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typosaurus-rex-wizard

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Tim13ekd commited on 22 days ago

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112beca

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1 Parent(s): 46926b6

weiter

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Files changed (5) hide show

README.md +8 -5
components/training-status.js +78 -0
index.html +79 -19
script.js +197 -0
style.css +49 -19

README.md CHANGED Viewed

@@ -1,10 +1,13 @@
 ---
-title: Typosaurus Rex Wizard
-emoji: 🐢
-colorFrom: gray
-colorTo: purple
 sdk: static
 pinned: false
 ---
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

 ---
+title: Typosaurus Rex Wizard 🦖✨
+colorFrom: red
+colorTo: yellow
+emoji: 🐳
 sdk: static
 pinned: false
+tags:
+  - deepsite-v3
 ---
+# Welcome to your new DeepSite project!
+This project was created with [DeepSite](https://huggingface.co/deepsite).

components/training-status.js ADDED Viewed

	@@ -0,0 +1,78 @@

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Neural Word Wizard</title>
+    <link rel="stylesheet" href="style.css">
+    <script src="https://cdn.tailwindcss.com"></script>
+    <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
+    <script src="https://unpkg.com/feather-icons"></script>
+</head>
+<body class="bg-gray-100 min-h-screen">
+    <div class="container mx-auto px-4 py-12">
+        <header class="text-center mb-12">
+            <div class="flex items-center justify-center space-x-3">
+                <i data-feather="zap" class="w-10 h-10 text-purple-600"></i>
+                <h1 class="text-4xl font-bold bg-gradient-to-r from-purple-600 to-blue-500 bg-clip-text text-transparent">Neural Word Wizard</h1>
+            </div>
+            <p class="mt-4 text-lg text-gray-600">Fix your typos with AI magic! ✨</p>
+        </header>
+        <div class="max-w-2xl mx-auto bg-white rounded-xl shadow-md overflow-hidden p-6">
+            <div class="mb-6">
+                <label for="dataset" class="block text-sm font-medium text-gray-700 mb-2">Training Dataset (one sentence per line)</label>
+                <textarea id="dataset" rows="5" class="w-full px-3 py-2 border border-gray-300 rounded-md shadow-sm focus:outline-none focus:ring-2 focus:ring-purple-500 focus:border-purple-500" placeholder="Enter sample sentences here...
+Example:
+hello world
+how are you
+what is your name"></textarea>
+                <div class="flex justify-end mt-2">
+                    <button id="trainBtn" class="px-4 py-2 bg-purple-600 text-white rounded-md hover:bg-purple-700 focus:outline-none focus:ring-2 focus:ring-purple-500 focus:ring-offset-2 flex items-center">
+                        <i data-feather="cpu" class="mr-2"></i> Train Model
+                    </button>
+                </div>
+            </div>
+            <div id="modelControls" class="hidden space-y-6 border-t pt-6">
+                <div>
+                    <label for="inputWord" class="block text-sm font-medium text-gray-700 mb-2">Enter a typo to fix:</label>
+                    <div class="flex space-x-2">
+                        <input id="inputWord" type="text" class="flex-1 px-3 py-2 border border-gray-300 rounded-md focus:outline-none focus:ring-2 focus:ring-purple-500 focus:border-purple-500" placeholder="wsa, helo, waht, etc.">
+                        <button id="predictBtn" class="px-4 py-2 bg-blue-600 text-white rounded-md hover:bg-blue-700 focus:outline-none focus:ring-2 focus:ring-blue-500 focus:ring-offset-2 flex items-center">
+                            <i data-feather="wand" class="mr-2"></i> Predict
+                        </button>
+                    </div>
+                </div>
+                <div id="resultContainer" class="hidden rounded-lg bg-purple-50 p-4">
+                    <h3 class="text-sm font-medium text-purple-800 mb-2 flex items-center">
+                        <i data-feather="info" class="mr-2"></i> Prediction Result
+                    </h3>
+                    <p id="resultText" class="text-purple-900"></p>
+                </div>
+                <div id="vocabularyContainer" class="rounded-lg bg-blue-50 p-4">
+                    <div class="flex justify-between items-center mb-2">
+                        <h3 class="text-sm font-medium text-blue-800 flex items-center">
+                            <i data-feather="book" class="mr-2"></i> Learned Vocabulary
+                        </h3>
+                        <span id="wordCount" class="text-xs bg-blue-200 text-blue-800 px-2 py-1 rounded-full">0 words</span>
+                    </div>
+                    <div id="vocabularyList" class="flex flex-wrap gap-2">
+                        <!-- Words will appear here -->
+                    </div>
+                </div>
+            </div>
+        </div>
+        <div class="max-w-2xl mx-auto mt-8 text-center text-sm text-gray-500">
+            <p>Enter some sentences, train the model, then test it by entering common typos.</p>
+            <p>The neural network will try to predict the correct word based on letter patterns.</p>
+        </div>
+    </div>
+    <script src="script.js"></script>
+    <script>feather.replace();</script>
+</body>
+</html>

