> ## Documentation Index > Fetch the complete documentation index at: https://docs.kiteml.com/llms.txt > Use this file to discover all available pages before exploring further. # Get Training Run > Status, live progress, metrics, and output for one run. ## OpenAPI ````yaml /api-reference/openapi.json get /v1/training_runs/{run_id} openapi: 3.1.0 info: title: Kite Platform API description: >- Public API for Kite. Authenticate with `Authorization: Bearer kite_...`, and send `Kite-Version: 2026-09-27` to pin the dated contract your code was written against (without it you get 2026-09-27). Every response carries the version that served it. version: '2026-09-27' servers: - url: https://api.kiteml.com description: Kite Platform API security: - bearerAuth: [] tags: - name: Augmentations description: Generate new episodes from a LeRobot dataset. - name: Training runs description: Fine-tune a policy on a dataset, one run per policy. - name: Twins description: Rebuild a robot episode as an interactable MuJoCo scene (private beta). - name: Catalog description: Policies, hardware tiers, and dataset inspection. - name: Operations description: Poll any run by its id. - name: Webhooks description: Endpoints that receive events, and the event log. - name: API keys description: The key making the request. - name: Usage description: Token usage and credit balance. paths: /v1/training_runs/{run_id}: get: tags: - Training runs summary: Get Training Run description: Status, live progress, metrics, and output for one run. operationId: get_training_run_v1_training_runs__run_id__get parameters: - name: run_id in: path required: true schema: type: string title: Run Id - $ref: '#/components/parameters/KiteVersion' responses: '200': description: The run, read live content: application/json: schema: $ref: '#/components/schemas/TrainingRun' '400': description: >- Invalid request (`parameter_invalid`, `unsupported_version`, ...); `param` names the field content: application/json: schema: $ref: '#/components/schemas/ApiErrorResponse' '401': description: Missing or invalid API key (`unauthenticated`) content: application/json: schema: $ref: '#/components/schemas/ApiErrorResponse' '403': description: >- The key lacks a scope this route needs (`missing_scope`), or the feature is not enabled for the account content: application/json: schema: $ref: '#/components/schemas/ApiErrorResponse' '404': content: application/json: schema: $ref: '#/components/schemas/ApiErrorResponse' description: >- No such resource (`resource_not_found`); another account's ids answer the same '429': description: >- Rate or concurrency limited (`rate_limit_exceeded`, `concurrency_limit_exceeded`, `capacity_exceeded`); honor `Retry-After` content: application/json: schema: $ref: '#/components/schemas/ApiErrorResponse' components: parameters: KiteVersion: name: Kite-Version in: header required: false description: >- The dated contract your code was written against. Without it you get 2026-09-27; every response says which version served it. schema: type: string enum: - '2026-09-27' default: '2026-09-27' schemas: TrainingRun: properties: id: type: string title: Id description: '`trn_` + a time-ordered ULID' object: type: string enum: - training_run const: training_run title: Object status: type: string title: Status description: '`processing`, `succeeded`, `failed`, `canceled`; an open set' phase: anyOf: - type: string - type: 'null' title: Phase description: >- Finer than `status`, e.g. `provisioning`, `preparing`, `downloading_dataset`, `training`, `completed`, `failed`, `cancelled`. Only GET /v1/training_runs/{id} reads it: null in list, create and cancel responses status_message: anyOf: - type: string - type: 'null' title: Status Message description: '`phase` in words, e.g. `Provisioning GPU…`' progress: type: number maximum: 1 minimum: 0 title: Progress error: anyOf: - $ref: '#/components/schemas/TrainingRunError' - type: 'null' description: Why, when `failed` policy: type: string title: Policy description: The LeRobot policy type (see GET /v1/training_policies) robot: anyOf: - type: string - type: 'null' title: Robot description: The robot tag from create (a label only) hardware_tier: type: string title: Hardware Tier description: See GET /v1/hardware_tiers group_id: type: string title: Group Id description: Shared by the runs one create started, one per policy dataset: $ref: '#/components/schemas/TrainingRunDataset' config: $ref: '#/components/schemas/TrainingRunResolvedConfig' cameras: $ref: '#/components/schemas/TrainingRunResolvedCameras' metrics: $ref: '#/components/schemas/TrainingRunMetrics' description: >- Live from the trainer on GET /v1/training_runs/{id}; elsewhere, the last values stored eval: anyOf: - $ref: '#/components/schemas/TrainingRunEval' - type: 'null' description: >- Once the trainer has reported on evaluation (a finished run has); null in list, create and cancel responses output: $ref: '#/components/schemas/TrainingRunOutputSummary' description: What the run has produced tokens: $ref: '#/components/schemas/TrainingRunTokens' webhook_metadata: anyOf: - type: object - type: 'null' title: Webhook Metadata description: Echoed from create created_at: type: string title: Created At started_at: anyOf: - type: string - type: 'null' title: Started At description: When the GPU job was submitted completed_at: anyOf: - type: string - type: 'null' title: Completed At description: When it became `succeeded`, `failed` or `canceled` type: object required: - id - object - status - phase - status_message - progress - error - policy - robot - hardware_tier - group_id - dataset - config - cameras - metrics - eval - output - tokens - webhook_metadata - created_at - started_at - completed_at title: TrainingRun description: One policy trained on one GPU. examples: - cameras: {} completed_at: '2026-09-27T15:41:52.664301Z' config: batch_size: 8 eval_enabled: false save_freq: 1000 steps: 30000 created_at: '2026-09-27T14:02:11.482913Z' dataset: uri: lerobot/svla_so101_pickplace eval: {} group_id: 5f0c2e9a7b1d4c3e8f6a2b9d0c1e7f35 hardware_tier: gcp_gpu_t4 id: trn_01K65Z3N8Q4W2H7R9T6Y1B3C5D metrics: loss: 0.043 max_steps: 30000 step: 30000 object: training_run output: checkpoint_count: 30 hf_push_status: ok hf_repo_id: your-hf-user/act-pickplace hf_url: https://huggingface.co/your-hf-user/act-pickplace latest_checkpoint: artifact_uri: >- gs://example-bucket/jobs/7c1e9f0a2b3d4e5f8a9b0c1d2e3f4a5b/artifacts/lerobot/checkpoints/030000/pretrained_model/ created_at: '2026-09-27T15:38:40.120394Z' download_url: >- /v1/training_runs/trn_01K65Z3N8Q4W2H7R9T6Y1B3C5D/checkpoints/30000/download object: training_checkpoint step: 30000 phase: completed policy: act progress: 1 robot: so101_follower started_at: '2026-09-27T14:02:13.107554Z' status: succeeded status_message: Completed tokens: charged: 500 refunded: 0 webhook_metadata: ref: nightly-42 ApiErrorResponse: properties: error: $ref: '#/components/schemas/ApiErrorBody' type: object required: - error title: ApiErrorResponse description: Every /v1 error has this shape. TrainingRunError: properties: code: type: string title: Code description: >- `training_failed`, `submission_failed`, `vertex_state_unobserved`, `service_unavailable`, `gpu_capacity_unavailable`. `submission_failed`: the GPU job never started, so nothing was charged message: type: string title: Message description: What went wrong, in at most 1,000 characters type: object required: - code - message title: TrainingRunError TrainingRunDataset: properties: uri: type: string maxLength: 500 minLength: 3 title: Uri description: >- LeRobot dataset: a HuggingFace repo id ('lerobot/pusht') or a gs:// path type: object required: - uri title: TrainingRunDataset TrainingRunResolvedConfig: properties: steps: type: integer title: Steps description: '`config.steps` from create, else the policy''s default' batch_size: type: integer title: Batch Size description: '`config.batch_size` from create, else the policy''s default' save_freq: type: integer title: Save Freq description: A checkpoint is saved every this many steps eval_enabled: type: boolean title: Eval Enabled type: object required: - steps - batch_size - save_freq - eval_enabled title: TrainingRunResolvedConfig TrainingRunResolvedCameras: properties: rename: anyOf: - additionalProperties: type: string type: object - type: 'null' title: Rename description: >- Dataset camera key → policy image slot, from create; null when Kite maps them type: object required: - rename title: TrainingRunResolvedCameras