7 @@ def _get_declaration(self) -> types.FunctionDeclaration:
     # Set response schema for non-GEMINI_API variants
     if self._api_variant != GoogleLLMVariant.GEMINI_API:
       # Determine response type based on agent's output schema
-      if isinstance(self.agent, LlmAgent) and self.agent.output_schema:
+      if output_schema:
         # Agent has structured output schema - response is an object
         if is_feature_enabled(FeatureName.JSON_SCHEMA_FOR_FUNC_DECL):
           result.response_json_schema = {'type': 'object'}
@@ -137,15 +191,15 @@ async def run_async(
       args: dict[str, Any],
       tool_context: ToolContext,
   ) -> Any:
-    from ..agents.llm_agent import LlmAgent
     from ..runners import Runner
     from ..sessions.in_memory_session_service import InMemorySessionService
 
     if self.skip_summarization:
       tool_context.actions.skip_summarization = True
 
-    if isinstance(self.agent, LlmAgent) and self.agent.input_schema:
-      input_value = self.agent.input_schema.model_validate(args)
+    input_schema = _get_input_schema(self.agent)
+    if input_schema:
+      input_value = input_schema.model_validate(args)
       content = types.Content(
           role='user',
           parts=[
@@ -212,10 +266,11 @@ async def run_async(
     merged_text = '\n'.join(
         p.text for p in last_content.parts if p.text and not p.thought
     )
-    if isinstance(self.agent, LlmAgent) and self.agent.output_schema:
-      tool_result = self.agent.output_schema.model_validate_json(
-          merged_text
-      ).model_dump(exclude_none=True)
+    output_schema = _get_output_schema(self.agent)
+    if output_schema:
+      tool_result = output_schema.model_validate_json(merged_text).model_dump(
+          exclude_none=True
+      )
     else:
       tool_result = merged_text
     return tool_result

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

@@ -0,0 +1,25 @@
+# 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.
+
+"""Data Agent Tools."""
+
+from __future__ import annotations
+
+from .credentials import DataAgentCredentialsConfig
+from .data_agent_toolset import DataAgentToolset
+
+__all__ = [
+    "DataAgentCredentialsConfig",
+    "DataAgentToolset",
+]

src/google/adk/tools/data_agent/config.py

@@ -0,0 +1,35 @@
+# 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
+
+from pydantic import BaseModel
+from pydantic import ConfigDict
+
+from ...features import experimental
+from ...features import FeatureName
+
+
+@experimental(FeatureName.DATA_AGENT_TOOL_CONFIG)
+class DataAgentToolConfig(BaseModel):
+  """Configuration for Data Agent tools."""
+
+  # Forbid any fields not defined in the model
+  model_config = ConfigDict(extra='forbid')
+
+  max_query_result_rows: int = 50
+  """Maximum number of rows to return from a query.
+
+  By default, the query result will be limited to 50 rows.
+  """