Freezmo: self-hosted notes-to-activities study app

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.

lib/deck-ops.ts

@@ -0,0 +1,18 @@
+"use client";
+
+import type { Activity, Difficulty, GeneratedActivity } from "./schemas";
+import { uid } from "./utils";
+import { xpForActivity } from "./xp";
+
+/** Turn freshly generated activities into stored ones (id + XP). */
+export function materialiseActivities(activities: GeneratedActivity[], difficulty: Difficulty): Activity[] {
+  return activities.map((activity) => ({
+    ...activity,
+    id: uid("act"),
+    xp: xpForActivity(activity.type, difficulty),
+  }));
+}
+
+export function activityTypes(activities: Activity[]): string[] {
+  return Array.from(new Set(activities.map((activity) => activity.type)));
+}