feat(samples): add ManagedAgent create-and-use custom-agent sample
Add a self-contained ManagedAgent sample that provisions a custom managed-agent resource (custom persona + server-side google_search) via `--create` / `--delete` CLI flags, reusing the genai client on `ManagedAgent.api_client`, then drives it with `adk web` / `adk run`. Co-authored-by: Haran Rajkumar <haranrk@google.com> PiperOrigin-RevId: 954729930
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# Managed Agent: Create and Use a Custom Agent
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> For setup, authentication, backends, and background on `ManagedAgent`, see the
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> [ManagedAgent guide](../../../../docs/guides/agents/managed_agent/index.md).
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## Overview
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This sample demonstrates the **control-plane lifecycle** of a custom managed
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agent: creating a persistent, named agent *resource* — its persona and
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server-side tools baked in — then driving it and deleting it.
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You do **not** need a custom resource just to set a persona or server-side
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tools. `ManagedAgent` accepts both inline: `instruction=...` for a persona (see
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the [`system_instruction`](../system_instruction) sample) and
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`tools=[google_search]` for server-side tools (see the [`basic`](../basic)
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sample). Create a custom resource when you instead want a reusable,
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server-managed agent that other apps and sessions can share by id.
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This module drives that lifecycle: run it with `--create` to provision the
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resource (reusing the genai client `ManagedAgent` already holds,
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`root_agent.api_client`, which exposes both interactions and agent
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create/delete), then drive `root_agent` with `adk web` / `adk run`, and
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`--delete` to remove it.
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## Setup
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Custom-agent creation requires the **GEAP / Vertex** backend (`global`
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location); the Gemini API backend cannot create agent resources. For backend
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selection, authentication, and credentials, see the
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[ManagedAgent guide](../../../../docs/guides/agents/managed_agent/index.md#prerequisites).
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## Usage
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```bash
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# 1. Create the custom agent (once).
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python contributing/samples/managed_agent/custom_agent/agent.py --create
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# 2. Chat with it. Provisioning can take a few minutes (longer for the first
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# agent in a project), so wait a moment after --create before the first turn.
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adk run contributing/samples/managed_agent/custom_agent
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# or: adk web
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# 3. Delete it when done.
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python contributing/samples/managed_agent/custom_agent/agent.py --delete
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```
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Creation is asynchronous: `--create` returns before the agent is fully ready, so
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if the first turn fails with a "not found" / "being created" error, wait a few
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seconds and retry.
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## Sample Inputs
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Answers are grounded in live search, so exact text varies:
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- `What are the most significant AI announcements this week?`
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The created agent's persona makes it answer **concisely** and **cite its
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sources**, using server-side `google_search`.
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- `Summarize that in one sentence.`
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A follow-up turn that reuses the recovered interaction (multi-turn chaining).
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## Graph
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```mermaid
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graph LR
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User -->|message| CustomManagedAgent
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CustomManagedAgent -->|interactions.create| ManagedAgentsAPI
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ManagedAgentsAPI -->|server-side google_search| ManagedAgentsAPI
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ManagedAgentsAPI -->|streamed events| CustomManagedAgent
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CustomManagedAgent -->|answer| User
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```
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## How To
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- **Define the custom agent**: pass a `system_instruction` (persona) and
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server-side `tools` (here `{'type': 'google_search'}`) to
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`client.agents.create(...)`, extending the `antigravity-preview-05-2026` base
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agent.
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- **Reuse the ManagedAgent client**: `root_agent.api_client` is the genai client
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`ManagedAgent` already holds; its `agents.create` / `agents.delete` cover the
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control plane.
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- **Provision a sandbox**: `ManagedAgent(environment={'type': 'remote'})` gives
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each interaction a remote sandbox (required to run the agent).
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- **Run it**: `--create` provisions, `--delete` removes; in between, `root_agent`
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is a normal `BaseAgent`, so `adk web` / `adk run` (or a `Runner`) drive it.
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@@ -0,0 +1,15 @@
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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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from . import agent
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@@ -0,0 +1,90 @@
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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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"""Create, use, and delete a custom managed-agent resource.
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This sample demonstrates the control-plane lifecycle of a custom managed agent:
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creating a persistent, named agent *resource* (its persona and server-side tools
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baked in), then driving it and deleting it.
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You don't need a custom resource just to set a persona or server-side tools --
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``ManagedAgent`` accepts both inline (``instruction=...`` and
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``tools=[google_search]``; see the ``system_instruction`` and ``basic``
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samples). Create a custom resource when you instead want a reusable,
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server-managed agent that other apps and sessions can share by id.
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Run this module with ``--create`` once to provision the resource, then drive
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``root_agent`` with ``adk web`` / ``adk run
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contributing/samples/managed_agent/custom_agent``, then ``--delete`` to remove
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it. See the README for the required GEAP/Vertex setup.
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python contributing/samples/managed_agent/custom_agent/agent.py --create
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python contributing/samples/managed_agent/custom_agent/agent.py --delete
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"""
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import argparse
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from dotenv import load_dotenv
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from google.adk.agents import ManagedAgent
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load_dotenv()
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_AGENT_ID = 'adk-custom-search-agent'
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_SYSTEM_INSTRUCTION = (
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'You are a concise research assistant. Use Google Search to ground every '
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'answer in current sources, cite the sources you used, and keep answers to '
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'a few sentences.'
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)
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root_agent = ManagedAgent(
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name='custom_managed_agent',
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agent_id=_AGENT_ID,
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environment={'type': 'remote'},
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)
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def main() -> None:
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"""Create or delete the custom managed-agent resource."""
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parser = argparse.ArgumentParser(
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description='Create or delete the custom managed agent for this sample.'
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)
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parser.add_argument(
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'--create', action='store_true', help='Create the custom managed agent.'
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)
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parser.add_argument(
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'--delete', action='store_true', help='Delete the custom managed agent.'
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)
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args = parser.parse_args()
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if not (args.create or args.delete):
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parser.print_help()
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return
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# ManagedAgent's genai client also exposes agent create/delete.
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client = root_agent.api_client
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if args.create:
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client.agents.create(
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id=_AGENT_ID,
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base_agent='antigravity-preview-05-2026',
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system_instruction=_SYSTEM_INSTRUCTION,
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tools=[{'type': 'google_search'}],
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)
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print(f'Created "{_AGENT_ID}".')
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if args.delete:
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client.agents.delete(id=_AGENT_ID)
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print(f'Deleted "{_AGENT_ID}".')
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if __name__ == '__main__':
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main()
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