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SkillsMP has collected 237 skills from adnan-drina/rhoai3-coding-demo. Open a skill to review its source and details.
adnan-drina/rhoai3-coding-demoShowing 37 of 237 collected skills.
Use when documenting, reviewing, or operating Red Hat OpenShift AI Gen AI studio playground workflows: enabling the playground dashboard feature, preparing AI asset endpoints, configuring project playgrounds, testing models, comparing models side by side,…
Use when documenting, reviewing, deploying, or operating Red Hat OpenShift AI guardrails and AI safety workflows from the official guardrails guide: NeMo Guardrails, NemoGuardrails custom resources, TrustyAI-managed guardrails services, built-in Presidio and…
Use when documenting, reviewing, or diagnosing Red Hat OpenShift AI installation problems from the official troubleshooting chapter: Operator image pull failures, unsupported infrastructure, failed OpenShift AI or Notebooks custom resource creation,…
Author, refactor, and review Kubeflow Pipelines v2 pipelines for the rhoai3-demo stages once active KFP content exists; during the reimplementation, use this skill to rebuild KFP standards from legacy references. Use when editing stage-*/**/kfp/**/*.py, KFP…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI Kubeflow Spark Operator workflows from the official guide: KSO architecture, activating kubeflowsparkoperator in the DataScienceCluster, verifying the operator pod in redhat-ods-applications,…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI workload management with Kueue: Red Hat build of Kueue Operator integration, DataScienceCluster kueue managementState, migration from embedded Kueue, namespace queue enforcement with…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI Llama Stack platform capabilities: Technology Preview support posture, native Llama Stack APIs, OpenAI-compatible APIs, file citation annotations, provider enablement environment variables,…
Use when configuring, documenting, reviewing, or troubleshooting Red Hat OpenShift AI Operator logging and audit-record workflows: DSCI spec.devFlags.logmode, development versus production log output, viewing rhods-operator pod logs in redhat-ods-operator,…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI Models-as-a-Service governance from the official guide: MaaS enablement, Red Hat Connectivity Link and Kuadrant prerequisites, Gateway API and Authorino TLS prerequisites, PostgreSQL API key…
Use when documenting, reviewing, installing, configuring, or operating MLflow in Red Hat OpenShift AI from the official Working with MLflow guide: shared cluster MLflow instance, project-to-workspace mapping, Kubernetes RBAC authorization, DataScienceCluster…
Use when documenting, reviewing, or administering Red Hat OpenShift AI model catalog source governance: viewing catalog sources in Model catalog settings, adding Hugging Face repository or YAML-file sources, enabling or disabling sources, previewing include…
Use when documenting, reviewing, or operating data scientist and AI engineer workflows in the Red Hat OpenShift AI model catalog: discovering generative AI models, using catalog categories, searching and filtering by task, provider, license, language, and…
Use when documenting, reviewing, or operating Red Hat OpenShift AI model customization and training workflows from the official Customize Models for Gen AI and Agentic AI Applications guide: Red Hat Python index, disconnected package mirroring, JupyterLab…
Guide RHOAI evaluation workflows once active evaluation content exists; during the reimplementation, use this skill to rebuild EvalHub, RAG evaluation, KFP/MLflow evidence, RAGAS patterns, and standard model benchmarking workflows from legacy references. Use…
Use when documenting, reviewing, or operating Red Hat OpenShift AI deployed model management and monitoring: custom model-serving runtime administration, KServe progress-deadline timeouts, multi-node vLLM deployments, Kueue labels for InferenceService…
Use when documenting, reviewing, or provisioning Red Hat OpenShift AI model registries: enabling the modelregistry DataScienceCluster component, setting registriesNamespace, creating and editing model registries, choosing default non-production or external…
Use when documenting, reviewing, or configuring the Red Hat OpenShift AI model-serving platform from the official configuration guide: KServe-based model serving, NVIDIA NIM platform enablement, ServingRuntime and InferenceService concepts, supported and…
Use when documenting, reviewing, installing, configuring, or operating Red Hat OpenShift AI TrustyAI model monitoring from the official Monitoring your AI systems guide: TrustyAI component enablement, TrustyAIService custom resources, per-project TrustyAI…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI observability from the Administer documentation: Technology Preview support posture, DSCInitialization spec.monitoring enablement, redhat-ods-monitoring namespace behavior, Cluster…
