Delete omnimind-ai.js

omnimind-ai.js

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-/**
- * OmniMind AI Simulator
- *
- * A JavaScript-based AI assistant that uses the OmniMind-100K dataset
- * to answer questions on coding, science, math, image generation,
- * general knowledge, and more.
- *
- * Usage: node omnimind-ai.js
- */
-
-const fs = require('fs');
-const readline = require('readline');
-
-// ============================================
-// CONFIGURATION
-// ============================================
-
-const CONFIG = {
-  datasetPath: './omnimind-100k.jsonl',
-  indexPath: './omnimind-index.json',
-  similarityThreshold: 0.3,
-  maxResults: 5,
-  modelName: 'OmniMind-100K',
-  version: '1.0.0'
-};
-
-// ============================================
-// TEXT PROCESSING UTILITIES
-// ============================================
-
-class TextProcessor {
-  static stopWords = new Set([
-    'a', 'an', 'the', 'is', 'are', 'was', 'were', 'be', 'been', 'being',
-    'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would', 'could',
-    'should', 'may', 'might', 'must', 'shall', 'can', 'need', 'dare',
-    'ought', 'used', 'to', 'of', 'in', 'for', 'on', 'with', 'at', 'by',
-    'from', 'as', 'into', 'through', 'during', 'before', 'after', 'above',
-    'below', 'between', 'under', 'again', 'further', 'then', 'once', 'here',
-    'there', 'when', 'where', 'why', 'how', 'all', 'each', 'few', 'more',
-    'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own',
-    'same', 'so', 'than', 'too', 'very', 'just', 'and', 'but', 'if', 'or',
-    'because', 'until', 'while', 'this', 'that', 'these', 'those', 'what',
-    'which', 'who', 'whom', 'it', 'its', 'i', 'me', 'my', 'myself', 'we',
-    'our', 'you', 'your', 'he', 'him', 'his', 'she', 'her', 'they', 'them'
-  ]);
-
-  static tokenize(text) {
-    return text
-      .toLowerCase()
-      .replace(/[^\w\s]/g, ' ')
-      .split(/\s+/)
-      .filter(word => word.length > 1 && !this.stopWords.has(word));
-  }
-
-  static extractKeywords(text) {
-    const tokens = this.tokenize(text);
-    const frequency = {};
-
-    tokens.forEach(token => {
-      frequency[token] = (frequency[token] || 0) + 1;
-    });
-
-    return Object.entries(frequency)
-      .sort((a, b) => b[1] - a[1])
-      .slice(0, 10)
-      .map(([word]) => word);
-  }
-
-  static calculateSimilarity(text1, text2) {
-    const tokens1 = new Set(this.tokenize(text1));
-    const tokens2 = new Set(this.tokenize(text2));
-
-    if (tokens1.size === 0 || tokens2.size === 0) return 0;
-
-    const intersection = new Set([...tokens1].filter(x => tokens2.has(x)));
-    const union = new Set([...tokens1, ...tokens2]);
-
-    // Jaccard similarity
-    const jaccard = intersection.size / union.size;
-
-    // Boost for exact keyword matches
-    const keywordBoost = intersection.size / Math.min(tokens1.size, tokens2.size);
-
-    return (jaccard + keywordBoost) / 2;
-  }
-
-  static fuzzyMatch(query, text) {
-    const queryLower = query.toLowerCase();
-    const textLower = text.toLowerCase();
-
-    // Direct substring match
-    if (textLower.includes(queryLower)) return 1.0;
-
-    // Check individual words
-    const queryWords = queryLower.split(/\s+/);
-    const matchCount = queryWords.filter(word => textLower.includes(word)).length;
-
-    return matchCount / queryWords.length;
-  }
-}
-
-// ============================================
-// KNOWLEDGE BASE
-// ============================================
-
-class KnowledgeBase {
-  constructor() {
-    this.entries = [];
-    this.index = {
-      byCategory: {},
-      bySubcategory: {},
-      byKeyword: {}
-    };
-    this.loaded = false;
-  }
-
-  async load() {
-    console.log('📚 Loading OmniMind knowledge base...');
-
-    // Check if dataset exists
-    if (!fs.existsSync(CONFIG.datasetPath)) {
-      console.log('⚠️  Dataset not found. Please run: node generate-dataset.js');
-      return false;
-    }
-
-    // Check for cached index
-    if (fs.existsSync(CONFIG.indexPath)) {
-      console.log('📑 Loading cached index...');