TrainingRunMetrics: properties: step: anyOf: - type: integer - type: 'null' title: Step description: The last step the trainer reported max_steps: anyOf: - type: integer - type: 'null' title: Max Steps loss: anyOf: - type: number - type: 'null' title: Loss description: The training loss at `step` type: object required: - step - max_steps - loss title: TrainingRunMetrics TrainingRunEval: properties: status: anyOf: - type: string - type: 'null' title: Status description: >- `enabled`, `ok` or `skipped: `; null when `config.eval_enabled` is false metrics: anyOf: - additionalProperties: type: number type: object - type: 'null' title: Metrics description: Rollout results, e.g. `pc_success`, `avg_sum_reward` type: object required: - status - metrics title: TrainingRunEval TrainingRunOutputSummary: properties: checkpoint_count: type: integer title: Checkpoint Count description: >- Checkpoints saved so far. Only GET /v1/training_runs/{id} reads storage: it is 0 in list, create and cancel responses latest_checkpoint: anyOf: - $ref: '#/components/schemas/TrainingCheckpoint' - type: 'null' description: The newest; all of them are GET /v1/training_runs/{id}/checkpoints hf_repo_id: anyOf: - type: string - type: 'null' title: Hf Repo Id description: >- Only when the run pushes to the Hub (`output.push_to_hub` at create): the repo it pushes to hf_url: anyOf: - type: string - type: 'null' title: Hf Url description: 'Only when pushing: the repo''s page' hf_push_status: anyOf: - type: string - type: 'null' title: Hf Push Status description: >- Only when pushing: null until the push starts, then `pushing (attempt n/5)`, `ok`, `skipped: ` or `failed: `, e.g. `skipped: no Hugging Face account connected` type: object required: - checkpoint_count - latest_checkpoint title: TrainingRunOutputSummary TrainingRunTokens: properties: charged: type: integer title: Charged description: >- Reserved at launch: one GPU-hour at the tier's rate (0 on a CPU tier, or when the GPU job never started) refunded: type: integer title: Refunded description: >- Given back when the run finished. 0 today: a run is charged its GPU-hour however long it trains type: object required: - charged - refunded title: TrainingRunTokens ApiErrorBody: properties: type: type: string title: Type description: >- invalid_request_error, authentication_error, permission_error, not_found_error, conflict_error, rate_limit_error, or api_error code: type: string title: Code description: 'Machine-readable: branch on this, not on the message' message: type: string title: Message param: anyOf: - type: string - type: 'null' title: Param description: The request field the error is about, when there is one request_id: anyOf: - type: string - type: 'null' title: Request Id description: Also in the X-Request-Id header; quote it to support details: anyOf: - type: object - type: 'null' title: Details description: >- Extra data for some codes (e.g. the cameras a dataset does have, for camera_not_found) type: object required: - type - code - message title: ApiErrorBody TrainingCheckpoint: properties: object: type: string enum: - training_checkpoint const: training_checkpoint title: Object step: type: integer title: Step artifact_uri: anyOf: - type: string - type: 'null' title: Artifact Uri description: >- Where it is stored (`gs://…/pretrained_model/`), for reading the bucket directly download_url: type: string title: Download Url description: >- This API's path to it as a ZIP of `pretrained_model/` (send your Authorization header) created_at: anyOf: - type: string - type: 'null' title: Created At description: When it was saved; null for older runs type: object required: - object - step - artifact_uri - download_url - created_at title: TrainingCheckpoint description: A checkpoint a training run saved. examples: - artifact_uri: >- gs://example-bucket/jobs/7c1e9f0a2b3d4e5f8a9b0c1d2e3f4a5b/artifacts/lerobot/checkpoints/030000/pretrained_model/ created_at: '2026-09-27T15:38:40.120394Z' download_url: >- /v1/training_runs/trn_01K65Z3N8Q4W2H7R9T6Y1B3C5D/checkpoints/30000/download object: training_checkpoint step: 30000 securitySchemes: bearerAuth: type: http scheme: bearer description: >- A Kite API key (`kite_...`), from **Platform API → Keys** in the dashboard. ````