Yamen Ahmad 096b042daf
Some checks failed
Deploy to Staging / Deploy backend + frontend to staging (push) Failing after 14s
feat(course-plan): RAG sources + multi-modal media + assignments + student view
Builds the §24 product on top of the LangGraph runtime from §22:

Phase A (Sources / RAG)
  - encoach.course.plan.source model (file | url | text)
  - SourceIndexer extracts PDF (pypdf), DOCX (python-docx), HTML, plain
    text and embeds chunks via the existing pgvector pipeline scoped to
    plan_id, so resources.search only returns the plan's own corpus
  - Endpoints: list/create/upload/reindex/delete + plan-scoped retrieval

Phase B (Deliverables)
  - services.deliverables.compute_deliverables walks the plan, derives
    {planned, generated, ready} per week from material + media state
  - GET /api/ai/course-plan/<id>/deliverables drives the new wizard
    preview step and the live progress strip on the detail page

Phase C (Multi-modal media)
  - encoach.course.plan.media model + MediaService:
    audio: AWS Polly (default) or ElevenLabs
    image: OpenAI DALL-E 3, capped per plan via system parameter
    video: local ffmpeg subprocess (image + audio -> MP4 1280x720)
  - Three new agent tools (media.synthesize_audio / generate_image /
    compose_video), wired into course_week_materials and a new
    course_media_director agent
  - Endpoints per material + week-level batch generator

Phase D (Assignments)
  - encoach.course.plan.assignment supports mode='batch' (op.batch) or
    mode='students' (res.users), with due_date + message + state
  - REST endpoints to list / create / delete assignments

Phase E (Student view)
  - /api/student/course-plans + /api/student/course-plans/<id>
    enforce visibility via assignment.expand_user_ids()
  - New /student/course-plans list + read-only drilldown rendering
    audio/image/video tiles from /web/content/<attachment_id>

Cross-cutting
  - encoach.ai.tool.category: + media (so the new tools register)
  - encoach.embedding gains a plan_id filter for plan-scoped RAG
  - Wizard adds Sources + Multimedia steps; AdminCoursePlanDetail
    rewritten with DeliverablesStrip + SourcesCard + AssignmentsCard +
    per-material MediaDrawer
  - ~280 new EN + AR i18n keys (full RTL coverage)
  - smoke_course_plan.py exercises every phase via odoo-bin shell;
    last run: PASS A/B/D/E + DALL-E 3 image (753 KB), Polly audio
    fails cleanly when AWS creds aren't configured (expected)

Documentation: §24 added to docs/PROJECT_SUMMARY.md with phase-by-phase
artefact list, endpoints, smoke test, ops notes, and gotchas.

Made-with: Cursor
2026-04-25 17:13:01 +04:00

EnCoach — Adaptive AI Learning Platform

EnCoach is a smart learning environment for individual and collaborative learning, fully integrated with AI and equipped with intelligent, professional-grade exercises, assessments, and e-exams.

This repository hosts the full stack:

  • Backend — Odoo 19 + ~30 encoach_* modules (Python 3.12, PostgreSQL 16)
  • Frontend — React 18 + Vite + TypeScript single-page app
  • AI layer — OpenAI + pgvector RAG, quality-gate validation, IELTS validator
  • Ops — Docker Compose, JWT auth with refresh tokens, Prometheus-compatible metrics, dynamic OpenAPI 3.0 spec

Canonical trees: backend/ (all server code) and frontend/ (all client code). The legacy new_project/ directory is deprecated — see new_project/DEPRECATED.md.


1. Quickstart

docker compose up -d
# Odoo:     http://localhost:8069
# Frontend: cd frontend && npm install && npm run dev  (http://localhost:8080)

Create a new Odoo database on first visit, then install the encoach_api module to pull in every encoach_* dependency.

Source

Prerequisites: Python 3.12, PostgreSQL 16, Node 20, npm 10.

# Backend
./setup.sh          # creates venv, installs requirements.txt
./run.sh            # starts Odoo on :8069

# Frontend
cd frontend
npm install
npm run dev         # starts Vite on :8080, proxies /api → :8069

See MANUAL-RUN.md for a step-by-step walkthrough and CONNECT-POSTGRES.md for database wiring.