-      const cached = JSON.parse(fs.readFileSync(CONFIG.indexPath, 'utf-8'));
-      this.entries = cached.entries;
-      this.index = cached.index;
-      this.loaded = true;
-      console.log(`✅ Loaded ${this.entries.length.toLocaleString()} entries from cache`);
-      return true;
-    }
-
-    // Load and index the dataset
-    const data = fs.readFileSync(CONFIG.datasetPath, 'utf-8');
-    const lines = data.trim().split('\n');
-
-    let processed = 0;
-    const total = lines.length;
-
-    for (const line of lines) {
-      try {
-        const entry = JSON.parse(line);
-        this.addEntry(entry);
-        processed++;
-
-        if (processed % 10000 === 0) {
-          process.stdout.write(`\r   Processing: ${processed.toLocaleString()}/${total.toLocaleString()}`);
-        }
-      } catch (e) {
-        // Skip malformed entries
-      }
-    }
-
-    console.log(`\n✅ Loaded ${this.entries.length.toLocaleString()} entries`);
-
-    // Cache the index
-    console.log('💾 Caching index for faster loading...');
-    fs.writeFileSync(CONFIG.indexPath, JSON.stringify({
-      entries: this.entries,
-      index: this.index
-    }));
-
-    this.loaded = true;
-    return true;
-  }
-
-  addEntry(entry) {
-    const idx = this.entries.length;
-    this.entries.push(entry);
-
-    // Index by category
-    if (!this.index.byCategory[entry.category]) {
-      this.index.byCategory[entry.category] = [];
-    }
-    this.index.byCategory[entry.category].push(idx);
-
-    // Index by subcategory
-    if (entry.subcategory) {
-      if (!this.index.bySubcategory[entry.subcategory]) {
-        this.index.bySubcategory[entry.subcategory] = [];
-      }
-      this.index.bySubcategory[entry.subcategory].push(idx);
-    }
-
-    // Index by keywords
-    const keywords = TextProcessor.extractKeywords(entry.instruction);
-    keywords.forEach(keyword => {
-      if (!this.index.byKeyword[keyword]) {
-        this.index.byKeyword[keyword] = [];
-      }
-      this.index.byKeyword[keyword].push(idx);
-    });
-  }
-
-  search(query, options = {}) {
-    const { category, maxResults = CONFIG.maxResults } = options;
-
-    const keywords = TextProcessor.extractKeywords(query);
-    const candidateIndices = new Set();
-
-    // Find candidates by keywords
-    keywords.forEach(keyword => {
-      const indices = this.index.byKeyword[keyword] || [];
-      indices.forEach(idx => candidateIndices.add(idx));
-    });
-
-    // If category specified, filter by category
-    if (category && this.index.byCategory[category]) {
-      const categoryIndices = new Set(this.index.byCategory[category]);
-      candidateIndices.forEach(idx => {
-        if (!categoryIndices.has(idx)) {
-          candidateIndices.delete(idx);
-        }
-      });
-    }
-
-    // If no keyword matches, search all entries (limited)
-    if (candidateIndices.size === 0) {
-      const sampleSize = Math.min(5000, this.entries.length);
-      for (let i = 0; i < sampleSize; i++) {
-        candidateIndices.add(Math.floor(Math.random() * this.entries.length));
-      }
-    }
-
-    // Score candidates
-    const scored = [];
-    candidateIndices.forEach(idx => {
-      const entry = this.entries[idx];
-      const similarity = TextProcessor.calculateSimilarity(query, entry.instruction);
-      const fuzzy = TextProcessor.fuzzyMatch(query, entry.instruction);
-      const score = (similarity * 0.6) + (fuzzy * 0.4);
-
-      if (score > CONFIG.similarityThreshold) {
-        scored.push({ entry, score, idx });
-      }
-    });
-
-    // Sort by score and return top results
-    scored.sort((a, b) => b.score - a.score);
-    return scored.slice(0, maxResults);
-  }
-
-  getRandomEntry(category) {
-    let pool = this.entries;
-
-    if (category && this.index.byCategory[category]) {
-      const indices = this.index.byCategory[category];
-      pool = indices.map(idx => this.entries[idx]);
-    }
-
-    return pool[Math.floor(Math.random() * pool.length)];
-  }
-
-  getCategories() {
-    return Object.keys(this.index.byCategory);
-  }
-
-  getStats() {
-    const stats = {
