- alembic.ini: remove hardcoded sqlite URL - alembic/env.py: inject DATABASE_URL from container env - main.py: serialize Base.metadata.create_all() + setup_pgvector() behind a Postgres advisory lock (_run_startup_ddl). Previously all 4 uvicorn workers ran the DDL in parallel and occasionally deadlocked each other on ALTER TABLE ordering, killing one worker at startup. - CLAUDE.md: add Database migrations (Alembic) section DB was stamped at 9bac7bf02e38; no schema changes in this commit.
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PedsHub — AI Synopsis for Codebase Work
What this is
PedsHub is a pediatric medical learning platform with an integrated LMS. Admins upload PREP exam PDFs, AI extracts MCQ questions (or generates flashcards), and users study them with an AI tutor. Any user can create courses, quizzes, and questions. Everything runs in Docker.
Critical rules
- Never restart services while a Celery task is running — check
docker compose logs celery --tail=5first - Backend and Celery share the same code but build separate images — after changing backend code, you must
docker compose build --no-cache backend celerythendocker compose up -d backend celery --force-recreate - Frontend is a Vite build inside Docker — source changes require
docker compose build frontendthendocker compose up -d frontend. Vite minifies function names, sogrep FunctionNameon the built JS won't work. - Never import inside a function body if the same name exists at module level — Python treats it as a local variable for the entire function scope, causing
UnboundLocalErrorbefore the import line executes. This was a real bug withsa_text. docker compose restartdoes NOT pick up code changes — it reuses the old image. Alwaysbuildthenup -d --force-recreate.- Pydantic schemas must match DB nullability — if a column allows NULL, the schema field must be
type | None. A mismatch causes 500 on serialization. - The Question model uses
source_quiz_idas the Python attribute butquiz_idas the DB column — useQuestion.source_quiz_idin SQLAlchemy filters, neverQuestion.quiz_id.
Stack
- Backend: FastAPI + SQLAlchemy + PostgreSQL 16 (pgvector) + Redis + Celery
- Frontend: React 18 + Vite + React Router 6 + plain CSS + Milkdown (markdown WYSIWYG) + Nginx
- AI: LiteLLM proxy routes to Claude/GPT/Gemini/Bedrock.
_proxy_model()in ai_service.py addsopenai/prefix for the proxy. - Vectors: ChromaDB for document page chunks (RAG), pgvector for question embeddings (semantic search)
- Config: Backend reads
.envvia pydantic-settings. Frontend uses runtimewindow.__APP_CONFIG__injected bydocker-entrypoint.sh(not Vite build-time env).
Architecture
Browser → Nginx (frontend) → FastAPI (4 uvicorn workers)
├── PostgreSQL (users, quizzes, questions, flashcards, attempts + pgvector embeddings)
├── ChromaDB (document page chunks for extraction context)
├── Redis (Celery broker, rate limits, settings, job progress, session locks)
└── Celery (2 fork workers: PDF processing, quiz extraction, flashcard generation, classification, embedding regeneration)
└── db-backup (daily PostgreSQL dumps, 14 daily / 4 weekly / 6 monthly retention, ./backups/)
## Course/LMS system
Any user can create courses (not just moderators). Course structure: Course → Modules → Lessons.
- **Lesson types**: text (markdown), video (Vimeo/YouTube/local), document, quiz (from question bank), live_session (BBB/Zoom/Meet)
- **Enrollment**: users enroll in published courses, progress tracked per-lesson
- **Video**: auto-detect provider from URL (vimeo.com → vimeo, youtube.com → youtube)
- **BBB**: full API integration (create/join/end). Config: `BBB_SERVER_URL` + `BBB_SECRET` in .env
- **AI**: generate/refine lesson text via `POST /courses/{id}/lessons/{id}/ai-generate`
- **Status**: draft (creator-only) → published (visible to all) → archived
- **Subscription gate**: `requires_subscription` flag on courses (402 on enroll if set — Stripe integration placeholder)
- **Course quizzes**: fully decoupled from main quiz system. `POST /courses/{id}/quiz` copies questions and creates an independent quiz with `course_id` set. Hidden from main quizzes page, search, dashboard stats, and attempt history. Creator sets mode (timed/study), time limit, max attempts, questions per attempt (random pool), and `allow_review` (whether students can review answers). Results page is course-aware — shows "Back to Course" instead of retake/all quizzes/delete. Users see attempt history + review links on the course page only.
