Models & Inference

These endpoints control the AI lifecycle: training models on your custom data and running inference to generate risk scores.

Calibrate Model

Triggers the asynchronous training of an anomaly detection model using the files uploaded to a mission.

Overview: Requires at least 15 files uploaded to the mission.
Endpoint: /api/calibrate
Method: POST

Request Headers

Key	Value	Required
`Content-Type`	`application/json`	Yes
`X-API-KEY`	Your-API-Key	Yes

Request Body

Parameter	Type	Required	Description
`robot_id`	uuid	Yes	The UUID of the robot.
`mission_id`	uuid	Yes	The UUID of the mission.
`robot_type`	string	Yes	The hardware type. Allowed: `SPOT`, `UR6`.
`blob_names`	list[str]	No	List of `unique_filenames` to train on. Defaults to all.
`epochs1`	int	No	Training epochs (Default: 100).
`batch_size`	int	No	Batch size for training (Default: 128).
`retrain`	boolean	No	Set `true` to force retraining (Default: false).

Success Response

Code: 200 OK

{
  "details": {
    "task_id": "a493b453-e29b-41d4-a716-446655440000"
  },
  "message": "Training task queued"
}

Possible Errors

400 Bad Request: Expected 15 files, but found X.
400 Bad Request: Model already exists.
401 Unauthorized: Invalid or missing API Key.

Sample Code (Python)

import requests

url = "[https://api.ridescan.ai/api/calibrate](https://api.ridescan.ai/api/calibrate)"
headers = {
    "Content-Type": "application/json",
    "X-API-KEY": "YOUR_API_KEY"
}
payload = {
    "robot_id": "e7201eff-e29b-41d4-a716-446655440000",
    "mission_id": "9384ac10-e29b-41d4-a716-446655440000",
    "robot_type": "SPOT",
    "epochs1": 150,
    "retrain": True
}

response = requests.post(url, json=payload, headers=headers)
print(response.json())

Process Files (Inference)

Runs the trained model against specific files to generate Risk Scores.

Overview: The mission must have a trained model (calibration_completed) before you can run inference.
Endpoint: /api/process
Method: POST

Request Headers

Key	Value	Required
`Content-Type`	`application/json`	Yes
`X-API-KEY`	Your-API-Key	Yes

Request Body

Parameter	Type	Required	Description
`robot_id`	uuid	Yes	The UUID of the robot.
`mission_id`	uuid	Yes	The UUID of the mission.
`blob_names`	list[str]	No	List of `unique_filenames` to analyze. Defaults to all.
`device`	string	No	Device to run inference on: `cpu` or `cuda` (Default: `cpu`).

Success Response

Code: 200 OK

{
  "file sent": [
    "1a3a81da-e29b-41d4-a716-446655440000_Day16.bag",
    "ac8d4704-e29b-41d4-a716-446655440000_Day17.bag"
  ],
  "message": "Processing queued"
}

Possible Errors

RS-MOD-001: Model not found (Training not completed).
401 Unauthorized: Invalid or missing API Key.

Sample Code (Python)

import requests

url = "[https://api.ridescan.ai/api/process](https://api.ridescan.ai/api/process)"
headers = {
    "Content-Type": "application/json",
    "X-API-KEY": "YOUR_API_KEY"
}
payload = {
    "robot_id": "e7201eff-e29b-41d4-a716-446655440000",
    "mission_id": "9384ac10-e29b-41d4-a716-446655440000",
    "device": "cpu"
}

response = requests.post(url, json=payload, headers=headers)
print(response.json())

Get Model & Mission Details

Retrieves the current status of the AI model and the aggregated risk scores.

Endpoint: /api/model/mission-details
Method: GET

Request Headers

Key	Value	Required
`Content-Type`	`application/json`	Yes
`X-API-KEY`	Your-API-Key	Yes

Query Parameters

Parameter	Type	Required	Description
`mission_id`	uuid	Yes	The Public UUID of the mission.

Success Response

Code: 200 OK

{
  "data": {
    "calibration_status": "calibration_completed",
    "epochs": 100,
    "files": [
      {
        "event time": "2026-03-04T10:30:00",
        "file type": "calib_file",
        "original filename": "Day1.bag",
        "risk_score": 10.02,
        "unique filename": "b503c086-3_Day1.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day2.bag",
        "risk_score": 10.02,
        "unique filename": "db830b9b-6_Day2.bag"
      },
      {
        "event time": "2026-03-04T10:30:00",
        "file type": "calib_file",
        "original filename": "Day1.bag",
        "risk_score": 10.02,
        "unique filename": "c9c20b14-e_Day1.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day2.bag",
        "risk_score": 10.02,
        "unique filename": "b64bf76e-7_Day2.bag"
      },
      {
        "event time": "2026-03-04T10:30:00",
        "file type": "calib_file",
        "original filename": "Day1.bag",
        "risk_score": 10.02,
        "unique filename": "ddb86b72-5_Day1.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day2.bag",
        "risk_score": 10.02,
        "unique filename": "e3517aad-b_Day2.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day3.bag",
        "risk_score": 13.02,
        "unique filename": "ce1931d0-9_Day3.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day4.bag",
        "risk_score": 15.02,
        "unique filename": "b0a66594-4_Day4.bag"
      },
      {
        "event time": "2026-03-04T10:30:00",
        "file type": "calib_file",
        "original filename": "Day1.bag",
        "risk_score": 04.02,
        "unique filename": "1f073c92-a_Day1.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day2.bag",
        "risk_score": 10.06,
        "unique filename": "553a87ff-b_Day2.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day3.bag",
        "risk_score": 10.03,
        "unique filename": "3acee6fb-8_Day3.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day4.bag",
        "risk_score": 10.07,
        "unique filename": "92663c10-3_Day4.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day1.bag",
        "risk_score": 08.02,
        "unique filename": "9f4b6f7d-c_Day1.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day2.bag",
        "risk_score": 11.02,
        "unique filename": "5a25512f-6_Day2.bag"
      },
      {
        "event time": "2026-03-03T10:30:00",
        "file type": "calib_file",
        "original filename": "Day3.bag",
        "risk_score": 10.02,
        "unique filename": "d5544d2b-1_Day3.bag"
      }
    ],
    "inference_possible": true,
    "inference_status": "processing_completed",
    "mission_avg_risk_score": 21.19,
    "mission_length": 1977,
    "robot_avg_risk_score": 21.19,
    "robot_type": "0",
    "training_time": "Thu, 26 Feb 2026 13:34:14 GMT",
    "upload_time": "Thu, 26 Feb 2026 13:41:43 GMT"
  },
  "message": "Model fetched successfully"
}

Possible Errors

RS-MSN-002: Mission ID not found.
401 Unauthorized: Invalid or missing API Key.

Sample Code (Python)

import requests

url = "[https://api.ridescan.ai/api/model/mission-details](https://api.ridescan.ai/api/model/mission-details)"
headers = {
    "Content-Type": "application/json",
    "X-API-KEY": "YOUR_API_KEY"
}
params = {
    "mission_id": "9384ac10-e29b-41d4-a716-446655440000"
}

response = requests.get(url, params=params, headers=headers)
print(response.json())