List Pipelines - Archetype AI Documentation

curl "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines?pipeline_type=batch&status=published" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

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

response = requests.get(
    "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines",
    headers={"Authorization": f"Bearer {api_key}"},
    params={
        "pipeline_type": "batch",
        "status": "published"
    }
)

data = response.json()
print(f"Total pipelines: {data['total']}")
for pipeline in data["pipelines"]:
    print(f"  {pipeline['pipeline_key']} v{pipeline['pipeline_version']}: {pipeline['name']}")

const params = new URLSearchParams({
  pipeline_type: 'batch',
  status: 'published'
});

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

const data = await response.json();
console.log(`Total pipelines: ${data.total}`);
data.pipelines.forEach(pipeline => {
  console.log(`  ${pipeline.pipeline_key} v${pipeline.pipeline_version}: ${pipeline.name}`);
});

{
  "total": 5,
  "offset": 0,
  "limit": 20,
  "pipelines": [
    {
      "id": "ppl_abc123def456",
      "pipeline_key": "machine-state-classification",
      "pipeline_version": "1.1.1",
      "name": "Machine State Classification",
      "description": "Identify labeled states in time series sensor data",
      "pipeline_type": "batch",
      "components": {
        "worker": "cmp_xyz789"
      },
      "default_config": {
        "worker": {
          "parallelism": 1,
          "config": {
            "model_type": "omega_1_4_base",
            "batch_size": 32
          }
        }
      },
      "config_schema": {},
      "user_config_schema": {},
      "edges": [],
      "inputs": {
        "worker.inference": {
          "name": "Input files",
          "description": "CSV files for machine-state classification",
          "mode": "plain_file_list",
          "distribute": "scatter",
          "required": true,
          "tracked": true
        },
        "worker.n_shots": {
          "name": "N-Shot example files",
          "description": "Labeled few-shot training files (class declared via input metadata)",
          "mode": "n_shot_file_list",
          "distribute": "replicate",
          "required": true,
          "tracked": false
        }
      },
      "outputs": {
        "worker.results": {
          "name": "Output files",
          "description": "Machine-state classification results"
        }
      },
      "retry_policy": {},
      "visibility": "platform",
      "org_id": "org_1abc2def3ghi4jkl",
      "status": "published",
      "created_at": "2026-03-01T00:00:00Z",
      "updated_at": "2026-04-01T00:00:00Z"
    }
  ]
}

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

GET

batch

registry

pipelines

curl "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines?pipeline_type=batch&status=published" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

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

response = requests.get(
    "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines",
    headers={"Authorization": f"Bearer {api_key}"},
    params={
        "pipeline_type": "batch",
        "status": "published"
    }
)

data = response.json()
print(f"Total pipelines: {data['total']}")
for pipeline in data["pipelines"]:
    print(f"  {pipeline['pipeline_key']} v{pipeline['pipeline_version']}: {pipeline['name']}")

const params = new URLSearchParams({
  pipeline_type: 'batch',
  status: 'published'
});

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

const data = await response.json();
console.log(`Total pipelines: ${data.total}`);
data.pipelines.forEach(pipeline => {
  console.log(`  ${pipeline.pipeline_key} v${pipeline.pipeline_version}: ${pipeline.name}`);
});

{
  "total": 5,
  "offset": 0,
  "limit": 20,
  "pipelines": [
    {
      "id": "ppl_abc123def456",
      "pipeline_key": "machine-state-classification",
      "pipeline_version": "1.1.1",
      "name": "Machine State Classification",
      "description": "Identify labeled states in time series sensor data",
      "pipeline_type": "batch",
      "components": {
        "worker": "cmp_xyz789"
      },
      "default_config": {
        "worker": {
          "parallelism": 1,
          "config": {
            "model_type": "omega_1_4_base",
            "batch_size": 32
          }
        }
      },
      "config_schema": {},
      "user_config_schema": {},
      "edges": [],
      "inputs": {
        "worker.inference": {
          "name": "Input files",
          "description": "CSV files for machine-state classification",
          "mode": "plain_file_list",
          "distribute": "scatter",
          "required": true,
          "tracked": true
        },
        "worker.n_shots": {
          "name": "N-Shot example files",
          "description": "Labeled few-shot training files (class declared via input metadata)",
          "mode": "n_shot_file_list",
          "distribute": "replicate",
          "required": true,
          "tracked": false
        }
      },
      "outputs": {
        "worker.results": {
          "name": "Output files",
          "description": "Machine-state classification results"
        }
      },
      "retry_policy": {},
      "visibility": "platform",
      "org_id": "org_1abc2def3ghi4jkl",
      "status": "published",
      "created_at": "2026-03-01T00:00:00Z",
      "updated_at": "2026-04-01T00:00:00Z"
    }
  ]
}

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

Requires version 1.1.0 or later of the Archetype platform.