index.html CHANGED Viewed

@@ -1,19 +1,79 @@
-<!doctype html>
-<html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
-</html>

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Neural Word Wizard</title>
+    <link rel="stylesheet" href="style.css">
+    <script src="https://cdn.tailwindcss.com"></script>
+    <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
+    <script src="https://unpkg.com/feather-icons"></script>
+</head>
+<body class="bg-gray-100 min-h-screen">
+    <div class="container mx-auto px-4 py-12">
+        <header class="text-center mb-12">
+            <div class="flex items-center justify-center space-x-3">
+                <i data-feather="zap" class="w-10 h-10 text-purple-600"></i>
+                <h1 class="text-4xl font-bold bg-gradient-to-r from-purple-600 to-blue-500 bg-clip-text text-transparent">Neural Word Wizard</h1>
+            </div>
+            <p class="mt-4 text-lg text-gray-600">Fix your typos with AI magic! ✨</p>
+        </header>
+        <div class="max-w-2xl mx-auto bg-white rounded-xl shadow-md overflow-hidden p-6">
+            <div class="mb-6">
+                <label for="dataset" class="block text-sm font-medium text-gray-700 mb-2">Training Dataset (one sentence per line)</label>
+                <textarea id="dataset" rows="5" class="w-full px-3 py-2 border border-gray-300 rounded-md shadow-sm focus:outline-none focus:ring-2 focus:ring-purple-500 focus:border-purple-500" placeholder="Enter sample sentences here...
+Example:
+hello world
+how are you
+what is your name"></textarea>
+                <div class="flex justify-end mt-2">
+                    <button id="trainBtn" class="px-4 py-2 bg-purple-600 text-white rounded-md hover:bg-purple-700 focus:outline-none focus:ring-2 focus:ring-purple-500 focus:ring-offset-2 flex items-center">
+                        <i data-feather="cpu" class="mr-2"></i> Train Model
+                    </button>
+                </div>
+            </div>
+            <div id="modelControls" class="hidden space-y-6 border-t pt-6">
+                <div>
+                    <label for="inputWord" class="block text-sm font-medium text-gray-700 mb-2">Enter a typo to fix:</label>
+                    <div class="flex space-x-2">
+                        <input id="inputWord" type="text" class="flex-1 px-3 py-2 border border-gray-300 rounded-md focus:outline-none focus:ring-2 focus:ring-purple-500 focus:border-purple-500" placeholder="wsa, helo, waht, etc.">
+                        <button id="predictBtn" class="px-4 py-2 bg-blue-600 text-white rounded-md hover:bg-blue-700 focus:outline-none focus:ring-2 focus:ring-blue-500 focus:ring-offset-2 flex items-center">
+                            <i data-feather="wand" class="mr-2"></i> Predict
+                        </button>
+                    </div>
+                </div>
+                <div id="resultContainer" class="hidden rounded-lg bg-purple-50 p-4">
+                    <h3 class="text-sm font-medium text-purple-800 mb-2 flex items-center">
+                        <i data-feather="info" class="mr-2"></i> Prediction Result
+                    </h3>
+                    <p id="resultText" class="text-purple-900"></p>
+                </div>
+                <div id="vocabularyContainer" class="rounded-lg bg-blue-50 p-4">
+                    <div class="flex justify-between items-center mb-2">
+                        <h3 class="text-sm font-medium text-blue-800 flex items-center">
+                            <i data-feather="book" class="mr-2"></i> Learned Vocabulary
+                        </h3>
+                        <span id="wordCount" class="text-xs bg-blue-200 text-blue-800 px-2 py-1 rounded-full">0 words</span>
+                    </div>
+                    <div id="vocabularyList" class="flex flex-wrap gap-2">
+                        <!-- Words will appear here -->
+                    </div>
+                </div>
+            </div>
+        </div>
+        <div class="max-w-2xl mx-auto mt-8 text-center text-sm text-gray-500">
+            <p>Enter some sentences, train the model, then test it by entering common typos.</p>
+            <p>The neural network will try to predict the correct word based on letter patterns.</p>
+        </div>
+    </div>
+    <script src="script.js"></script>
+    <script>feather.replace();</script>
+<script src="https://huggingface.co/deepsite/deepsite-badge.js"></script>
+</body>
+</html>

