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

<head>
    <meta charset="UTF-8">
    <title>Translation - huggingface.js</title>
<!--
    <script type="module">
        // Import the library
        //import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';

        // Make it available globally
        //window.pipeline = pipeline;
    </script>
-->
    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.0/dist/css/bootstrap.min.css" rel="stylesheet">
    <link rel="stylesheet" href="css/styles.css">
</head>

<body>
    <div class="container-main">

        <!-- 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>Translation</h4>
            </div>

            <!-- Actual Content of this page -->
          <form id="hf-form">
            <input
                type="text"
                style="display:none"  
                autocomplete="username"  
                value="user" 
            />
            <div>
                <label for="hf-token">Hugging Face Token (optional but limited if absent)</label>
                <input
                    id="hf-token"
                    placeholder="HF-TOKEN"
                    type="password"
                    autocomplete="new-password"
                />
            </div>
            <div id="translation-container" class="container mt-4">
                <h5>Translation w/ Xenova/t5-base:</h5>
                <div class="d-flex align-items-center">
                    <label for="translationText2" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Text to
                        Translate:</label>
                    <input type="text" class="form-control flex-grow-1" id="translationText2" value="My name is Wolfgang and I live in Amsterdam"
                        placeholder="Enter text" style="margin-right: 15px; margin-left: 15px;">
                    <button id="translateButton2" class="btn btn-primary" onclick="translateText()">Translate</button>
                </div>
          
                <div class="mt-4">
                    <h4>Output:</h4>
                    <pre id="outputArea2"></pre>
                </div>
            </div>
          </form>
            <!-- 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 type="module">
       import { HfInference } from 'https://cdn.jsdelivr.net/npm/@huggingface/inference@2.6.4/+esm';

        // Initialize the sentiment analysis model
        async function initializeModel() {
            const token = document.getElementById('hf-token').value;
            const hf = new HfInference(token);
        }

        async function translateText() {
            const textFieldValue = document.getElementById("translationText").value.trim();

            let result = await hf.translation({
                  model: 't5-base',
                  inputs: textFieldValue,          
          });
            document.getElementById("outputArea2").innerText = JSON.stringify(result, null, 2);
        }  


/*          
          document.getElementById('hf-form').addEventListener('submit', async (event) => {
              event.preventDefault();
              

              
              // You can also omit "model" to use the recommended model for the task
              let result = await hf.translation({
                  model: 't5-base',
                  inputs: textFieldValue,
              document.getElementById("outputArea2").innerText = JSON.stringify(result, null, 2);          
          });
            
          console.log(result);
          });
      
*/
        // Initialize the model after the DOM is completely loaded
        window.addEventListener("DOMContentLoaded", initializeModel);
    </script>
</body>

</html>