> ## Documentation Index > Fetch the complete documentation index at: https://docs.tuneplane.ai/llms.txt > Use this file to discover all available pages before exploring further. # Glossary > The nouns the CLI, the console and the error messages use. These words appear in error messages. Reaching for a near synonym — run for job, image for recipe, gym for environment — usually lands you on the wrong page. ## Your project | Term | Meaning | | - | - | | **Project** | The `name` in `tuneplane.yaml`. The console groups every job from this directory under it. Names are unique per user, not globally. | | **Experiment** | A directory under `experiments//`, holding `config.yaml`, `recipe.lock.json`, and for a custom job `train.sh`. Creating one starts no GPUs. | | **Job** | One admitted submission. It has a run id, a state, and once launched a backend handle. One experiment produces many jobs. | | **Run id** | The identity everything else refers to: artifacts, `--init-from`, share links. | | **Pipeline** | One submission and every **Step** the platform runs for it. The unit the job list lists. | | **Step** | One job inside a Pipeline, with exactly one **Step Role**: `train`, `export`, `evaluate`, `benchmark`, `serve` or `process`. | | **Root Step** | The Step you submitted. The only one that can carry a **Derivation** or belong to a sweep. | | **Derivation** | That a run began from another run's artifact. Crosses projects and owners; Pipeline membership never does. | ## Methods and packaging | Term | Meaning | | - | - | | **Method id** | `/`, for example `nemo-rl/grpo` or `trl/kto`. | | **Recipe** | The versioned declaration of a method: entrypoint, tunable parameters with ranges, metrics, artifacts, and which framework versions it runs on. | | **Method Category** | What kind of training a recipe is, from a closed set: `supervised`, `sft`, `preference`, `reward-model`, `rl`, `distillation`, `evaluation`, `custom`. The axis is what the method needs in order to run. | | **Catalogue** | The recipes the connected server has published. Your lock file and the server must agree. | | **`recipe.lock.json`** | Written by `tp new`. Pins the recipe digest and the framework version. Submit refuses a stale lock — upgrade with `tp recipe upgrade`. | | **JobSpec** | The JSON `tp` builds and the server admits. You do not hand-write it. See [JobSpec](https://docs.tuneplane.ai/en/reference/jobspec.md). | | **Job Capsule** | `capsule.json`, `bootstrap.sh` and `runner.pex`, injected by the server under `.tuneplane/capsule/`. The training image does not have the platform package installed. | | **`runtime_id`** | Which deployment artifact runs the job — an OCI image, a SIF, a SQSH. Resolved from `--image`, the framework default, the runtime registry, then the catalogue. | ## Hardware and placement | Term | Meaning | | - | - | | **Series** | One class of accelerator, as the deployment defines it: per-card memory, compute weight, the scheduling pin, the Slurm constraint, and how many cards exist. Quota and capacity are per series. | | **Profile** | A named preset over a series: a default shape plus env and framework overrides for that shape. `h200`, `h200-2g`, `h100`. What `--profile` takes. | | **Resource Pool** | A group of same-series cards *within one job*, which the job's roles are assigned to. A shape in the JobSpec, never a set of machines. | | **Fleet** | A named execution target: registered Nodes or an existing Kubernetes or Slurm cluster. Jobs are placed onto a Fleet. Its kind is `node`, `kubernetes` or `slurm`. | | **Node** | One registered machine in a Fleet. Its id does not survive a reinstall: a rebuilt machine is a new Node. | | **Executor** | How the control plane starts a container on a Fleet. One per Fleet kind, with no fallback between them. | ## Data and material | Term | Meaning | | - | - | | **Dataset** | Versioned training material, referenced `/[@version]`. A version is immutable. | | **Volume** | A named directory a job reads through a read-only mount. It has **no versions**: files change in place, and a reference names the volume. Downloading its files is off until the owner turns it on. | | **Hub Reference** | `[:]/[@]`. Unprefixed means this platform; `hf:` and `ms:` mean Hugging Face and ModelScope. | | **Hub Import** | Copying a hub repository once into this platform's registry, so preview, scanning, redaction, classification and quota apply to it. | | **Data Classification** | The handling policy a derived dataset inherits from the material it was produced from. Computed by the platform, not declared by the job. | | **`$TUNEPLANE_OUT_DIR`** | The one directory whose contents survive the job. A checkpoint written anywhere else disappears with the scratch tree. | | **Ingest** | The HTTP path from the training container back to the console: logs, metrics, samples, artifacts. Its address arrives in the job as `TUNEPLANE_JOB_ENDPOINT`, and it must be reachable from the GPU node. | ## Evaluation | Term | Meaning | | - | - | | **Benchmark pack** | A declaration of an evaluation set: image, argv, and how to map its output onto score fields. Runs through `tp bench run`. | | **Rubric** | Your team's written standard for a correct answer: named criteria, weights, a scale. Owned and versioned, referenced `/`. | | **Environment** | A taskset plus a manifest, owned and versioned like a dataset. What an agent practises against. | | **Taskset** | The tasks in one environment version. Never handed out: a job references one, and no route returns a copy. | | **Verifier** | What decides whether a task was completed — a Rubric, a plugin entrypoint, or an HTTP endpoint. Always a reference; the platform never is one. | | **Harness** | The code that drives a model through an environment, supplied as a `capability: environment` plugin. | | **Sandbox** | Where model-generated code runs: a throwaway container with no GPU, no network and hard limits. A job that needs one on a deployment without one is refused. | ## Serving | Term | Meaning | | - | - | | **Playground Session** | A temporary serving instance for a human to try a checkpoint. Not a Deployment. | | **Model Deployment** | A managed model version for application traffic, behind a stable address, with a declared desired state. | | **Deployment Revision** | An immutable snapshot of a Deployment's model source and serving configuration. Promoted or rolled back whole. | | **Deployment Token** | A revocable credential for application traffic to one Deployment, independent of anyone's login. | | **Serving Engine** | The runtime that answers inference requests. vLLM and SGLang are different engines. | | **Reflow Buffer** | The retained request and response records of one Deployment, under a retention clock. Not a dataset: it expires, and nothing has vouched for it. | ## Next [Job states](https://docs.tuneplane.ai/en/concepts/job-lifecycle.md) · [Resources](https://docs.tuneplane.ai/en/concepts/resources.md) · [Architecture](https://docs.tuneplane.ai/en/concepts/architecture.md) This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.