Martin Dvorak
3ea2cea100
Next.js 15 app that turns photos, PDFs, DOCX/PPTX and text into a swipeable feed of AI-generated activities (flashcards, multiple choice, true/false, fill-in-the-blank, matching, ordering, short answer) using the user's own Ollama models. Highlights: - All AI calls run in server route handlers; the browser never talks to Ollama. - Bring-your-own-key mode (default): the key lives only in the browser and is sent per-request; server, local-daemon and shared-key modes also supported. - Client-side document extraction (pdf.js, mammoth, jszip) with scanned-PDF page rendering for the vision model; notes stay in their original language. - ChatGPT-style shell: collapsible sidebar / mobile drawer, neutral token-based light + dark themes, folder organisation, PWA (manifest, SW, offline page). - Strict JSON validation with zod + auto-repair, rate limiting, and request guards (cross-origin, body-size, API-key sanitising). - setup.sh bootstraps deps, .env.local and a production build. Gitignore excludes .env*, the generated pdf.js worker and local scratch files.
26 lines
695 B
TypeScript
26 lines
695 B
TypeScript
import type { Difficulty } from "./schemas";
|
|
|
|
/**
|
|
* Base XP for a correct answer. Harder decks are worth more, and the
|
|
* multi-part activity types get a small bonus.
|
|
*/
|
|
export const XP_BY_DIFFICULTY: Record<Difficulty, number> = {
|
|
easy: 10,
|
|
medium: 15,
|
|
hard: 20,
|
|
};
|
|
|
|
const TYPE_BONUS: Record<string, number> = {
|
|
matching: 5,
|
|
ordering: 5,
|
|
short_answer: 5,
|
|
};
|
|
|
|
export function xpForActivity(type: string, difficulty: Difficulty): number {
|
|
return XP_BY_DIFFICULTY[difficulty] + (TYPE_BONUS[type] ?? 0);
|
|
}
|
|
|
|
/** Consecutive-correct streak multiplier (capped at 3x). */
|
|
export function streakMultiplier(streak: number): number {
|
|
return Math.min(1 + Math.max(0, streak) * 0.1, 3);
|
|
}
|