curl https://api.u1.archetypeai.app/v0.5/batch/registry/pipelines/ppl_abc123def456/schema \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")
pipeline_id = "ppl_abc123def456"

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

schema = response.json()
print(f"Pipeline: {schema['pipeline_key']} v{schema['pipeline_version']}")
print(f"Inputs: {list(schema['inputs'].keys())}")
print(f"Outputs: {list(schema['outputs'].keys())}")
print(f"User schema: {schema['user_schema']}")

const pipelineId = 'ppl_abc123def456';

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

const schema = await response.json();
console.log(`Pipeline: ${schema.pipeline_key} v${schema.pipeline_version}`);
console.log('Inputs:', Object.keys(schema.inputs));
console.log('Outputs:', Object.keys(schema.outputs));
console.log('User schema:', JSON.stringify(schema.user_schema, null, 2));

{
  "id": "ppl_abc123def456",
  "pipeline_key": "machine-state-classification",
  "pipeline_version": "1.1.1",
  "user_schema": {
    "type": "object",
    "properties": {
      "model_type": {
        "type": "string",
        "description": "Omega model variant used to generate embeddings.",
        "enum": ["omega_1_4_base", "omega_1_3_surface", "omega_1_3_power_drive"],
        "default": "omega_1_4_base"
      },
      "batch_size": {
        "type": "integer",
        "description": "Number of windows processed together in a single batch.",
        "default": 32,
        "minimum": 1
      },
      "classifier_config": {
        "type": "object",
        "properties": {
          "n_neighbors": {"type": "integer", "minimum": 3, "default": 5},
          "metric": {"type": "string", "enum": ["euclidean", "cosine", "manhattan"], "default": "euclidean"},
          "weights": {"type": "string", "enum": ["uniform", "distance"], "default": "uniform"},
          "normalize_embeddings": {"type": "boolean", "default": false}
        }
      }
    }
  },
  "config_schema": {},
  "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"
    }
  }
}

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

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