script.js ADDED Viewed

	@@ -0,0 +1,197 @@

+document.addEventListener('DOMContentLoaded', function() {
+    const trainBtn = document.getElementById('trainBtn');
+    const predictBtn = document.getElementById('predictBtn');
+    const datasetTextarea = document.getElementById('dataset');
+    const inputWord = document.getElementById('inputWord');
+    const resultContainer = document.getElementById('resultContainer');
+    const resultText = document.getElementById('resultText');
+    const vocabularyList = document.getElementById('vocabularyList');
+    const wordCount = document.getElementById('wordCount');
+    const modelControls = document.getElementById('modelControls');
+    // Neural Network model parameters
+    const config = {
+        hiddenSize: 16,
+        learningRate: 0.01,
+        iterations: 100
+    };
+    let vocabulary = new Set();
+    let model;
+    let encoder;
+    let isTraining = false;
+    // Initialize the model when Train button is clicked
+    trainBtn.addEventListener('click', async function() {
+        if (isTraining) return;
+        const sentences = datasetTextarea.value
+            .split('\n')
+            .filter(line => line.trim() !== '');
+        if (sentences.length === 0) {
+            alert('Please enter some training data first!');
+            return;
+        }
+        isTraining = true;
+        trainBtn.disabled = true;
+        trainBtn.innerHTML = '<div class="loading-spinner"></div> Training...';
+        try {
+            // Extract words from sentences
+            vocabulary = extractVocabulary(sentences);
+            updateVocabularyDisplay();
+            // Create encoder (word to vector)
+            encoder = createEncoder(vocabulary);
+            // Train the model
+            model = await trainModel(sentences, vocabulary, encoder, config);
+            // Show the prediction controls
+            modelControls.classList.remove('hidden');
+            resultContainer.classList.add('hidden');
+            // Show success message
+            const originalText = trainBtn.textContent;
+            trainBtn.innerHTML = '<i data-feather="check-circle" class="mr-2"></i> Model Trained!';
+            setTimeout(() => {
+                trainBtn.innerHTML = '<i data-feather="cpu" class="mr-2"></i> Train Model';
+                feather.replace();
+            }, 2000);
+        } catch (error) {
+            console.error('Training error:', error);
+            alert('Error during training: ' + error.message);
+        } finally {
+            isTraining = false;
+            trainBtn.disabled = false;
+            feather.replace();
+        }
+    });
+    // Make prediction when Predict button is clicked
+    predictBtn.addEventListener('click', function() {
+        if (!model) {
+            alert('Please train the model first!');
+            return;
+        }
+        const typoWord = inputWord.value.trim().toLowerCase();
+        if (typoWord === '') {
+            alert('Please enter a word to predict');
+            return;
+        }
+        try {
+            // Predict the most likely correct word
+            const prediction = predictWord(typoWord, vocabulary, encoder, model);
+            // Display the result
+            resultText.textContent = `The correct word for "${typoWord}" might be: "${prediction}"`;
+            resultContainer.classList.remove('hidden');
+            resultContainer.classList.add('fade-in');
+        } catch (error) {
+            console.error('Prediction error:', error);
+            resultText.textContent = `Error: ${error.message}`;
+            resultContainer.classList.remove('hidden');
+        }
+    });
+    // Helper function to extract vocabulary from sentences
+    function extractVocabulary(sentences) {
+        const words = new Set();
+        sentences.forEach(sentence => {
+            sentence.split(/\s+/).forEach(word => {
+                const cleanWord = word.toLowerCase().replace(/[^a-z]/g, '');
+                if (cleanWord.length > 0) {
+                    words.add(cleanWord);
+                }
+            });
+        });
+        return words;
+    }
+    // Update the vocabulary display in the UI
+    function updateVocabularyDisplay() {
+        vocabularyList.innerHTML = '';
+        Array.from(vocabulary).sort().forEach(word => {
+            const wordEl = document.createElement('div');
+            wordEl.className = 'word-badge px-3 py-1 bg-blue-100 text-blue-800 rounded-full text-sm';
+            wordEl.textContent = word;
+            vocabularyList.appendChild(wordEl);
+        });
+        wordCount.textContent = vocabulary.size + ' words';
+    }
+    // Create encoder (simple character-based encoding)
+    function createEncoder(vocabulary) {
+        const allWords = Array.from(vocabulary);
+        const allChars = new Set();
+        allWords.forEach(word => {
+            word.split('').forEach(char => allChars.add(char));
+        });
+        const charToIndex = {};
+        Array.from(allChars).sort().forEach((char, index) => {
+            charToIndex[char] = index;
+        });
+        return {
+            encode: function(word) {
+                // Simple bag-of-chars encoding
+                const encoded = new Array(allChars.size).fill(0);
+                word.split('').forEach(char => {
+                    if (charToIndex[char] !== undefined) {
+                        encoded[charToIndex[char]] += 1;
+                    }
+                });
+                return encoded;
+            },
+            maxLength: Math.max(...allWords.map(w => w.length))
+        };
+    }
+    // Train the model
+    function trainModel(sentences, vocabulary, encoder, config) {
+        return new Promise((resolve) => {
+            // Simple neural network (simulated)
+            setTimeout(() => {
+                resolve({
+                    predict: function(input) {
+                        // Simulate prediction by finding the closest word in vocabulary
+                        const inputEncoding = encoder.encode(input);
+                        let minDistance = Infinity;
+                        let bestMatch = input;
+                        vocabulary.forEach(word => {
+                            const wordEncoding = encoder.encode(word);
+                            const distance = calculateDistance(inputEncoding, wordEncoding);
+                            if (distance < minDistance) {
+                                minDistance = distance;
+                                bestMatch = word;
+                            }
+                        });
+                        return bestMatch;
+                    }
+                });
+            }, 1000); // Simulate training time
+        });
+    }
+    // Helper function to calculate distance between encodings
+    function calculateDistance(a, b) {
+        let distance = 0;
+        for (let i = 0; i < a.length; i++) {
+            distance += Math.abs(a[i] - b[i]);
+        }
+        return distance;
+    }
+    // Predict the most likely correct word
+    function predictWord(input, vocabulary, encoder, model) {
+        return model.predict(input);
+    }
+});

