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tfy-deploy-skills
tfy-deploy-skills contient 22 skills collectées depuis truefoundry, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Manages TrueFoundry roles, teams, and collaborators. Create custom roles, organize users into teams, and grant access to resources. Use when managing permissions, creating teams, or adding collaborators.
Manages TrueFoundry personal access tokens (PATs). List, create, and delete tokens for API auth and CI/CD.
Lists, inspects, and manages TrueFoundry application deployments. Shows status, health, and details for services, jobs, and Helm releases. Also handles requests to delete, remove, or destroy applications by directing users to the TrueFoundry UI.
Deploys applications to TrueFoundry. Handles single HTTP services, async/queue workers, multi-service projects, and declarative manifest apply. Supports `tfy apply`, `tfy deploy`, docker-compose translation, and CI/CD pipelines. Use when deploying apps, applying manifests, shipping services, or orchestrating multi-service deployments.
Fetches TrueFoundry documentation, API reference, and deployment guides. Use when the user needs platform docs or how-to guidance.
Sets up GitOps CI/CD pipelines for TrueFoundry using tfy apply. Supports GitHub Actions, GitLab CI, and Bitbucket Pipelines.
Deploys infrastructure components via Helm charts on TrueFoundry. Supports any public or private OCI Helm chart including databases (Postgres, MongoDB, Redis), message brokers (Kafka, RabbitMQ), and vector databases (Qdrant, Milvus). Uses YAML manifests with `tfy apply`. Use when installing Helm charts or deploying infrastructure on TrueFoundry.
Deploys and monitors TrueFoundry batch jobs, scheduled cron jobs, and one-time tasks. Uses YAML manifests with `tfy apply`. Use when deploying jobs, scheduling cron tasks, checking job run status, or viewing execution history. For listing job applications, use `applications` skill.
Deploys ML and LLM models on TrueFoundry with GPU inference servers (vLLM, TGI, NVIDIA NIM). Uses YAML manifests with `tfy apply`. Use when serving language models, deploying Hugging Face models, or hosting GPU-accelerated inference endpoints.
Views, downloads, and searches application and job logs from TrueFoundry. Supports time-range filtering, pod filtering, and error search.
Browses TrueFoundry ML repositories and model registry. Lists repos, models, and artifacts with FQNs for use in other skills.
Monitors TrueFoundry deployment rollouts after deploy/apply. Polls status, checks pod health and readiness, fetches logs on failure, and reports a final summary. Use after deploying or applying a manifest to track rollout progress.
Deploys Jupyter notebooks on TrueFoundry infrastructure with optional GPU support. Use when launching JupyterLab environments, setting up ML development workspaces, or running cloud-hosted notebooks for data exploration.
Guides new users through TrueFoundry setup — account registration, email verification, credential configuration, and first deployment. Use when the user says "get started", "set up truefoundry", "new account", "register", "onboard", "I'm new", or has no credentials configured.
Manages TrueFoundry secret groups and secrets. Handles listing, creating, updating, and deleting secret groups and individual key-value secrets.
Validates deployed TrueFoundry services with health checks, endpoint smoke tests, and optional load soak tests. Covers REST APIs and web apps.
Deploys remote development environments with SSH access on TrueFoundry. Use when setting up VS Code Remote workspaces, cloud development machines, GPU dev boxes, or remote coding environments with SSH access.
Checks TrueFoundry connection status and verifies credentials (TFY_BASE_URL/TFY_HOST, TFY_API_KEY). Used as a preflight check before any TrueFoundry operation.
Adds OpenTelemetry-based tracing to applications via TrueFoundry's tracing platform (Traceloop SDK). Creates tracing projects, instruments Python/TypeScript code, and captures LLM calls and custom spans.
Creates and manages persistent volumes on TrueFoundry. Handles creation, listing, mounting, storage class selection, and static volume attachment.
Builds and deploys data processing and ML training pipelines using TrueFoundry Workflows (built on Flyte). Use when creating DAGs, orchestrating multi-step tasks, scheduling ETL pipelines, or running ML training workflows.
Lists TrueFoundry workspaces and clusters. Provides workspace FQNs for deployment, cluster connectivity status, available GPU types, and base domains.