b02ee8b6b7
Generation Page (complete rebuild): - Full production-parity exam generation wizard with 4 IELTS modules - Reading: AI passage gen, 5 exercise types (MCQ, Fill, Write, T/F, Match) - Listening: 4 section types, AI context gen, TTS audio gen (ElevenLabs) - Writing: Task 1/2, AI instruction gen, word limits, marks - Speaking: 3 parts, AI script gen, avatar video gen (7 avatars) - Per-module config: timer, CEFR difficulty, access, approval, rubrics - Exam submission workflow (draft/published) Exam Structures: - New encoach.exam.structure model + CRUD controller - ExamStructuresPage wired to real API AI Module (encoach_ai): - OpenAI service, ElevenLabs TTS, AWS Polly, ELAI avatars - AI settings model with Odoo config parameters - 7 generation endpoints (passage, exercises, instructions, scripts, context) Vector Module (encoach_vector): - pgvector integration for RAG-based content search - Embedding service with sentence-transformers Exam Session Fixes: - Fixed ExamSession.tsx field mapping (question_type→type, exam_title→title) - Fixed submit payload to include attempt_id and answers - Fixed normalizeType to handle null/undefined Tested: 12/12 API tests passed, browser-verified with real OpenAI calls Made-with: Cursor
EnCoach Backend — v2
Branching Workflow
This repo is connected to the staging server via a Git post-receive hook. All deployment is automatic — but only after code review approval.
How to contribute
- Never push directly to
main— branch protection will block it. - Create a feature or fix branch:
git checkout -b feature/your-feature-name - Develop, commit, and push your branch:
git push origin feature/your-feature-name - Open a Pull Request on Gitea targeting
main. - Request review from devops (Talal).
- Once approved and merged, the staging server rebuilds and redeploys automatically.
Environment
The .env file is not committed. It lives only on the staging server at /opt/encoach/backend-v2/.env.
Contact the team lead if you need a local copy of the environment variables.
Required files (push with your code)
Dockerfile— used by the staging server to build the container imagedocker-compose.yml— defines the backend service (port mapping, env vars, etc.)