-      total: this.entries.length,
-      categories: {}
-    };
-
-    Object.entries(this.index.byCategory).forEach(([cat, indices]) => {
-      stats.categories[cat] = indices.length;
-    });
-
-    return stats;
-  }
-}
-
-// ============================================
-// AI ASSISTANT
-// ============================================
-
-class OmniMindAI {
-  constructor() {
-    this.kb = new KnowledgeBase();
-    this.context = [];
-    this.maxContextLength = 5;
-  }
-
-  async initialize() {
-    const success = await this.kb.load();
-    if (!success) {
-      throw new Error('Failed to load knowledge base');
-    }
-    return this;
-  }
-
-  async respond(userInput) {
-    const input = userInput.trim();
-
-    // Handle special commands
-    if (input.startsWith('/')) {
-      return this.handleCommand(input);
-    }
-
-    // Handle greetings
-    if (this.isGreeting(input)) {
-      return this.getGreetingResponse();
-    }
-
-    // Handle farewells
-    if (this.isFarewell(input)) {
-      return this.getFarewellResponse();
-    }
-
-    // Handle thanks
-    if (this.isThanks(input)) {
-      return this.getThanksResponse();
-    }
-
-    // Detect intent and category
-    const intent = this.detectIntent(input);
-
-    // Search knowledge base
-    const results = this.kb.search(input, { category: intent.category });
-
-    if (results.length > 0) {
-      // Return best matching response
-      const best = results[0];
-      this.addToContext(input, best.entry.response);
-      return this.formatResponse(best.entry, best.score);
-    }
-
-    // Generate fallback response
-    return this.getFallbackResponse(input, intent);
-  }
-
-  handleCommand(input) {
-    const [command, ...args] = input.slice(1).split(' ');
-
-    switch (command.toLowerCase()) {
-      case 'help':
-        return this.getHelpMessage();
-
-      case 'stats':
-        return this.getStatsMessage();
-
-      case 'categories':
-        return this.getCategoriesMessage();
-
-      case 'random':
-        const category = args[0];
-        const entry = this.kb.getRandomEntry(category);
-        return `**Random Knowledge:**\n\n**Q:** ${entry.instruction}\n\n**A:** ${entry.response}`;
-
-      case 'clear':
-        this.context = [];
-        return 'Context cleared. Starting fresh conversation.';
-
-      case 'about':
-        return this.getAboutMessage();
-
-      default:
-        return `Unknown command: /${command}\nType /help for available commands.`;
-    }
-  }
-
-  detectIntent(input) {
-    const inputLower = input.toLowerCase();
-
-    // Coding indicators
-    if (/\b(code|program|function|class|javascript|python|java|typescript|bug|debug|algorithm|api|database|sql|html|css|react|node|git)\b/i.test(input)) {
-      return { category: 'coding', confidence: 0.8 };
-    }
-
-    // Math indicators
-    if (/\b(math|calculate|equation|formula|algebra|geometry|calculus|trigonometry|derivative|integral|solve|number|percent)\b/i.test(input)) {
-      return { category: 'math', confidence: 0.8 };
-    }
-
-    // Science indicators
-    if (/\b(science|physics|chemistry|biology|atom|molecule|cell|dna|gravity|energy|evolution|quantum|element)\b/i.test(input)) {
-      return { category: 'science', confidence: 0.8 };
-    }
-
-    // Image generation indicators
-    if (/\b(image|picture|photo|draw|paint|art|generate|create|design|style|visual|render|illustration)\b/i.test(input)) {
-      return { category: 'image_generation', confidence: 0.8 };
-    }
-
-    // Reasoning indicators
-    if (/\b(puzzle|logic|riddle|think|reason|solve|problem|brain teaser|sequence|pattern)\b/i.test(input)) {
-      return { category: 'reasoning', confidence: 0.7 };
-    }
-
-    // Advice indicators
-    if (/\b(advice|recommend|suggest|should i|how can i|tips|help me|improve|better)\b/i.test(input)) {
-      return { category: 'advice', confidence: 0.6 };
-    }
-
-    // General question indicators
-    if (/^(what|who|where|when|why|how|which|is|are|can|do|does)/i.test(input)) {
-      return { category: 'question_answering', confidence: 0.5 };
