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https://github.com/googleapis/genai-toolbox.git
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docs(adk): align quickstart script with other orchestrations (#2423)
This brings the ADK Python quickstart sample up to par with the other orchestrations in the guidance, removing the need for special test handling.
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@@ -115,7 +115,7 @@ pip install google-genai
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1. Update `my_agent/agent.py` with the following content to connect to Toolbox:
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```py
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{{< include "quickstart/python/adk/quickstart.py" >}}
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{{< regionInclude "quickstart/python/adk/quickstart.py" "quickstart" >}}
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```
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<br/>
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@@ -1,6 +1,21 @@
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# [START quickstart]
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import asyncio
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from google.adk import Agent
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from google.adk.apps import App
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from google.adk.runners import InMemoryRunner
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from google.adk.tools.toolbox_toolset import ToolboxToolset
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from google.genai.types import Content, Part
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prompt = """
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You're a helpful hotel assistant. You handle hotel searching, booking and
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cancellations. When the user searches for a hotel, mention it's name, id,
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location and price tier. Always mention hotel ids while performing any
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searches. This is very important for any operations. For any bookings or
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cancellations, please provide the appropriate confirmation. Be sure to
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update checkin or checkout dates if mentioned by the user.
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Don't ask for confirmations from the user.
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"""
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# TODO(developer): update the TOOLBOX_URL to your toolbox endpoint
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toolset = ToolboxToolset(
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@@ -8,10 +23,35 @@ toolset = ToolboxToolset(
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)
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root_agent = Agent(
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name='root_agent',
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name='hotel_assistant',
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model='gemini-2.5-flash',
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instruction="You are a helpful AI assistant designed to provide accurate and useful information.",
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instruction=prompt,
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tools=[toolset],
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)
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app = App(root_agent=root_agent, name="my_agent")
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# [END quickstart]
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queries = [
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"Find hotels in Basel with Basel in its name.",
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"Can you book the Hilton Basel for me?",
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"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.",
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"My check in dates would be from April 10, 2024 to April 19, 2024.",
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]
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async def main():
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runner = InMemoryRunner(app=app)
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session = await runner.session_service.create_session(
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app_name=app.name, user_id="test_user"
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)
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for query in queries:
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print(f"\nUser: {query}")
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user_message = Content(parts=[Part.from_text(text=query)])
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async for event in runner.run_async(user_id="test_user", session_id=session.id, new_message=user_message):
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if event.is_final_response() and event.content and event.content.parts:
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print(f"Agent: {event.content.parts[0].text}")
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -41,31 +41,29 @@ def golden_keywords():
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class TestExecution:
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"""Test framework execution and output validation."""
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_cached_output = None
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@pytest.fixture(scope="function")
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def script_output(self, capsys):
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"""Run the quickstart function and return its output."""
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# TODO: Add better validation for ADK once we have a way to capture its
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# output.
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if ORCH_NAME == "adk":
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return quickstart.app.root_agent.name
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else:
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if TestExecution._cached_output is None:
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asyncio.run(quickstart.main())
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return capsys.readouterr()
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out, err = capsys.readouterr()
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TestExecution._cached_output = (out, err)
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class Output:
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def __init__(self, out, err):
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self.out = out
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self.err = err
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return Output(*TestExecution._cached_output)
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def test_script_runs_without_errors(self, script_output):
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"""Test that the script runs and produces no stderr."""
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if ORCH_NAME == "adk":
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return
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assert script_output.err == "", f"Script produced stderr: {script_output.err}"
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def test_keywords_in_output(self, script_output, golden_keywords):
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"""Test that expected keywords are present in the script's output."""
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if ORCH_NAME == "adk":
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assert script_output == "root_agent"
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return
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output = script_output.out
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missing_keywords = [kw for kw in golden_keywords if kw not in output]
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assert not missing_keywords, f"Missing keywords in output: {missing_keywords}"
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@@ -83,15 +83,12 @@ Toolbox instead of the local address.
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2. Open your agent file (`my_agent/agent.py`).
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3. Update the `ToolboxSyncClient` initialization to use your Cloud Run URL.
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3. Update the `ToolboxToolset` initialization to point to your Cloud Run service URL. Replace the existing initialization code with the following:
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{{% alert color="info" %}}
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Since Cloud Run services are secured by default, you also need to provide an
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authentication token.
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{{% alert color="info" title="Note" %}}
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Since Cloud Run services are secured by default, you also need to provide a workload identity.
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{{% /alert %}}
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Replace your existing client initialization code with the following:
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```python
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from google.adk import Agent
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from google.adk.apps import App
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@@ -132,14 +129,14 @@ app = App(root_agent=root_agent, name="my_agent")
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Run the deployment command:
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```bash
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make backend
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make deploy
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```
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This command will build your agent's container image and deploy it to Vertex AI.
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## Step 6: Test your Deployment
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Once the deployment command (`make backend`) completes, it will output the URL
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Once the deployment command (`make deploy`) completes, it will output the URL
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for the Agent Engine Playground. You can click on this URL to open the
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Playground in your browser and start chatting with your agent to test the tools.
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