Viewing Details About an AI Application

Viewing the AI Application List

You can view all created AI applications on the AI application list page. The AI application list page displays the following information.

**Table 1** AI application list
Parameter	Description
AI Application Name	Name of an AI application.
Latest Version	Latest version of an AI application.
Status	Status of an AI application.
Deployment Type	Types of the services that an AI application can be deployed as.
Versions	Number of AI application versions.
Request Mode	Request mode of real-time services. Synchronous request: one-off inference with results returned synchronously (within 60s). This mode is suitable for images and small video files. Asynchronous request: one-off inference with results returned asynchronously (longer than 60s). This mode is suitable for real-time video inference and large videos.
Created	Time when an AI application is created.
Description	Description of an AI application.
Operation	Deploy: Deploy an AI application as real-time services, batch services, or edge services. Create Version: Create an AI application version. The settings of the last version are used by default, except for the version. You can change the parameter settings. Delete: Delete the AI application. NOTE: If an AI application version has been deployed as a service, you must delete the associated service before deleting the AI application version. A deleted AI application cannot be recovered.

Click the number in Versions to view the version list.

Figure 1 Version list

The version list displays the following information.

**Table 2** Version list
Parameter	Description
Version	Current version of an AI application.
Status	Status of an AI application.
Deployment Type	Types of the services that an AI application can be deployed as.
Model Size	Size of an AI application.
Model Source	Model source of an AI application.
Created	Time when an AI application is created.
Description	Description of an AI application.
Operation	Deploy: Deploy an AI application as real-time services, batch services, or edge services. Delete: Delete a version of an AI application.

Viewing Details About an AI Application

After an AI application is created, you can view its information on the details page.

Log in to the ModelArts console, and choose AI Applications from the navigation pane. The My AI Applications tab is displayed by default.

Click the name of the target AI application. The application details page is displayed.

On the application details page, you can view the basic information and model precision of the AI application, and switch tab pages to view more information.

**Table 3** Basic information about an AI application
Parameter	Description
Name	Name of an AI application.
Status	Status of an AI application
Version	Current version of an AI application.
ID	ID of an AI application.
Description	Click the edit button to add the description of an AI application.
Deployment Type	Types of the services that an AI application can be deployed as.
Meta Model Source	Source of the meta model, which can be training jobs, OBS, or container images.
Training Name	Associated training job if the meta model comes from a training job. Click the training job name to go to its details page.
Training Version	Training job version if the meta model comes from an old-version training job.
Storage path of the meta model	Path to the meta model if the meta model comes from OBS.
Container Image Storage Path	Path to the container image if the meta model comes from a container image.
AI Engine	AI engine if the meta model comes from a training job or OBS.
Engine Package Address	Engine package address if the meta model comes from OBS and AI Engine is Custom.
Runtime Environment	Runtime environment on which the meta model depends if the meta model comes from a training job or OBS and a preset AI engine is used.
Container API	Protocol and port number for starting the AI application if the meta model comes from OBS (AI Engine is Custom) or a container image.
Inference Code	Path to the inference code if the meta model comes from an olde-version training job.
Image Replication	Image replication status for meta models from a container image.
Dynamic loading	Dynamic loading status if the meta model comes from a training job or OBS.
Size	Size of an AI application.
Health Check	Displays health check status if the meta model comes from OBS or a container image. When health check is enabled, the probe parameter settings are displayed. Startup Probe: This probe checks if the application instance has started. If a startup probe is provided, all other probes are disabled until it succeeds. If the startup probe fails, the instance is restarted. If no startup probe is provided, the default status is Success. Readiness Probe: This probe verifies whether the application instance is ready to handle traffic. If the readiness probe fails (meaning the instance is not ready), the instance is taken out of the service load balancing pool. Traffic will not be routed to the instance until the probe succeeds. Liveness Probe: This probe monitors the application health status. If the liveness probe fails (indicating the application is unhealthy), the instance is automatically restarted. The probe parameters include Check Mode, Health Check URL (displayed when Check Mode is set to HTTP request), Health Check Command (displayed when Check Mode is set to Command), Health Check Period, Delay, Timeout, and Maximum Failures.
AI Application Description	Description document added during the creation of an AI application.
Instruction Set Architecture	System architecture.
Inference Accelerator	Type of inference accelerator cards.

**Table 4** Tabs
Parameter	Description
Model Precision	Model recall, precision, accuracy, and F1 score of an AI application.
Parameter Configuration	API configuration, input parameters, and output parameters of an AI application.
Runtime Dependency	Model dependency on the environment. If creating a job failed, edit the runtime dependency. After the modification is saved, the system will automatically use the original image to create the job again.
Events	The progress of key operations during AI application creation. Events are stored for three months and will be automatically cleared then. For details about how to view events of an AI application, see Viewing Events of an AI Application.
Constraint	Displays the constraints of service deployment, such as the request mode, boot command, and model encryption, based on the settings during AI application creation. For AI applications in asynchronous request mode, parameters including the input mode, output mode, service startup parameters, and job configuration parameters can be displayed.
Associated Services	The list of services that an AI application was deployed. Click a service name to go to the service details page.