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- Sidebar: dynamic brand-accent colors, brainstorm section restyled - AI chat general: popup panel with expand/collapse, hides when contextual AI open - AI chat contextual: tabs reordered (Actions first), X close button, height fix - Settings: all tabs restyled, 6 new color presets (sage, terracotta, iron, etc.) - Global color cleanup: emerald/orange hardcoded → brand-accent dynamic - Brainstorm page: orange → brand-accent throughout - PageEntry animation component added to key pages - Floating AI button: bg-brand-accent instead of hardcoded black - i18n: all 15 locales updated with new AI/billing keys - Billing: freemium quota tracking, BYOK, stripe subscription scaffolding - Admin: integrated into new design - AGENTS.md + CLAUDE.md project rules added
77 lines
2.6 KiB
TypeScript
77 lines
2.6 KiB
TypeScript
import { Note, NoteAccessLog, NotePrediction } from '../types';
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/**
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* Simulates finding the dominant frequency in access logs for a specific note
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* returning the period in days.
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*/
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export function detectAccessCycle(logs: NoteAccessLog[]): number | null {
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if (logs.length < 5) return null;
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const accessDays = logs
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.map(log => new Date(log.accessedAt).getTime())
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.sort((a, b) => a - b);
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const intervals: number[] = [];
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for (let i = 1; i < accessDays.length; i++) {
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intervals.push((accessDays[i] - accessDays[i - 1]) / (1000 * 60 * 60 * 24));
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}
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// Simple heuristic: if intervals are consistently around a value, that's our cycle
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// We'll calculate the median interval
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const sortedIntervals = [...intervals].sort((a, b) => a - b);
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const median = sortedIntervals[Math.floor(sortedIntervals.length / 2)];
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// Check if enough intervals are close to median
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const withinThreshold = intervals.filter(v => Math.abs(v - median) < Math.max(2, median * 0.2));
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if (withinThreshold.length >= intervals.length * 0.6) {
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return median;
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}
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return null;
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}
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export function predictNextAccess(note: Note, logs: NoteAccessLog[]): NotePrediction | null {
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const cycleDays = detectAccessCycle(logs);
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if (!cycleDays) return null;
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const lastAccess = new Date(logs[logs.length - 1].accessedAt);
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const nextAccessDate = new Date(lastAccess.getTime() + cycleDays * 24 * 60 * 60 * 1000);
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const now = new Date();
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const daysUntilNext = (nextAccessDate.getTime() - now.getTime()) / (1000 * 60 * 60 * 24);
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// Only predict if it's coming up in the next 2 weeks
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if (daysUntilNext > 0 && daysUntilNext < 14) {
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return {
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noteId: note.id,
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predictedRelevanceDate: nextAccessDate.toISOString(),
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confidence: 0.7,
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reason: `Historical access pattern suggests a ${Math.round(cycleDays)}-day cycle.`,
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generatedAt: now.toISOString()
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};
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}
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return null;
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}
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export function getCoaccessedNotes(baseNoteId: string, logs: NoteAccessLog[], allNotes: Note[]): Note[] {
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const WINDOW_MS = 30 * 60 * 1000; // 30 minutes
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const baseNoteLogs = logs.filter(l => l.noteId === baseNoteId);
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const coaccessedIds = new Set<string>();
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baseNoteLogs.forEach(baseLog => {
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const baseTime = new Date(baseLog.accessedAt).getTime();
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logs.forEach(otherLog => {
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if (otherLog.noteId === baseNoteId) return;
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const otherTime = new Date(otherLog.accessedAt).getTime();
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if (Math.abs(baseTime - otherTime) < WINDOW_MS) {
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coaccessedIds.add(otherLog.noteId);
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}
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});
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});
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return allNotes.filter(n => coaccessedIds.has(n.id));
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}
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