RaymondVerhoef 66e0c275da
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feat: phase 4 of AI pipeline hardening — quiz & content quality
- src/lib/random.js: Fisher–Yates shuffle/sample/pickInt; replace every
  biased .sort(() => 0.5 - Math.random()) site in testService.
- testService: debias correctIndex via prompt + runtime re-roll (up to 2x
  when one position holds >50%); quality gate rejecting <4 distinct
  options, banned filler ("all of the above" etc) and explanations
  shorter than 20 chars; dedup new questions against the existing bank
  via normalised question text.
- Quiz schema/tool/prompt require difficulty ('easy'|'medium'|'hard');
  db.getQuizBank defaults legacy records to 'medium' on read.
- learningService.generateCustomTopic: kebab-case slug ID from the
  polished label with collision suffixes; default learning_relevance
  'standard' when the model omits it.
- Tests for random helpers, dedup/quality-gate behaviour and the
  extended quiz schema.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-20 19:22:10 +02:00

Respellion Learning Platform

An internal AI-powered learning platform that keeps Respellion employees up to date with the company's evolving knowledge base.

Features

  • Weekly Learning Station — Each employee is assigned a topic each week (via deterministic hash of user ID + week number). They choose their preferred format: Article, Slides, or Infographic. Content is generated on-demand by Claude and cached per topic.
  • Weekly Test — AI-generated quiz based on the knowledge graph. Results are stored and feed the leaderboard.
  • Leaderboard & Gamification — Points for correct answers, badges for streaks and perfect scores.
  • R42 Chatbot — An always-available AI assistant (backed by Claude) with access to the full knowledge graph. Can propose graph updates that admins approve or reject.
  • Admin Panel — Manage the knowledge graph, sync from GitHub, review generated content, refine it with AI, and monitor team progress.

Tech Stack

Layer Technology
Frontend React 18 + Vite
Styling Vanilla CSS (custom properties) + Tailwind utility classes
Animations Framer Motion
Icons Lucide React
Graph viz D3.js (admin knowledge graph only)
Backend / DB PocketBase (self-hosted)
AI Anthropic Claude (via Caddy reverse proxy)
Infra Docker + Caddy

Getting Started (local dev)

# 1. Install dependencies
npm install

# 2. Start PocketBase (Windows)
./pocketbase.exe serve

# 3. Start the dev server
npm run dev

The Vite dev server proxies /api/anthropic and /pb — see vite.config.js.

Deployment (Docker)

docker compose up -d

The Caddyfile handles:

  • SPA fallback routing
  • /pb/* → PocketBase sidecar
  • /api/anthropic/* → Anthropic API (with server-side API key injection)

Key Files

File Purpose
src/lib/learningService.js Selective content generation (article / slides / infographic)
src/lib/extractionPipeline.js GitHub file → knowledge graph extraction
src/lib/api.js Anthropic API wrapper (generateContent + chat)
src/lib/db.js All PocketBase data access
src/lib/giteaService.js GitHub API client (folder listing + raw file fetch)
src/store/AppContext.jsx Global state; computes ISO week number on load
src/components/admin/UploadZone.jsx GitHub sync UI (default folder: docs/knowledge-base/)
AI_AGENT.md Detailed context guide for AI coding agents

Content Types

Learning content is generated on demand per type and merged into the cached object:

Type Key in DB Description
Article content.article Long-form reading
Slides content.slides Slide deck with speaker notes
Infographic content.infographic Visual summary with stats and steps

The podcast type was removed. Do not re-add it.

Documentation

  • AI_AGENT.md — Full architectural guide for AI coding agents (patterns, gotchas, decisions).
  • CHANGELOG.md — PocketBase upstream changelog (not application changelog).
Description
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