-    }
-
-    return { category: null, confidence: 0 };
-  }
-
-  isGreeting(input) {
-    return /^(hi|hello|hey|greetings|good morning|good afternoon|good evening|howdy|what's up|sup)\b/i.test(input);
-  }
-
-  isFarewell(input) {
-    return /^(bye|goodbye|see you|farewell|take care|later|cya|gtg)\b/i.test(input);
-  }
-
-  isThanks(input) {
-    return /^(thanks|thank you|thx|appreciate|grateful)\b/i.test(input);
-  }
-
-  getGreetingResponse() {
-    const responses = [
-      "Hello! I'm OmniMind, your AI assistant. I can help you with coding, math, science, image generation prompts, and much more. What would you like to know?",
-      "Hi there! Welcome to OmniMind. I'm trained on 100,000 examples covering various topics. How can I assist you today?",
-      "Hey! Great to see you. I'm here to help with questions, explanations, coding, creative tasks, and more. What's on your mind?",
-      "Greetings! I'm OmniMind AI - ask me anything about programming, science, math, or get creative prompts. What can I do for you?"
-    ];
-    return responses[Math.floor(Math.random() * responses.length)];
-  }
-
-  getFarewellResponse() {
-    const responses = [
-      "Goodbye! It was great chatting with you. Come back anytime you have questions!",
-      "See you later! Feel free to return whenever you need help.",
-      "Take care! I'll be here if you need any assistance in the future.",
-      "Farewell! Thanks for using OmniMind. Have a great day!"
-    ];
-    return responses[Math.floor(Math.random() * responses.length)];
-  }
-
-  getThanksResponse() {
-    const responses = [
-      "You're welcome! I'm happy I could help. Is there anything else you'd like to know?",
-      "My pleasure! Feel free to ask if you have more questions.",
-      "Glad I could assist! Don't hesitate to ask about anything else.",
-      "Anytime! That's what I'm here for. What else can I help with?"
-    ];
-    return responses[Math.floor(Math.random() * responses.length)];
-  }
-
-  getFallbackResponse(input, intent) {
-    const category = intent.category ? ` about ${intent.category}` : '';
-
-    const responses = [
-      `I don't have a specific answer for that question${category}, but I can try to help! Could you rephrase your question or provide more details?`,
-      `Interesting question! While I may not have an exact match in my knowledge base, I'd be happy to help explore this topic. Can you tell me more about what you're looking for?`,
-      `I'm not sure I have the perfect answer for this, but let me suggest some related topics:\n- Try asking about specific programming languages\n- Ask about math formulas or scientific concepts\n- Request image generation prompts\n- Explore reasoning puzzles\n\nWhat interests you most?`
-    ];
-
-    return responses[Math.floor(Math.random() * responses.length)];
-  }
-
-  formatResponse(entry, score) {
-    let response = entry.response;
-
-    // Add category context if relevant
-    if (score < 0.7) {
-      response = `Based on my knowledge about **${entry.category.replace('_', ' ')}**:\n\n${response}`;
-    }
-
-    return response;
-  }
-
-  addToContext(userInput, response) {
-    this.context.push({ user: userInput, assistant: response });
-    if (this.context.length > this.maxContextLength) {
-      this.context.shift();
-    }
-  }
-
-  getHelpMessage() {
-    return `
-**OmniMind AI Help**
-
-I can assist you with many topics including:
-• **Coding** - Programming questions, algorithms, code examples
-• **Math** - Formulas, calculations, problem solving
-• **Science** - Physics, chemistry, biology, astronomy
-• **Image Generation** - Create detailed prompts for AI art
-• **General Knowledge** - History, geography, facts
-• **Reasoning** - Logic puzzles, brain teasers
-• **Advice** - Productivity, health, learning tips
-
-**Commands:**
-• /help - Show this help message
-• /stats - Show knowledge base statistics
-• /categories - List all categories
-• /random [category] - Get random knowledge
-• /about - About OmniMind
-• /clear - Clear conversation context
-
-Just ask me anything!