- **User roles**: `admin`, `moderator`, `user`. Only moderators and admins can create courses. Any user can create quizzes from the question bank.
- **Enrollee analytics**: `GET /courses/{id}/enrollees` returns progress + quiz scores. `GET /courses/{id}/enrollees/export` exports CSV.
- **Question ownership**: questions have `user_id` and `is_shared`. Users see shared + own questions. `PATCH /questions/{id}/share` toggles visibility.
- **Rich editor**: Milkdown (ProseMirror-based markdown WYSIWYG) for lesson content. Supports GFM tables, code blocks, LaTeX math (`$formula$`). No JSX parsing issues with `<` or `{`.
Key directories
backend/app/
main.py — App startup, DDL migrations (setup_pgvector), router mounting, singleton lock
config.py — All settings from .env
models/ — SQLAlchemy ORM (user, quiz, question, flashcard, attempt, section, pdf_document, ...)
schemas/ — Pydantic request/response models
routers/ — API endpoints (auth, quizzes, questions, flashcards, attempts, admin, teach, tts, tags, ...)
services/
ai_service.py — LLM calls, _proxy_model(), get_model_for_task() fallback chain
extraction_modes.py — 6 quiz extraction modes + flashcard generation prompt
vector_service.py — ChromaDB: store/query page chunks, LiteLLMEmbeddingFunction
embedding_service.py — pgvector: embed questions for semantic search
pdf_service.py — PyMuPDF: text extraction, image extraction with MD5 hash skip list
tasks/
quiz_tasks.py — Celery: extract_quiz, classify_questions, regenerate_embeddings, generate_flashcard_deck
pdf_tasks.py — Celery: process_pdf (text extraction + vectorization)
frontend/src/
App.jsx — Routes (public, authenticated, moderator-only)
context/AuthContext.jsx — Login/logout/register, JWT token management
pages/
DocumentDetailPage.jsx — Section management, "Extract Quiz" / "Create Flashcards" buttons, job progress
QuestionBankPage.jsx — Browse questions, multi-category + tag filtering, TagBrowser component
FlashcardsPage.jsx — Browse decks + card browser with search
FlashcardStudyPage.jsx — Flip cards, got-it/review, keyboard nav, progress
QuizPage.jsx — Take quiz (exam/study mode), timer, progress save to Redis
CoursesPage.jsx — Browse/enroll courses, my courses, create courses
CourseDetailPage.jsx — Student view: modules, lessons, video player, progress
CourseEditorPage.jsx — Course creator: modules, lessons, AI content, question bank browser
AdminPage.jsx — Model config, user management, settings
components/
Navbar.jsx — Auth-aware nav with jobs badge
TeachChat.jsx — AI tutor drawer (lazy loaded, markdown/GFM tables)
RichEditor.jsx — Milkdown markdown WYSIWYG editor with toolbar, GFM tables, math, history
Database tables (key ones)
| Table | Purpose | Key FKs |
|---|---|---|
| users | Accounts with role (admin/moderator/user) | — |
| pdf_documents | Uploaded PDFs | user_id → users |
| sections | Page ranges within a document | document_id → pdf_documents |
| quizzes | Quiz metadata (course_id set = course-only, allow_review controls student access) | section_id → sections (nullable), user_id → users, course_id → courses (nullable) |
| questions | MCQ questions with pgvector embedding | source_quiz_id → quizzes (nullable), user_id → users (nullable) |
| quiz_question_links | Quiz ↔ Question many-to-many | quiz_id, question_id |
| flashcard_decks | Flashcard deck metadata | section_id → sections, user_id → users |
| flashcards | Individual cards (front/back) | deck_id → flashcard_decks |
| question_tags | Tag definitions (subject/disease/keyword) | — |
| question_tag_links | Question ↔ Tag | question_id, tag_id |
| flashcard_tag_links | Flashcard ↔ Tag | flashcard_id, tag_id |
| quiz_attempts | User quiz sessions with score | quiz_id, user_id |
| courses | LMS courses (draft/published/archived) | user_id → users |
| course_modules | Sections within a course | course_id → courses |
| course_lessons | Items within a module (text/video/quiz/live) | module_id → course_modules, quiz_id → quizzes |
| course_enrollments | User enrollment + progress tracking | course_id, user_id (unique) |
| course_lesson_progress | Per-lesson completion status | enrollment_id, lesson_id (unique) |
Common patterns
- Tag filtering SQL:
WHERE tag_id = ANY(:tag_ids) GROUP BY ... HAVING COUNT(DISTINCT tag_id) = :cnt— AND logic across tags - Multi-category filtering:
category_idsparam (comma-separated), uses.in_()— OR logic within categories - Job progress: Celery tasks push steps to Redis lists (
extraction:steps:{job_id}), frontend pollsGET /quizzes/job/{job_id} - Model selection: Admin configures models per task (extraction, teach, tts, keyword, flashcard).
