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HelixML API for Integration

Scenario: A developer, named Alex, wants to integrate HelixML into their existing application and automate machine learning workflows. HelixML provides a RESTful API that allows developers to interact with the platform programmatically. In this example, Alex will create a Go application that uses the HelixML API to perform various tasks, such as creating a new model, making predictions, and managing data.

Prerequisites:

  • Familiarity with Go programming language
  • Basic understanding of HelixML and its concepts
  • HelixML API documentation: https://docs.helixml.ai/api/

Steps:

  1. Create a new Go project:
mkdir go-helixml-integration
cd go-helixml-integration
go mod init go-helixml-integration
  1. Install required packages:
go get github.com/parnurzeal/gorequest
go get github.com/joho/godotenv
  1. Create a .env file to store HelixML API credentials:
HELIXML_API_KEY=<your_api_key>
HELIXML_API_SECRET=<your_api_secret>
  1. Create a main.go file and import necessary packages:
package main

import (
    "context"
    "encoding/json"
    "fmt"
    "github.com/parnurzeal/gorequest"
    "github.com/joho/godotenv"
    "os"
)

// ...
  1. Load environment variables from .env file:
func main() {
    err := godotenv.Load()
    if err != nil {
        fmt.Println("Error loading .env file")
        os.Exit(1)
    }
}
  1. Define HelixML API client:
type HelixMLClient struct {
    BaseURL string
    Client  *gorequest.Client
}

func NewHelixMLClient() *HelixMLClient {
    return &HelixMLClient{
        BaseURL: "https://api.helixml.ai/v1",
        Client:  gorequest.New(),
    }
}
  1. Implement HelixML API methods:
func (h *HelixMLClient) CreateModel(modelName string, modelDescription string) error {
    // ...
}

func (h *HelixMLClient) MakePrediction(modelID int, inputData map[string]interface{}) (map[string]interface{}, error) {
    // ...
}

// ...
  1. Implement main function:
func main() {
    client := NewHelixMLClient()

    // Create a new model
    err := client.CreateModel("my_model", "A model for predicting sales leads")
    if err != nil {
        fmt.Println("Error creating model:", err)
        os.Exit(1)
    }

    // Make a prediction
    inputData := map[string]interface{}{
        "age": 30,
        "income": 50000,
        "job_title": "Software Engineer",
    }
    prediction, err := client.MakePrediction(1, inputData)
    if err != nil {
        fmt.Println("Error making prediction:", err)
        os.Exit(1)
    }

    fmt.Println("Prediction:", prediction)
}

Tests:

To test the integration, you can create unit tests for each HelixML API method. For example, you can create a test.go file with the following content:

package main

import (
    "testing"
    "github.com/parnurzeal/gorequest"
    "github.com/joho/godotenv"
    "os"
    "assert"
    "encoding/json"
)

func TestCreateModel(t *testing.T) {
    // ...
}

func TestMakePrediction(t *testing.T) {
    // ...
}

func main() {
    godotenv.Load()
    testing.Main()
}

In each test function, you can use gorequest to send HTTP requests to the HelixML API and assert the response data against expected values.

Conclusion:

In this example, we have demonstrated how to integrate HelixML into a Go application using its RESTful API. We created a new Go project, installed required packages, loaded environment variables, defined HelixML API client, and implemented HelixML API methods. We also provided a main function to create a new model and make a prediction using the HelixML API. Finally, we created unit tests for each HelixML API method.