-`;
-  }
-
-  getStatsMessage() {
-    const stats = this.kb.getStats();
-    let message = `**OmniMind Knowledge Base Statistics**\n\nTotal entries: ${stats.total.toLocaleString()}\n\n**By Category:**\n`;
-
-    Object.entries(stats.categories)
-      .sort((a, b) => b[1] - a[1])
-      .forEach(([cat, count]) => {
-        const pct = ((count / stats.total) * 100).toFixed(1);
-        message += `• ${cat.replace('_', ' ')}: ${count.toLocaleString()} (${pct}%)\n`;
-      });
-
-    return message;
-  }
-
-  getCategoriesMessage() {
-    const categories = this.kb.getCategories();
-    return `**Available Categories:**\n\n${categories.map(c => `• ${c.replace('_', ' ')}`).join('\n')}\n\nYou can ask questions related to any of these topics!`;
-  }
-
-  getAboutMessage() {
-    return `
-**About OmniMind AI**
-
-Version: ${CONFIG.version}
-Model: ${CONFIG.modelName}
-
-OmniMind is a knowledge-based AI assistant trained on 100,000 high-quality examples covering:
-- Programming and Software Development
-- Mathematics and Problem Solving
-- Science (Physics, Chemistry, Biology, Astronomy)
-- Image Generation Prompts
-- General Knowledge and Trivia
-- Logical Reasoning and Puzzles
-- Practical Advice and Tips
-
-This is a demonstration of how dataset-driven AI can provide helpful, accurate responses across many domains.
-
-Created for educational and demonstration purposes.
-`;
-  }
-}
-
-// ============================================
-// INTERACTIVE CLI
-// ============================================
-
-async function startInteractiveSession() {
-  console.log('\n' + '='.repeat(60));
-  console.log('   🧠 OmniMind AI - 100K Knowledge Base Assistant');
-  console.log('='.repeat(60));
-  console.log('\nInitializing...\n');
-
-  const ai = new OmniMindAI();
-
-  try {
-    await ai.initialize();
-  } catch (error) {
-    console.error('Failed to initialize:', error.message);
-    process.exit(1);
-  }
-
-  console.log('\n✨ OmniMind is ready! Type your questions or /help for commands.');
-  console.log('   Type "exit" or "quit" to end the session.\n');
-  console.log('-'.repeat(60) + '\n');
-
-  const rl = readline.createInterface({
-    input: process.stdin,
-    output: process.stdout
-  });
-
-  const prompt = () => {
-    rl.question('\n🧑 You: ', async (input) => {
-      if (!input || input.trim() === '') {
-        prompt();
-        return;
-      }
-
-      const trimmed = input.trim().toLowerCase();
-      if (trimmed === 'exit' || trimmed === 'quit') {
-        console.log('\n👋 Goodbye! Thanks for using OmniMind AI.\n');
-        rl.close();
-        process.exit(0);
-      }
-
-      try {
-        const response = await ai.respond(input);
-        console.log('\n🤖 OmniMind:', response);
-      } catch (error) {
-        console.log('\n⚠️  Error:', error.message);
-      }
-
-      prompt();
-    });
-  };
-
-  prompt();
-}
-
-// ============================================
-// PROGRAMMATIC API
-// ============================================
-
-class OmniMindAPI {
-  constructor() {
-    this.ai = null;
-    this.initialized = false;
-  }
-
-  async init() {
-    if (this.initialized) return this;
-
-    this.ai = new OmniMindAI();
-    await this.ai.initialize();
-    this.initialized = true;
-    return this;
-  }
-
-  async ask(question) {
-    if (!this.initialized) {
-      await this.init();
-    }
-    return this.ai.respond(question);
-  }
-
-  async search(query, options) {
-    if (!this.initialized) {
-      await this.init();
-    }
-    return this.ai.kb.search(query, options);
-  }
-
-  getStats() {
-    if (!this.initialized) {
-      throw new Error('API not initialized. Call init() first.');
-    }
-    return this.ai.kb.getStats();
-  }
-}
-
-// ============================================
-// EXPORTS AND MAIN
-// ============================================
-
-// Export for programmatic use
-module.exports = { OmniMindAPI, OmniMindAI, KnowledgeBase, TextProcessor };
-
-// Run interactive session if executed directly
-if (require.main === module) {
-  startInteractiveSession();
-}