Get Training Status

Poll a policy import until its Training Studio adapter is ready

GET /api/policies/import/{import_id}/train

Get Training Status

cURL

curl --request GET \
  --url https://api.zerodrift.ai/api/policies/import/{import_id}/train \
  --header 'x-api-key: <api-key>'

200 Training Succeeded

{
  "import_id": "550e8400-e29b-41d4-a716-446655440000",
  "training_run_id": "run-808961af",
  "status": "succeeded",
  "stage": "complete",
  "progress": {
    "completed": 4,
    "total": 4
  },
  "error": null
}

Return the current training run for a policy import. Poll after Train Policy Adapter until status is succeeded or failed.

The successful poll is part of activation: when Training Studio reports succeeded, ZeroDrift records the run as the import’s active adapter. A failed retraining attempt does not replace an earlier working adapter.

Path Parameters

import_id · string · required

The policy import whose training run you want to inspect.

Response

import_id · string

Policy import associated with the run.

training_run_id · string

Training Studio run identifier.

status · string

Current run status. succeeded and failed are terminal.

stage · string

Current training pipeline stage, when reported.

progress · object

Training progress details, when reported.

error · string

Failure detail when status is failed.

200 Training Succeeded

{
  "import_id": "550e8400-e29b-41d4-a716-446655440000",
  "training_run_id": "run-808961af",
  "status": "succeeded",
  "stage": "complete",
  "progress": {
    "completed": 4,
    "total": 4
  },
  "error": null
}

Error Responses

Status	Description
403	Invalid API key, or the import belongs to another customer
404	Import not found, or no training run has been started
500	Import state could not be read or updated
502	Training Studio status request failed
503	Training is not configured in this environment

Complete flow

Training extends the custom-policy flow:

1. Import Policy.
2. Poll Get Import Details until extraction reaches pending_review.
3. Review or simulate the extracted rules, then Activate Rules.
4. Train Policy Adapter.
5. Poll this endpoint until status is succeeded or failed. Stop on either terminal status; do not keep polling a failed run.
6. If the run succeeded, enforce content with validation_scope.imports containing the import ID.

Do not submit content for enforcement to a still-training run. ZeroDrift only promotes training_run_id after a successful status poll; until then, scoped enforcement follows its configured fallback path.

Example

This sample starts training and polls to a terminal state.

Python

import time
import requests

API_BASE = "https://api.zerodrift.ai"
API_KEY = "YOUR_API_KEY"
IMPORT_ID = "550e8400-e29b-41d4-a716-446655440000"
URL = f"{API_BASE}/api/policies/import/{IMPORT_ID}/train"
HEADERS = {"x-api-key": API_KEY}

started = requests.post(URL, headers=HEADERS, json={})
started.raise_for_status()
print(started.json())

while True:
    response = requests.get(URL, headers=HEADERS)
    response.raise_for_status()
    training = response.json()
    print(training["status"])

    if training["status"] in ("succeeded", "failed"):
        break
    time.sleep(10)

if training["status"] == "failed":
    raise SystemExit(training.get("error", "Training failed"))