Use when planning, documenting, or reviewing the Red Hat OpenShift AI platform baseline for the demo: supported OpenShift versions, AWS self-managed posture, subscriptions, cluster-admin access, worker resources, default storage class, identity provider,…
Use when documenting, reviewing, or rebuilding Red Hat OpenShift AI project-scoped resources: project-local workbench images, hardware profiles, and KServe model-serving runtime templates; dashboard visibility controlled by disableProjectScoped; resource…
Use when documenting, reviewing, or operating Red Hat OpenShift AI project workflows from the Working on projects guide: creating, updating, and deleting data science projects; creating, starting, updating, and deleting project workbenches; adding, updating,…
Use when documenting, reviewing, or deciding Red Hat OpenShift AI release and support posture: release notes, lifecycle phases, GA, EUS, Early Access, Technology Preview, Developer Preview, deprecated and removed functionality, known issues, support windows,…
Use when documenting, reviewing, or authoring Red Hat OpenShift AI workbench workflows for S3-compatible object storage: creating a Boto3 S3 client from project-scoped connection environment variables, listing buckets, creating buckets, listing objects,…
Use when installing, documenting, reviewing, or rebuilding Red Hat OpenShift AI Self-Managed on an existing OpenShift cluster for this demo. Covers AWS-hosted OpenShift assumptions, exact OpenShift version checks, subscription and cluster-admin prerequisites,…
Use when documenting, reviewing, or managing Red Hat OpenShift AI storage classes from the Managing resources documentation: persistent storage concepts, dashboard storage class enablement, display names, descriptions, access mode selection, OpenShift AI…
Use when documenting, reviewing, or configuring Red Hat OpenShift AI administrator telemetry settings: usage data collection notice, enabling or disabling Red Hat usage data collection from Cluster settings, dashboard `disableTracking`, MaaS telemetry in the…
Use when documenting, reviewing, planning, or executing Red Hat OpenShift AI Self-Managed uninstallation and decommissioning: Operator-managed resource removal, retained user resources, PVC backup requirements, the official CLI uninstall ConfigMap and…
Use when selecting, documenting, reviewing, or changing Red Hat OpenShift AI Operator update channels and update strategy for the demo. Covers fast, fast-x.y, stable, stable-x.y, eus-x.y, and alpha channel intent; choosing a feature-forward channel for latest…
Use when documenting, reviewing, or operating Red Hat OpenShift AI user and group access: OpenShift AI user versus administrator permissions, default access behavior, restricting access through OpenShift groups, adding users to RHOAI user/admin groups,…
Use when documenting, reviewing, or rebuilding custom workbench image compatibility with the Red Hat OpenShift AI Kubernetes Gateway API routing model: path-based routing, NB_PREFIX handling, full-prefix request paths, health check endpoint behavior, idle…
Use when documenting, reviewing, or performing the Red Hat OpenShift AI dashboard workflow for importing a custom workbench image: support boundary for custom image contents, Workbench images dashboard menu prerequisites, registry reachability, image tag or…
Use when creating, documenting, reviewing, or rebuilding Red Hat OpenShift AI workbenches and custom workbench images: deriving images from default RHOAI workbench images, building compatible bring-your-own workbench images, ImageStream resources for…
Create or update a compliant product skill from official Red Hat documentation for this demo's platform stack. Use when the user provides Red Hat OpenShift AI, OpenShift Container Platform, or OpenShift Data Foundation documentation sources and asks to create…
Create or update a compliant rhoai-* component skill from one official Red Hat OpenShift AI documentation chapter. Use when the user provides a docs.redhat.com RHOAI chapter URL, asks to turn an official RHOAI chapter into a reusable skill, wants source…
Maintain the operational documentation for the RHOAI coding demo. Use when creating or updating docs/OPERATIONS.md, docs/TROUBLESHOOTING.md, deployment instructions, validation guidance, ArgoCD operational notes, or known failure recovery procedures. Also use…
Create beautiful, shareable HTML-based slide presentations styled to Red Hat brand standards. Generates single-file, self-contained HTML decks with click/keyboard navigation, story-arc-driven narrative structure, and cinematic dark-mode aesthetics. Supports…