Request a Forecast - Nolano API

POST /forecast

This endpoint allows you to get a time series forecast from the API.

Base URL

https://api.nolano.ai/forecast

Authentication

An API key must be provided in the request headers using the Authorization header.

Authorization: your_api_key_here

Headers

X-Model-Id

string

The ID of the model you want to use for the forecast. If not provided, the default model will be used.

Available Models

The API provides four different forecasting models, each optimized for different use cases:

Show Model Details

forecast-model-1

string

Primary Forecasting Model - Optimized for time series prediction and trend analysis. Best for general forecasting tasks with good balance of accuracy and performance.

forecast-model-2

string

Alternative Forecasting Model - Enhanced accuracy for complex patterns with multi-seasonal forecasting and anomaly detection capabilities.

forecast-model-3

string

Advanced Forecasting Model - High-frequency data processing with real-time forecasting and scalable predictions for large datasets.

forecast-model-4

string

Next-Generation Model - Deep learning integration with ensemble methods and cross-domain forecasting capabilities.

Request Body

The request must be a JSON object with the following structure.

series

array

required

An array containing one or more time series objects. For now, only one is supported.

Show Series Object Properties

timestamps

array of strings

required

A list of timestamps for your historical data in YYYY-MM-DDTHH:MM:SS format.

values

array of numbers

required

A list of numerical values corresponding to each timestamp. This array must be the same length as timestamps.

forecast_horizon

integer

required

The number of future periods you want to predict.

data_frequency

string

required

The frequency of your input timestamps. Must be one of: “Seconds”, “Minutes”, “Hours”, “Daily”, “Weekly”, “Monthly”, “Quarterly”, “Yearly”.

forecast_frequency

string

required

The desired frequency of the forecast output. Currently, this must match data_frequency.

confidence

float

default:"0.95"

The desired confidence level for the upper and lower forecast bounds. Must be between 0 and 1 (e.g., 0.95 for 95%).

Example Request

curl --location 'https://api.nolano.ai/forecast' \
--header 'Content-Type: application/json' \
--header 'Authorization: your_api_key_here' \
--header 'X-Model-Id: forecast-model-1' \
--data '{
  "series": [
    {
      "timestamps": ["2023-01-01T00:00:00", "2023-01-02T00:00:00"],
      "values": [100, 102]
    }
  ],
  "forecast_horizon": 24,
  "data_frequency": "Daily",
  "forecast_frequency": "Daily",
  "confidence": 0.95
}'

Response

On a successful request, the API will return a 200 OK status with a JSON object containing the forecast.

forecast_timestamps

array of strings

The timestamps for the forecasted values.

lower_bound

array of numbers

The lower bound of the forecast confidence interval.

median

array of numbers

The median forecasted values.

upper_bound

array of numbers

The upper bound of the forecast confidence interval.

Example Response

{
    "forecast_timestamps": ["2024-01-01T00:00:00", "2024-01-02T00:00:00"],
    "lower_bound": [145.5, 146.5],
    "median": [150.0, 151.0],
    "upper_bound": [154.5, 155.5]
}

Overview

Forecasting

​POST /forecast

​Base URL

​Authentication

​Headers

​Available Models

​Request Body

​Example Request

​Response

​Example Response

POST /forecast

Base URL

Authentication

Headers

Available Models

Request Body

Example Request

Response

Example Response