2. Repository layout

odoo19/
├── backend/
│   └── custom_addons/
│       ├── encoach_api/              REST base + JWT + OpenAPI + metrics
│       ├── encoach_core/             Users, entities, roles, permissions
│       ├── encoach_taxonomy/         Subject → Domain → Topic
│       ├── encoach_ai/               OpenAI wrapper, cefr_mapper, validator
│       ├── encoach_ai_course/        AI course/exam generation pipelines
│       ├── encoach_ai_grading/       AI grading (writing/speaking/math/IT)
│       ├── encoach_ai_media/         TTS (Polly), STT (Whisper), ELAI
│       ├── encoach_vector/           pgvector store + RAG embeddings
│       ├── encoach_exam_template/    Canonical exam + student attempt models
│       ├── encoach_scoring/          Score computation, CEFR mapping
│       ├── encoach_quality_gate/     Automated content-quality checks
│       ├── encoach_ielts_validation/ IELTS-specific validators
│       ├── encoach_adaptive/         Adaptive engine, style matcher
│       ├── encoach_lms_api/          OpenEduCat bridge + LMS endpoints
│       ├── encoach_branding/         White-label config per entity
│       └── … (other encoach_* modules)
├── frontend/
│   ├── src/
│   │   ├── pages/                    Route pages (React.lazy code-split)
│   │   ├── components/               Shared UI (shadcn/ui + custom)
│   │   ├── services/                 Thin API wrappers over fetch
│   │   ├── hooks/queries/            React Query hooks + keys
│   │   ├── lib/api-client.ts         Fetch + auto JWT refresh
│   │   └── types/                    Shared DTO types
│   └── vite.config.ts                manualChunks: react, query, charts, radix…
├── docs/
│   ├── PROJECT_SUMMARY.md            Release notes & architecture history
│   ├── adr/                          Architecture Decision Records
│   └── ENCOACH_*.md                  SRS, workflows, user stories
├── docker-compose.yml
├── Dockerfile
├── requirements.txt                  Python deps (pgvector, textstat, etc.)
└── README.md                         You are here

3. Architecture at a glance

┌────────────────────┐     HTTPS/JWT      ┌────────────────────┐
│  React SPA (Vite)  │  ───────────────►  │   Odoo 19 + FastAPI-style   │
│  - React Query     │  ◄───────────────  │   controllers (encoach_*)   │
│  - next-themes     │   X-Request-Id     └──────┬─────────────┘
│  - shadcn/ui       │                           │
└────────────────────┘                           ▼
                                          ┌──────────────┐
                                          │  PostgreSQL  │
                                          │  + pgvector  │
                                          └──────┬───────┘
                                                 │
                                                 ▼
                                          ┌──────────────┐
                                          │   OpenAI,    │
                                          │   Whisper,   │
                                          │   Polly…     │
                                          └──────────────┘

Every request carries an X-Request-Id and emits structured JSON logs. Prometheus-compatible counters are exposed at /api/metrics, and the live OpenAPI 3.0 spec is at /api/openapi.json.


4. Key conventions

  • Canonical response envelope — list endpoints return { items: T[], total, page, size, data: T[] } (see encoach_api.controllers.base.paginated_envelope).
  • CEFR mapping — only encoach_ai.services.cefr_mapper is canonical. Do not reintroduce local band_to_cefr copies.
  • JWT tokens — short-lived access tokens (1h) + revocable refresh tokens (7d). Only access tokens are accepted as Bearer credentials; refresh tokens must go through /api/auth/refresh. See docs/adr/0002-jwt-refresh-token-flow.md.
  • RAG metadata — vector embeddings carry course_id, subject_id, entity_id, taxonomy, content_hash. Chunking kicks in above 2 000 chars.
  • Frontend paginationPaginatedResponse<T> exposes both items and data. Read from items in new code.
  • Frontend theming — tokens live in frontend/src/index.css (:root and .dark). Always use hsl(var(--token)) instead of raw hex.

5. Health, observability, docs

Endpoint Purpose
GET /api/health Liveness (always 200 when server is up)
GET /api/health/ready Readiness (DB + required config)
GET /api/openapi.json Dynamic OpenAPI 3.0 spec generated from @http.route
GET /api/metrics Prometheus-format counters per route

6. Deployment

Staging and production both use Docker Compose. The staging server rebuilds automatically from main; never force-push. See INSTALL-ODOO-SUMMARY.md for bootstrap notes.

Service Staging URL
Odoo backend http://5.189.151.117:8069
React frontend http://5.189.151.117:3000

The .env file is never committed. On staging it lives at /opt/encoach/backend-v2/.env.


7. Further reading

Document Description
docs/PROJECT_SUMMARY.md Release notes + architecture history
docs/adr/ Architecture Decision Records (why we built it this way)
docs/ENCOACH_UNIFIED_SRS.md Unified frontend + backend SRS
docs/ENCOACH_ODOO19_BACKEND_SRS.md Backend SRS v3.0
docs/ENCOACH_WORKFLOWS_BACKEND_SRS.md Backend workflows
docs/ENCOACH_WORKFLOWS_FRONTEND_SRS.md Frontend workflows

8. Contributing

  1. Branch from main — never push direct. Branch protection enforces it.
  2. Run npx tsc --noEmit -p tsconfig.app.json (frontend) and the module smoke tests before opening a PR.
  3. Every architectural decision should be captured as an ADR under docs/adr/. Copy 0000-template.md to start one.
  4. Open the PR against main and request review from devops (Talal).
Description
No description provided
Readme 375 MiB
Languages
Python 70.8%
HTML 22.1%
JavaScript 3.9%
SCSS 2.1%
CSS 1.1%