Overview

This endpoint returns a paginated list of pipelines available in the registry. You can filter by pipeline type, visibility, and status.

Request

string

Filter by pipeline type: batch or training

string

Filter by visibility: platform (visible to all orgs) or org (visible only to owning org)

string

Filter by registry status: draft, published, deactivated, or deleted

integer

Number of items to skip for pagination (default: 0)

integer

Maximum number of items to return per page

Response

integer

Total number of pipelines matching the filter criteria

integer

Current pagination offset

integer

Maximum number of items returned

array

Array of pipeline objects, each containing:

id — Unique pipeline identifier
pipeline_key — Pipeline key
pipeline_version — Pipeline version
name — Human-readable pipeline name
description — Pipeline description
pipeline_type — Pipeline type (batch or training)
components — Map of component names to component IDs
default_config — Default configuration per component
config_schema — JSON Schema for pipeline configuration
user_config_schema — User-facing JSON Schema
edges — Pipeline graph edges connecting components
inputs — Map of input port name to port definition. Each port has name, description, mode (plain_file_list or n_shot_file_list), distribute (scatter or replicate), required (bool), and tracked (bool — whether files on this port participate in per-input lifecycle tracking; false for reference/n-shot ports)
outputs — Map of output port name to port definition (name, description)
retry_policy — Retry policy configuration
visibility — Visibility level (platform or org)
org_id — Owning organization ID
status — Registry status
created_at — Creation timestamp
updated_at — Last update timestamp

curl "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines?pipeline_type=batch&status=published" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

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

response = requests.get(
    "https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines",
    headers={"Authorization": f"Bearer {api_key}"},
    params={
        "pipeline_type": "batch",
        "status": "published"
    }
)

data = response.json()
print(f"Total pipelines: {data['total']}")
for pipeline in data["pipelines"]:
    print(f"  {pipeline['pipeline_key']} v{pipeline['pipeline_version']}: {pipeline['name']}")

const params = new URLSearchParams({
  pipeline_type: 'batch',
  status: 'published'
});

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

const data = await response.json();
console.log(`Total pipelines: ${data.total}`);
data.pipelines.forEach(pipeline => {
  console.log(`  ${pipeline.pipeline_key} v${pipeline.pipeline_version}: ${pipeline.name}`);
});

{
  "total": 5,
  "offset": 0,
  "limit": 20,
  "pipelines": [
    {
      "id": "ppl_abc123def456",
      "pipeline_key": "machine-state-classification",
      "pipeline_version": "1.1.1",
      "name": "Machine State Classification",
      "description": "Identify labeled states in time series sensor data",
      "pipeline_type": "batch",
      "components": {
        "worker": "cmp_xyz789"
      },
      "default_config": {
        "worker": {
          "parallelism": 1,
          "config": {
            "model_type": "omega_1_4_base",
            "batch_size": 32
          }
        }
      },
      "config_schema": {},
      "user_config_schema": {},
      "edges": [],
      "inputs": {
        "worker.inference": {
          "name": "Input files",
          "description": "CSV files for machine-state classification",
          "mode": "plain_file_list",
          "distribute": "scatter",
          "required": true,
          "tracked": true
        },
        "worker.n_shots": {
          "name": "N-Shot example files",
          "description": "Labeled few-shot training files (class declared via input metadata)",
          "mode": "n_shot_file_list",
          "distribute": "replicate",
          "required": true,
          "tracked": false
        }
      },
      "outputs": {
        "worker.results": {
          "name": "Output files",
          "description": "Machine-state classification results"
        }
      },
      "retry_policy": {},
      "visibility": "platform",
      "org_id": "org_1abc2def3ghi4jkl",
      "status": "published",
      "created_at": "2026-03-01T00:00:00Z",
      "updated_at": "2026-04-01T00:00:00Z"
    }
  ]
}

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

List Job Progress Get Pipeline

⌘I

​Overview

​Request

​Response

Overview

Request

Response