Manage the deployed application

Basic Operations

You can list ReasoningEngine instances, get a ReasoningEngine instance, or delete a ReasoningEngine instance.

List ReasoningEngine instances

Vertex AI SDK for Python

The following command lists all ReasoningEngine instances for a given project and location:

reasoning_engines.ReasoningEngine.list()

The following code filters the list of ReasoningEngine instances by display_name:

reasoning_engines.ReasoningEngine.list(filter='display_name="DISPLAY_NAME"')

For example,

reasoning_engines.ReasoningEngine.list(filter='display_name="Demo Langchain Application"')

REST

Execute the following curl command to list all ReasoningEngine instances for a given project and location:

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines

Get a ReasoningEngine instance

Each ReasoningEngine instance has a unique RESOURCE_ID identifier. To learn more, see Deploy the application.

Vertex AI SDK for Python

The following code lets you get a specific ReasoningEngine resource:

remote_app = reasoning_engines.ReasoningEngine("RESOURCE_ID")

Alternately, you can provide the entire resource name:

remote_app = reasoning_engines.ReasoningEngine(
"projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID"
)

REST

Execute the following curl command to get a specific ReasoningEngine resource:

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID

Update a ReasoningEngine instance

Vertex AI SDK for Python

The following code lets you update a ReasoningEngine instance that was set to the remote_app variable:

remote_app.update(
    reasoning_engine=UPDATED_AGENT_INSTANCE,  # Optional.
    requirements=REQUIREMENTS,                # Optional.
    display_name="DISPLAY_NAME",              # Optional.
    description="DESCRIPTION",                # Optional.
    extra_packages=EXTRA_PACKAGES,            # Optional.
)

The arguments are the same as when you are deploying the application. You can find details in the API reference.

Note: You can update one or more fields of the ReasoningEngine instance at the same time, but you have to specify at least one of the fields to be updated. The amount of time it takes to update the instance will depend on the update being performed, but it should generally take between a few seconds to a few minutes.

REST

Execute the following curl command to update the display name and description of a ReasoningEngine resource:

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID?update_mask="display_name,description" \
-d '{ "displayName": "DISPLAY_NAME", "description": "DESCRIPTION" }'

Note: You can similarly make changes to the other fields and specify them under the update_mask when you do.

Delete a ReasoningEngine instance

Vertex AI SDK for Python

The following code lets you delete a ReasoningEngine instance that was set to the remote_app variable:

remote_app.delete()

REST

Each ReasoningEngine instance has a unique RESOURCE_ID identifier. To learn more, see Deploy the application.

Execute the following curl command to delete a specific ReasoningEngine instance:

curl \
-X DELETE \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID

Tracing for a LangchainAgent instance

To enable tracing for LangchainAgent applications, specify enable_tracing=True when you develop the application. For example:

agent = reasoning_engines.LangchainAgent(
    model=model,                # Required.
    tools=[get_exchange_rate],  # Optional.
    enable_tracing=True,        # [New] Optional.
)

agent.query(input="What is the exchange rate from US dollars to Swedish currency?")

This will export traces to Cloud Trace under the project in Set up your Google Cloud project.

Viewing Traces

You can find the traces in Trace Explorer.

Go to the Trace Explorer

The following Gantt chart shows the trace result of the example application from Develop an application:

 

The first row in the Gantt chart is for the trace, and there exists one row for each span in the trace, describing how long each sub-operation took.

To learn more, see the documentation for Trace Explorer.

Enable Tracing for a Custom Application

To enable tracing for custom applications, you can use Open Telemetry Google Cloud Integration in combination with an instrumentation framework such as OpenInference or OpenLLMetry.

Quotas and limits

Some attribute values might get truncated when they reach quota limits. For details, visit Cloud Trace Quota.

Cost

Cloud Trace has a free tier. Beyond the free tier, visit Cloud Trace Pricing.