Get Job - Archetype AI Documentation

curl https://api.u1.archetypeai.app/v0.5/batch/jobs/job_2abc3def4ghi5jkl6mno7pqr \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")
job_id = "job_2abc3def4ghi5jkl6mno7pqr"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.5/batch/jobs/{job_id}",
    headers={"Authorization": f"Bearer {api_key}"}
)

job = response.json()
print(f"Job: {job['name']} — Status: {job['status']}")

const jobId = 'job_2abc3def4ghi5jkl6mno7pqr';

const response = await fetch(`https://api.u1.archetypeai.app/v0.5/batch/jobs/${jobId}`, {
  headers: {
    'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
  }
});

const job = await response.json();
console.log(`Job: ${job.name} — Status: ${job.status}`);

{
  "id": "job_2abc3def4ghi5jkl6mno7pqr",
  "org_id": "org_1abc2def3ghi4jkl",
  "name": "tep-classification",
  "pipeline_type": "batch",
  "pipeline_key": "machine-state-classification",
  "pipeline_version": "1.1.1",
  "status": "COMPLETED",
  "outcome" "SUCCESS",
  "parameters": {
    "worker": {
      "parallelism": 1,
      "config": {
        "model_type": "omega_1_4_base",
        "batch_size": 32,
        "reader_config": {
          "data_columns": ["xmeas_1", "xmeas_2", "xmv_11"],
          "timestamp_column": "timestamp",
          "window_size": 64,
          "step_size": 1
        },
        "classifier_config": {
          "n_neighbors": 5,
          "metric": "euclidean",
          "weights": "uniform",
          "normalize_embeddings": false
        }
      }
    }
  },
  "retry_count": 0,
  "preemption_count": 0,
  "queue_position": null,
  "queue_depth": null,
  "input_progress": {
    "pending": 0,
    "processing": 0,
    "completed": 1,
    "failed": 0,
    "processed_bytes": 511733,
    "total_bytes": 105332974
  },
  "created_at": "2026-04-14T10:00:00Z",
  "updated_at": "2026-04-14T10:15:00Z",
  "started_at": "2026-04-14T10:02:00Z",
  "completed_at": "2026-04-14T10:15:00Z",
  "failed_at": null,
  "cancelled_at": null,
  "error": null
}

{
  "code": "NOT_FOUND",
  "message": "Job not found",
  "error_uid": "err_abc123"
}

{
  "detail": "Invalid access with key: api_key_not_found"
}

GET

batch

jobs

{id}

curl https://api.u1.archetypeai.app/v0.5/batch/jobs/job_2abc3def4ghi5jkl6mno7pqr \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")
job_id = "job_2abc3def4ghi5jkl6mno7pqr"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.5/batch/jobs/{job_id}",
    headers={"Authorization": f"Bearer {api_key}"}
)

job = response.json()
print(f"Job: {job['name']} — Status: {job['status']}")

const jobId = 'job_2abc3def4ghi5jkl6mno7pqr';

const response = await fetch(`https://api.u1.archetypeai.app/v0.5/batch/jobs/${jobId}`, {
  headers: {
    'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
  }
});

const job = await response.json();
console.log(`Job: ${job.name} — Status: ${job.status}`);

{
  "id": "job_2abc3def4ghi5jkl6mno7pqr",
  "org_id": "org_1abc2def3ghi4jkl",
  "name": "tep-classification",
  "pipeline_type": "batch",
  "pipeline_key": "machine-state-classification",
  "pipeline_version": "1.1.1",
  "status": "COMPLETED",
  "outcome" "SUCCESS",
  "parameters": {
    "worker": {
      "parallelism": 1,
      "config": {
        "model_type": "omega_1_4_base",
        "batch_size": 32,
        "reader_config": {
          "data_columns": ["xmeas_1", "xmeas_2", "xmv_11"],
          "timestamp_column": "timestamp",
          "window_size": 64,
          "step_size": 1
        },
        "classifier_config": {
          "n_neighbors": 5,
          "metric": "euclidean",
          "weights": "uniform",
          "normalize_embeddings": false
        }
      }
    }
  },
  "retry_count": 0,
  "preemption_count": 0,
  "queue_position": null,
  "queue_depth": null,
  "input_progress": {
    "pending": 0,
    "processing": 0,
    "completed": 1,
    "failed": 0,
    "processed_bytes": 511733,
    "total_bytes": 105332974
  },
  "created_at": "2026-04-14T10:00:00Z",
  "updated_at": "2026-04-14T10:15:00Z",
  "started_at": "2026-04-14T10:02:00Z",
  "completed_at": "2026-04-14T10:15:00Z",
  "failed_at": null,
  "cancelled_at": null,
  "error": null
}

{
  "code": "NOT_FOUND",
  "message": "Job not found",
  "error_uid": "err_abc123"
}

{
  "detail": "Invalid access with key: api_key_not_found"
}

Requires version 1.1.0 or later of the Archetype platform.

