lab-on-serving-ml-models-202509-m/frontend/api_test_DT_classifier.html at main · BI-course/lab-on-serving-ml-models-202509-m · GitHub

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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Decision Tree Classifier - Predict Customer Churn</title>
    <style>
        body {
            font-family: Arial, sans-serif;
            margin: 40px;
            max-width: 500px;
        }
        input[type="number"] {
            width: 100%;
            padding: 8px;
            margin: 8px 0;
            box-sizing: border-box;
        }
        button {
            padding: 10px 15px;
            background-color: #4CAF50;
            color: white;
            border: none;
            cursor: pointer;
            margin-top: 10px;
        }
        #result {
            margin-top: 20px;
            font-weight: bold;
        }
    </style>
</head>
<body>

<h2>Predict Customer Churn using a Decision Tree Classifier</h2>

<form id="predictForm">
    <label for="monthly_fee">Monthly Fee:</label>
    <input type="number" id="monthly_fee" name="monthly_fee" required>

    <label for="customer_age">Customer Age:</label>
    <input type="number" id="customer_age" name="customer_age" required>

    <label for="support_calls">Support Calls:</label>
    <input type="number" id="support_calls" name="support_calls" required>

    <button type="submit">Predict</button>
</form>

<div id="result"></div>

<script>
    document.getElementById('predictForm').addEventListener('submit', async function(event) {
        event.preventDefault();

        // Read form values
        const monthly_fee = parseFloat(document.getElementById('monthly_fee').value);
        const customer_age = parseFloat(document.getElementById('customer_age').value);
        const support_calls = parseFloat(document.getElementById('support_calls').value);

        // Create JSON payload
        const data = {
            monthly_fee: monthly_fee,
            customer_age: customer_age,
            support_calls: support_calls
        };

        try {
            const response = await fetch('http://127.0.0.1:5000/api/v1/models/decision-tree-classifier/predictions', {
            // const response = await fetch('https://127.0.0.1:443/api/v1/models/decision-tree-classifier/predictions', {
                method: 'POST',
                headers: {
                    'Content-Type': 'application/json'
                },
                body: JSON.stringify(data)
            });

            const result = await response.json();
            document.getElementById('result').innerText = 'Prediction: ' + result['Predicted Class = '];

        } catch (error) {
            console.error('Error:', error);
            document.getElementById('result').innerText = 'An error occurred while making the prediction.';
        }
    });
</script>

</body>
</html>