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<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <title>Token Classification - Hugging Face Transformers.js</title>

    <script type="module">
        // Import the library
        import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';

        // Make it available globally
        window.pipeline = pipeline;
    </script>

    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">

    <link rel="stylesheet" href="css/styles.css">
</head>

<body>
    <div class="container-main">
        <!-- Page Header -->
        <div class="header">
            <div class="header-logo">
                <img src="images/logo.png" alt="logo">
            </div>
            <div class="header-main-text">
                <h1>Hugging Face Transformers.js</h1>
            </div>
            <div class="header-sub-text">
                <h3>Free AI Models for JavaScript Web Development</h3>
            </div>
        </div>
        <hr> <!-- Separator -->

        <!-- Back to Home button -->
        <div class="row mt-5">
            <div class="col-md-12 text-center">
                <a href="index.html" class="btn btn-outline-secondary"
                    style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
            </div>
        </div>

        <!-- Content -->
        <div class="container mt-5">
            <!-- Centered Titles -->
            <div class="text-center">
                <h2>Natural Language Processing</h2>
                <h4>Token Classification (Named Entity Recognition)</h4>
            </div>

            <!-- Actual Content of this page -->
            <div id="token-classification-container" class="container mt-4">
                <h5>Perform Named Entity Recognition with Xenova/bert-base-NER:</h5>
                <div class="d-flex align-items-center">
                    <label for="tokenClassificationText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text to Recognize:</label>
                    <input type="text" class="form-control flex-grow-1" id="tokenClassificationText"
                        value="My name is Sarah and I live in London" placeholder="Enter text"
                        style="margin-right: 15px; margin-left: 15px;">
                    <button id="classifyButton" class="btn btn-primary" onclick="analyzeText()">analyze</button>
                </div>
                <div class="mt-4">
                    <h4>Output:</h4>
                    <pre id="outputArea"></pre>
                </div>
            </div>

            <hr> <!-- Line Separator -->

            <div id="token-classification-container2" class="container mt-4">
                <h5>Perform Named Entity Recognition with Xenova/bert-base-NER (Return all Labels):</h5>
                <div class="d-flex align-items-center">
                    <label for="tokenClassificationText2" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text to Recognize:</label>
                    <input type="text" class="form-control flex-grow-1" id="tokenClassificationText2"
                        value="Sarah lives in the United States of America" placeholder="Enter text"
                        style="margin-right: 15px; margin-left: 15px;">
                    <button id="classifyButton2" class="btn btn-primary" onclick="analyzeText2()">analyze</button>
                </div>
                <div class="mt-4">
                    <h4>Output:</h4>
                    <pre id="outputArea2"></pre>
                </div>
            </div>

            <!-- Back to Home button -->
            <div class="row mt-5">
                <div class="col-md-12 text-center">
                    <a href="index.html" class="btn btn-outline-secondary"
                        style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
                </div>
            </div>
        </div>
    </div>

    <script>

        let classifier;

        // Initialize the sentiment analysis model
        async function initializeModel() {
            classifier = await pipeline('token-classification', 'Xenova/bert-base-NER');

        }

        async function analyzeText() {
            const textFieldValue = document.getElementById("tokenClassificationText").value.trim();

            const result = await classifier(textFieldValue);

            document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2);
        }

        async function analyzeText2() {
            const textFieldValue = document.getElementById("tokenClassificationText2").value.trim();

            const result = await classifier(textFieldValue, { ignore_labels: [] });

            document.getElementById("outputArea2").innerText = JSON.stringify(result, null, 2);
        }

        // Initialize the model after the DOM is completely loaded
        window.addEventListener("DOMContentLoaded", initializeModel);
    </script>
</body>

</html>