get_model_for_task(db, task)returns (model_id, api_key) with fallback tosettings.LITELLM_MODEL. - useEffect dependencies: Use
.join(',')on arrays to create a stable string key (e.g.,tagIdsKey,catIdsKey) - Admin page data refresh:
loadData(false)— thefalseparam skips the loading spinner on re-fetch after actions
Database migrations (Alembic)
What's a migration? A migration is a small, ordered change to the database schema — adding a column, renaming a table, changing a type. Each change lives in a Python file under backend/alembic/versions/. Alembic tracks which ones have been applied in an alembic_version table inside Postgres, so it knows what's new next time you run it.
Why it exists here: until now, schema was created via Base.metadata.create_all() in main.py:478, which only creates missing tables — it never alters existing ones. Every column change required manual ALTER TABLE. Alembic makes schema changes versioned, reversible, and reproducible across environments.
Current setup
alembic.inicontains no hardcoded URL;alembic/env.pyinjectsDATABASE_URLfrom the container's env.- Live DB is stamped at revision
9bac7bf02e38(the latest inalembic/versions/). Base.metadata.create_all()remains in place as a fallback for fresh deploys — don't remove it without first generating a complete baseline migration from the live schema.
Developer workflow
# where am I?
docker compose exec backend alembic current
docker compose exec backend alembic heads
# create a new migration (auto-diff model vs live DB)
docker compose exec backend alembic revision --autogenerate -m "add some column"
# ↑ review the generated file under backend/alembic/versions/ before applying
# apply pending migrations
docker compose exec backend alembic upgrade head
# roll back the last one
docker compose exec backend alembic downgrade -1
When to write one — any schema change: new column, dropped column, renamed field, new table, altered index, new FK. Model edit → migration → apply → commit both together.
Gotchas
- Migrations run as a normal transaction. A failed migration rolls back cleanly.
--autogeneratedoesn't catch: server_default changes, CHECK constraints, enum value additions, data migrations. Hand-edit the file when needed.- After applying a new migration in dev, rebuild the backend image (
docker compose build backend celery) so it ships with the migration file baked in. - The
alembic_versiontable should only ever have one row. If you see multiple, you have branched heads — runalembic mergeto reconcile.
What NOT to do
- Don't add
from sqlalchemy import text as Xinside functions — import at module top only - Don't use
Question.quiz_id— it'sQuestion.source_quiz_id - Don't set
Content-Type: multipart/form-datamanually on axios FormData uploads — axios handles it - Don't use
[someValue === null]as a useEffect dependency — it evaluates to a constant boolean - Don't
docker compose restartexpecting code changes to apply — must rebuild - Don't use
window.confirm()— user hates browser popups, use inline confirmation or the Dialog component - Don't use MDXEditor — it's an MDX parser that chokes on
<and{in medical content. Milkdown (CommonMark) is used instead. - Don't create quizzes via
POST /questions/from-bankfor courses — usePOST /courses/{id}/quizwhich copies questions and hides the quiz from the main page. - Don't show course quiz data on the main quizzes page, dashboard stats, or attempt history — course quizzes are fully decoupled. Filter with
Quiz.course_id.is_(None). - Don't show "from pool of N" to users on course quiz display — just show the number of questions per attempt.
- Don't allow users to delete course quiz attempts — the backend returns 403.
- Don't put documents listing on the dashboard — it's in Settings page under Nextcloud.