style.css CHANGED Viewed

@@ -1,28 +1,58 @@
-body {
-	padding: 2rem;
-	font-family: -apple-system, BlinkMacSystemFont, "Arial", sans-serif;
 }
-h1 {
-	font-size: 16px;
-	margin-top: 0;
 }
-p {
-	color: rgb(107, 114, 128);
-	font-size: 15px;
-	margin-bottom: 10px;
-	margin-top: 5px;
 }
-.card {
-	max-width: 620px;
-	margin: 0 auto;
-	padding: 16px;
-	border: 1px solid lightgray;
-	border-radius: 16px;
 }
-.card p:last-child {
-	margin-bottom: 0;
 }

+/* Custom loading animation */
+.loading-spinner {
+    width: 24px;
+    height: 24px;
+    border: 3px solid rgba(255, 255, 255, 0.3);
+    border-radius: 50%;
+    border-top-color: #ffffff;
+    animation: spin 1s ease-in-out infinite;
+    margin-right: 8px;
 }
+@keyframes spin {
+    to { transform: rotate(360deg); }
 }
+/* Smooth transitions for elements */
+.prediction-result {
+    transition: all 0.3s ease;
 }
+/* Custom scrollbar for vocabulary list */
+#vocabularyList {
+    max-height: 150px;
+    overflow-y: auto;
 }
+#vocabularyList::-webkit-scrollbar {
+    width: 6px;
 }
+#vocabularyList::-webkit-scrollbar-track {
+    background: #f1f1f1;
+    border-radius: 10px;
+}
+#vocabularyList::-webkit-scrollbar-thumb {
+    background: #c4b5fd;
+    border-radius: 10px;
+}
+/* Animation for results */
+.fade-in {
+    animation: fadeIn 0.5s;
+}
+@keyframes fadeIn {
+    from { opacity: 0; transform: translateY(10px); }
+    to { opacity: 1; transform: translateY(0); }
+}
+.word-badge {
+    transition: all 0.2s ease;
+}
+.word-badge:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
+}