When you upload the generation or consumption data to a site, a set of preconfigured machine learning (ML) models is created. To start the training procedure of these models, you will need to provide a number of training parameters. Currently the following parameters are supported.

Site IDs site_ids
Specify a list of site IDs for which ML models will be trained.
Example: ["8fa9ef1d-4s89-4waf-8g52-b1aww743by47"]

Training set splits splits
Specify the starting and ending periods for the training data set splits.

  • Starting period start_date
    Specify the starting timestamp.
    Example: "2022-01-01T00:00Z"

  • Ending period end_date
    Specify the ending timestamp.
    Example: "2022-12-31T23:00Z"

Train models
import requests

api_key = "Your API key" # Set your API key
site_id = "a923653c-26f1-1b29-955d-ffde5d182276" # Set the site ID

payload = {
    "site_ids": ["8fa9ef1d-4s89-4waf-8g52-b1aww743by47"],
    "splits": [
        {
            "start_date": "2022-01-01T00:00Z",
			"end_date": "2022-12-31T23:00Z"
        },
        {
            "start_date": "2024-01-01T00:00Z",
			"end_date": "2024-06-30T23:00Z"
        }		
    ]
}

url = f"https://api.rebase.energy/platform/v2/sites/{site_id}/models/train"
headers = {"Authorization": api_key, "Content-Type": "application/json"}			

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