Based on UTAS GE1 Course Outline structure (Reading/Writing 10hrs + Listening/Speaking 8hrs)
New Models:
- encoach.course.plan.deliverable: Explicit learning outcome tracking by week/skill
- encoach.course.plan.resource.dep: Resource dependencies (textbooks, videos, etc.)
- encoach.course.plan.assignment: Assign plans to classes/students with progress tracking
- encoach.course.plan.assignment.deliverable: Per-student deliverable completion status
Extended Models:
- course.plan.material: Added media fields (media_type, media_asset_url, media_asset_id,
media_generation_prompt, media_metadata_json) for rich content
- New material types: video_lesson, audio_recording, image_visual, interactive, assessment
AI Agent Tools (agent_tools.py):
- deliverables.detect: Parse course outlines (like GE1 PDF) and extract structured outcomes
- deliverables.fetch: Get deliverables for AI to reference when generating
- resources.fetch: Check available resources before generating content
- resources.save: Persist resource dependencies
- media.suggest_visuals: AI suggests images/diagrams for materials
- media.generate_image: Generate educational images (DALL-E integration ready)
- media.generate_audio: Generate TTS audio (ElevenLabs/Polly integration ready)
- assignment.*: Create assignments and track progress
Pipeline Enhancements (course_plan_pipeline.py):
- generate_deliverables_from_outline(): Parse PDF/text outlines into structured deliverables
- generate_week_materials_with_resources(): Resource-aware content generation
- suggest_media_for_material(): AI visual aid suggestions
- generate_media_for_material(): Actual image/audio generation
New AI Agents (agents_defaults.xml):
- deliverable_detector: Parses GE1-style outlines, extracts deliverables week-by-week
- media_generator: Creates images/audio for teaching materials
- Updated course_planner & course_week_materials with resource tools
REST APIs (course_plan.py):
POST /api/ai/course-plan/<id>/deliverables/detect - Parse outline
GET /api/ai/course-plan/<id>/deliverables - List deliverables
PUT /api/ai/course-plan/deliverables/<id> - Update status
GET /api/ai/course-plan/<id>/resources - List resources
POST /api/ai/course-plan/<id>/resources - Add resource
POST /api/ai/course-plan/materials/<id>/media/suggest - Get visual suggestions
POST /api/ai/course-plan/materials/<id>/media/generate - Generate image/audio
POST /api/ai/course-plan/<id>/assignments - Assign to class/student
GET /api/ai/course-plan/<id>/assignments - List assignments
GET /api/ai/course-plan/assignments/<id> - Get with progress
PUT /api/ai/course-plan/assignments/<id>/deliverables/<del_id> - Update status
Security: Added ir.model.access.csv entries for all new models
Made-with: Cursor
Frontend
- i18n: install tailwindcss-rtl, Cairo font, RTL-aware direction in index.css.
- Language toggle: localize aria-label / menu label, persist choice, update
document dir synchronously.
- Sidebar: add `side` prop so the drawer pins to the right in RTL; wire up
AdminLmsLayout, RoleLayout (student/teacher) and AppSidebar to pass
side = i18n.dir() === 'rtl' ? 'right' : 'left'.
- AdminLmsLayout: convert every nav item from hard-coded title to titleKey,
translate group labels (incl. the collapsible Training), breadcrumbs,
user menu (Profile / Settings / Logout), help button and toggle aria
labels; replace physical mr-/right- utilities with logical me-/end-.
- AI components (AiTipBanner, AiInsightsPanel, AiAlertBanner, AiSearchBar,
AiAssistantDrawer): apply dir="auto" at the container level, localize
titles, loading / error / empty states.
- Dashboards (admin / student / teacher): wrap numeric values in <bdi>,
localize dates via ar-EG, fix flex direction for KPI and assignment cards.
- UI primitives (breadcrumb, calendar, carousel, dropdown-menu, menubar,
context-menu, pagination, sidebar): flip chevrons in RTL via a scoped
CSS rule, swap pl-/pr-/ml-/mr- for ps-/pe-/ms-/me-.
- Add logical-direction helpers and bidirectional isolation classes.
Locales
- Expand en.ts and ar.ts with full `nav`, `sidebarGroup`, `breadcrumb`,
`userMenu`, `chrome`, `ai`, and dashboard key sets; keep key parity.
API client
- `api-client.ts` reads the active language from localStorage/i18n and sends
`Accept-Language` on every request so the backend can localize AI output.
Backend (encoach_ai)
- openai_service: add _LANGUAGE_NAMES, normalize_language, language-aware
system prompt injection for every OpenAI call.
- coach_service + controllers (coach_controller, ai_controller): thread
the requested language from headers / user locale down to OpenAIService.
- ai_feedback: fix latent registry error by pointing course_id at op.course
instead of the non-existent encoach.course.
Other
- .gitignore: ignore runtime odoo logs and local caches.
Made-with: Cursor
- Fix ELAI video generation (correct render endpoint, script splitting for 60s limit)
- Fix speaking script generation error handling and empty response display
- Add custom exam list API (GET /api/exam/custom/list)
- Add assignments REST API (list, create, get)
- Add rubrics REST API (list, create)
- Enhance Generation page: dynamic exam structures, auto-module selection, preview dialog, audio player
- Improve submit feedback with exam ID and status in toast notifications
- Fix ExamsListPage to show both custom exams and exam sessions
- Connect RubricsPage to backend API with fallback data
- Add Dockerfile, docker-compose.yml, requirements.txt for deployment
- Fix placement, grading, scoring, and auth controllers
- Add ErrorBoundary component for frontend resilience
- Add QA report and credentials documentation
Made-with: Cursor
