AI Portfolio Assistant

1/**
2 * Intent Classification Engine
3 * Tier 1: Exact patterns → Tier 2: Rule scoring → Tier 3: Similarity
4 */
5
6export type Intent =
7    | 'greeting' | 'goodbye' | 'thanks'
8    | 'navigation' | 'pricing' | 'skills' | 'projects' 
9    | 'services' | 'about' | 'contact' | 'technical' | 'faq';
10
11// Tier 1: Instant pattern matching
12const exactPatterns: Record<string, RegExp[]> = {
13    greeting: [
14        /^(hi|hello|hey|yo|sup|greetings)/i,
15        /^good (morning|afternoon|evening)/i,
16    ],
17    navigation: [
18        /^(show|go to|navigate|take me|open) (projects|pricing|contact)/i,
19    ],
20};
21
22// Tier 2: Keyword-weighted scoring
23type IntentRule = {
24    keywords: string[];
25    weight: number; // 0-1 confidence
26};
27
28const intentRules: Record<Intent, IntentRule[]> = {
29    pricing: [
30        { keywords: ['cost', 'price', 'how much', 'budget', '$'], weight: 1.0 },
31        { keywords: ['afford', 'expensive', 'cheap'], weight: 0.7 },
32    ],
33    skills: [
34        { keywords: ['skill', 'tech stack', 'can you', 'experience with'], weight: 1.0 },
35        { keywords: ['python', 'react', 'nextjs', 'ai', 'ml'], weight: 0.6 },
36    ],
37    // ... 8 more intents
38};
39
40// Main classification function
41export function classifyIntent(query: string): ClassificationResult {
42    const normalized = normalizeQuery(query);
43    
44    // Tier 1: Check exact patterns first (fastest)
45    for (const [intent, patterns] of Object.entries(exactPatterns)) {
46        if (patterns.some(p => p.test(normalized))) {
47            return { 
48                intent: intent as Intent, 
49                confidence: 1.0,
50                suggestedAction: 'answer' 
51            };
52        }
53    }
54    
55    // Tier 2: Score by keyword rules
56    const scores = calculateIntentScores(normalized, intentRules);
57    const topIntent = Object.entries(scores)
58        .sort(([,a], [,b]) => b - a)[0];
59    
60    if (topIntent[1] > 0.5) {
61        return {
62            intent: topIntent[0] as Intent,
63            confidence: topIntent[1],
64            suggestedAction: topIntent[0] === 'navigation' ? 'navigate' : 'answer'
65        };
66    }
67    
68    // Tier 3: Semantic similarity (fallback)
69    return semanticMatch(normalized);
70}

1// Voice Activity Detection (VAD) configuration constants
2// Tuned for noise rejection while maintaining responsiveness
3
4const VAD_SPEECH_THRESHOLD = 0.015      // RMS amplitude above this = speech
5const VAD_SILENCE_TIMEOUT_MS = 600      // Stop after this much silence
6const VAD_NO_INPUT_TIMEOUT_MS = 8000    // Max recording duration
7const VAD_AUTO_RESTART_DELAY_MS = 600   // Pause before auto-restart
8
9// Usage in component
10function detectVoiceActivity(audioData: Float32Array): boolean {
11  // Calculate RMS (Root Mean Square) amplitude
12  const rms = Math.sqrt(
13    audioData.reduce((sum, val) => sum + val * val, 0) / audioData.length
14  );
15  
16  // Compare to threshold
17  return rms > VAD_SPEECH_THRESHOLD;
18}
19
20// Recording state machine
21useEffect(() => {
22  if (!isRecording) return;
23  
24  const checkVAD = setInterval(() => {
25    const hasVoiceInput = detectVoiceActivity(currentAudioBuffer);
26    
27    if (hasVoiceInput) {
28      lastSpeechTime.current = Date.now();
29    } else {
30      const silenceDuration = Date.now() - lastSpeechTime.current;
31      
32      if (silenceDuration > VAD_SILENCE_TIMEOUT_MS) {
33        stopRecording(); // Auto-stop on silence
34      }
35    }
36    
37    // Safety: Force stop after max duration
38    if (Date.now() - recordingStartTime.current > VAD_NO_INPUT_TIMEOUT_MS) {
39      stopRecording();
40    }
41  }, 100); // Check every 100ms
42  
43  return () => clearInterval(checkVAD);
44}, [isRecording]);