Overview

This endpoint returns the full details of a specific job, including its current status, parameters, and timestamps.

Request

string

required

The unique job identifier

Response

string

Unique job identifier

string

Organization identifier

string

Job name

string

Pipeline type (batch or training)

string

Pipeline key. The value is the same as workflow_key. This property is retained for backward compatibility.

string

Key of the workflow this job runs. The value is the same as pipeline_key, which is retained for backward compatibility. v1.1.8+

string

Pipeline version used

string

Current job status: PENDING, ADMITTED, RUNNING, PAUSED, COMPLETED, INTERRUPTED, FAILED, PREEMPTED, or CANCELLED

string

If and only if the job’s status is COMPLETED, this property’s value indicates how the job completed. It is set once upon completion and is never set for a job which is not completed; for incomplete jobs, this value is always omitted. v1.1.5+For completed jobs, the following values are possible:

Value	Description
`SUCCESS`	None of the job’s inputs failed.
`PARTIAL`	At least one of the job’s inputs failed, but the job still produced at least one artifact (either a `job_outputs` entry or a `checkpoints` entry).
`FAILED`	At least one input failed, and the job produced no artifacts at all (no outputs and no checkpoints).

object

Job parameters

integer

Number of times the job has been retried

integer

Number of times the job has been preempted

integer

Current position in queue (null if not queued)

integer

Total queue depth (null if not queued)

object

Per-status counts of tracked (non-reference) inputs, with integer fields shown in the table below. Populated on read paths so list views can render progress badges without N+1 fetches; null on write-path responses (create, retry, cancel).

Property	Description
`completed`	The number of inputs that have reached the `COMPLETED` state.
`failed`	The number of inputs that have reached the `FAILED` state.
`pending`	The number of inputs in the `PENDING` state.
`processed_bytes`	The number of bytes that have been processed so far. This is the sum of `input_bytes` for all inputs being processed plus the sum of the file sizes completed so far plus the sum of the file sizes for failed inputs. This property is only present when `total_bytes` is known and every processing input is reporting `input_bytes`. Otherwise this is absent.
`processing`	The number of inputs currently being processed.
`total_bytes`	The total file size across all tracked inputs. Present only when every tracked input has a known size; otherwise, this is absent.

string

Creation timestamp

string

Last update timestamp

string

Start timestamp (null if not yet started)

string

Completion timestamp (null if not completed)

string

Failure timestamp (null if not failed)

string

Cancellation timestamp (null if not cancelled)

object

Error details (null if no error)

curl https://api.u1.archetypeai.app/v0.5/batch/jobs/job_2abc3def4ghi5jkl6mno7pqr \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")
job_id = "job_2abc3def4ghi5jkl6mno7pqr"

response = requests.get(
    f"https://api.u1.archetypeai.app/v0.5/batch/jobs/{job_id}",
    headers={"Authorization": f"Bearer {api_key}"}
)

job = response.json()
print(f"Job: {job['name']} — Status: {job['status']}")

const jobId = 'job_2abc3def4ghi5jkl6mno7pqr';

const response = await fetch(`https://api.u1.archetypeai.app/v0.5/batch/jobs/${jobId}`, {
  headers: {
    'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
  }
});

const job = await response.json();
console.log(`Job: ${job.name} — Status: ${job.status}`);

{
  "id": "job_2abc3def4ghi5jkl6mno7pqr",
  "org_id": "org_1abc2def3ghi4jkl",
  "name": "tep-classification",
  "pipeline_type": "batch",
  "pipeline_key": "machine-state-classification",
  "pipeline_version": "1.1.1",
  "status": "COMPLETED",
  "outcome" "SUCCESS",
  "parameters": {
    "worker": {
      "parallelism": 1,
      "config": {
        "model_type": "omega_1_4_base",
        "batch_size": 32,
        "reader_config": {
          "data_columns": ["xmeas_1", "xmeas_2", "xmv_11"],
          "timestamp_column": "timestamp",
          "window_size": 64,
          "step_size": 1
        },
        "classifier_config": {
          "n_neighbors": 5,
          "metric": "euclidean",
          "weights": "uniform",
          "normalize_embeddings": false
        }
      }
    }
  },
  "retry_count": 0,
  "preemption_count": 0,
  "queue_position": null,
  "queue_depth": null,
  "input_progress": {
    "pending": 0,
    "processing": 0,
    "completed": 1,
    "failed": 0,
    "processed_bytes": 511733,
    "total_bytes": 105332974
  },
  "created_at": "2026-04-14T10:00:00Z",
  "updated_at": "2026-04-14T10:15:00Z",
  "started_at": "2026-04-14T10:02:00Z",
  "completed_at": "2026-04-14T10:15:00Z",
  "failed_at": null,
  "cancelled_at": null,
  "error": null
}

{
  "code": "NOT_FOUND",
  "message": "Job not found",
  "error_uid": "err_abc123"
}

{
  "detail": "Invalid access with key: api_key_not_found"
}

​Overview

​Request

​Response

Overview

Request

Response