ADK fails to deploy with 1.18.0 and above

[Alameyo]

I can deploy agent to Vertex AI using adk in 1.17.0 with this command:

    --project=$PROJECT_ID \
    --region=$LOCATION \
    --staging_bucket=$STAGING_BUCKET \
    --display_name="$AGENT_NAME" \
    ArchitectureAgent

However if I update to 1.18.0 and above

pip install google-adk==1.18.0

deployment will fail with this message:

Deploy failed: Failed to create Agent Engine: {'code': 3, 'message': 'Reasoning Engine resource [projects/{redacted_project_ID}/locations/europe-west2/reasoningEngines/{redacted_agent_ID}] failed to start and cannot serve traffic. Please refer to our documentation (https://cloud.google.com/vertex-ai/generative-ai/docs/agent-engine/troubleshooting/deploy) for checking logs and other troubleshooting tips.'}

Still I have other issues with running agent even 1.17 that might or might not be related, but my guess is it shouldn't influence deployment.

[smwitkowski]

We hit the same Agent Engine deployment failure (Reasoning Engine failed to start) and traced it to invalid import/module paths caused by the temp folder name and template import path. We’ve opened a PR with fixes for temp folder sanitization and proper template imports when the agent lives under app/: #4243. Hope this helps—happy to share more repro details if useful.

[llalitkumarrr]

Hello @Alameyo ,
We tried to reproduce this issue. Although no specific error message appears, the deployment process seems to be stuck for a long time.

Thank you, @smwitkowski for the PR. @ryanaiagent could you please provide guidance on the next steps required to merge this?

In the meantime, you can try wrapping your agent in agent_engines.AdkApp() and deploying it using agent_engines.create().

Below is a sample code snippet for your reference to help you deploy your agent:

vertexai.init(
    project=PROJECT_ID,
    location=LOCATION,
    staging_bucket=STAGING_BUCKET,
)

# Initialize the agent
my_agent = Agent(
    model="gemini-2.5-flash",
    name="my_agent",
    description="Add two numbers and provide step-by-step reasoning for a child to understand.",
    instruction="You are a helpful assistant that can add two numbers and provide step-by-step reasoning for a child to understand it."
)

# Wrap the agent into AdkApp
app = agent_engines.AdkApp(
    agent=my_agent,
    enable_tracing=True,
)

# Deploy to Agent Engine
remote_app = agent_engines.create(
    agent_engine=app,
    requirements=[
        "google-cloud-aiplatform[adk,agent_engines]"   
    ]
)

print(f"Deployment finished!")
print(f"Resource Name: {remote_app.resource_name}")