alicloud-ai-pai-aiworkspaceManage Alibaba Cloud Platform for Artificial Intelligence PAI - AIWorkspace (AIWorkSpace) via OpenAPI/SDK. Use for listing resources, creating or updating configurations, querying status, and troubleshooting workflows for this product.
Install via ClawdBot CLI:
clawdbot install cinience/alicloud-ai-pai-aiworkspaceCategory: service
Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for Platform for Artificial Intelligence PAI - AIWorkspace.
1) Confirm region, resource identifiers, and desired action.
2) Discover API list and required parameters (see references).
3) Call API with SDK or OpenAPI Explorer.
4) Verify results with describe/list APIs.
1) Environment variables: ALICLOUD_ACCESS_KEY_ID / ALICLOUD_ACCESS_KEY_SECRET / ALICLOUD_REGION_ID
Region policy: ALICLOUD_REGION_ID is an optional default. If unset, decide the most reasonable region for the task; if unclear, ask the user.
2) Shared config file: ~/.alibabacloud/credentials
AIWorkSpace2021-02-041) Inventory/list: prefer List / Describe APIs to get current resources.
2) Change/configure: prefer Create / Update / Modify / Set APIs for mutations.
3) Status/troubleshoot: prefer Get / Query / Describe*Status APIs for diagnosis.
Use metadata-first discovery before calling business APIs:
python scripts/list_openapi_meta_apis.py
Optional overrides:
python scripts/list_openapi_meta_apis.py --product-code <ProductCode> --version <Version>
The script writes API inventory artifacts under the skill output directory.
If you need to save responses or generated artifacts, write them under:
output/alicloud-ai-pai-aiworkspace/
references/sources.mdGenerated Mar 1, 2026
AI research teams use this skill to list and manage AIWorkspace resources across regions, ensuring efficient allocation of computational environments for experiments. It helps track workspace configurations and troubleshoot deployment issues during model training phases.
IT administrators leverage this skill to automate the creation and updating of AIWorkspace configurations for enterprise AI platforms, supporting scalable machine learning workflows. It enables monitoring resource status and optimizing costs through inventory checks.
Cloud support teams utilize this skill to diagnose and resolve customer issues with AIWorkspace by querying status APIs and verifying resource states. It aids in providing quick troubleshooting for workflow failures or configuration errors.
DevOps engineers integrate this skill into CI/CD pipelines to dynamically manage AIWorkspace resources, automating environment setups for testing and deployment of AI models. It ensures consistent configurations and reduces manual intervention.
Companies offer AI development platforms as a service, using this skill to manage backend AIWorkspace resources for customers. It enables scalable, pay-as-you-go access to AI tools and environments, generating subscription-based revenue.
Consulting firms provide managed services for AI infrastructure, leveraging this skill to oversee client AIWorkspace deployments and optimizations. Revenue comes from service contracts and performance-based improvements in resource efficiency.
Educational institutions or tech trainers use this skill in courses to teach AI cloud management, offering hands-on labs with AIWorkspace. Revenue is generated through course fees and certification programs for professionals.
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