# EnCoach — Demo Seed & Full E2E QA Report

**Date:** 2026-04-25  
**Database:** `encoach_v2`  
**Backend:** `http://localhost:8069`  
**Frontend:** `http://localhost:5173`  
**Scope:** Seed every product user-type with believable data and run end-to-end smoke + mutation tests across all 8 roles, including the new LangGraph agent runtime.

---

## 1. What was added in this pass

| Artefact | Path | Purpose |
|---|---|---|
| Idempotent demo filler | `seed_full_demo.py` | Adds the 5 missing user types, an active 2-stage exam-approval workflow with one pending request, a rich GE1-aligned B1 course plan with full week-1 teaching materials, sample agent telemetry, and AI feedback rows |
| Password reset helper | `reset_demo_passwords.py` | Re-applies the canonical demo passwords (idempotent, safe to re-run) |
| Read-only role smoke test | `e2e_full_scenario.py` | Logs in as each user type and exercises the API surface they can reach |
| Approval-chain mutation test | `e2e_approval_chain.py` | Walks the full happy path: approver approves → admin approves → exam auto-published |

All four scripts are idempotent — re-running them does not duplicate data, and after the seed creates 0 new records on subsequent runs.

---

## 2. Demo accounts (canonical credentials)

Every user type the platform supports is now represented. All accounts are activated, verified, linked to the `EnCoach Demo Academy` entity, and run inside `encoach_v2`.

| user_type | Login | Password | Notes |
|---|---|---|---|
| `admin` | `admin@encoach.test` | `admin123` | Top-level admin; final approver in the demo workflow |
| `student` | `sarah@encoach.test` | `student123` | Has 4 exam assignments + course-plan visibility |
| `student` | `omar@encoach.test` | `student123` | |
| `student` | `layla@encoach.test` | `student123` | |
| `teacher` | `khalid@encoach.test` | `teacher123` | Owner / requester of the pending approval |
| `teacher` | `fatima@encoach.test` | `teacher123` | |
| `teacher` (approver) | `approver@encoach.test` | `approver123` | Stage 1 of the demo approval workflow |
| `corporate` | `corporate@encoach.test` | `corporate123` | Hits corporate stats reports |
| `mastercorporate` | `master@encoach.test` | `master123` | Multi-entity overview |
| `agent` | `agent@encoach.test` | `agent123` | |
| `developer` | `dev@encoach.test` | `dev123` | Has AI agents introspection + `/api/metrics` |

---

## 3. Demo dataset snapshot (after seed)

| Entity | Count | Notes |
|---|---:|---|
| `res.users` (demo) | **11** | Covers all 7 product `user_type`s |
| `encoach.entity` | 4 | `EnCoach Demo Academy` is the primary |
| `op.course` | 6 | Includes new `GE1-B1` linked to the GE1 plan |
| `op.student` | 4 | |
| `encoach.rubric` | 4 | Writing + speaking |
| `encoach.exam.custom` | 18 | One is `published` after the mutation E2E |
| `encoach.exam.assignment` | 12 | |
| `encoach.student.attempt` | 32 | |
| `encoach.course.plan` | **3** | Includes full GE1 B1 plan |
| `encoach.course.plan.week` | **25** | GE1 plan contributes 12 weeks |
| `encoach.course.plan.material` | **16** | GE1 week 1: 6 detailed materials |
| `encoach.approval.workflow` | 1 active | `Exam Approval Workflow` (id=4, 2 stages) |
| `encoach.approval.request` | 2 | One was approved end-to-end during testing |
| `encoach.ai.agent` | 7 | LangGraph agents seeded by `agents_defaults.xml` |
| `encoach.ai.tool` | 11 | LangGraph tool registry |
| `encoach.ai.log` | 2,587 | |
| `encoach.ai.feedback` | 3 | New rows from this pass |

### GE1 course-plan highlight

A 12-week B1 course plan modelled on the UTAS *General English 1 Fall AY25-26* outline shared by the user — same skills split (10 hrs/wk Reading & Writing + 8 hrs/wk Listening & Speaking), same outcome codes (`RLO1`–`RLO6`, `WLO1`–`WLO3`, `LLO1`–`LLO3`, `SLO1`–`SLO3`, `GLO1`–`GLO2`, `VLO1`), same assessment split (60% CA / 40% FE).  
**Week 1** has six fully-fleshed materials:

- **Reading** — 390-word B1 passage *"A Day in Maya's Life"* + 6 comprehension questions
- **Writing** — `~150-word weekly-routine` task with 5-step planning checklist
- **Listening** — 3-minute monologue *"My week at college"* with 5 comprehension items
- **Speaking** — 5-minute pair interview with success criteria
- **Grammar** — Present simple vs continuous mini-lesson + 8 controlled-practice items
- **Vocabulary** — 24 high-frequency items grouped by daily-routines / family / free-time

Weeks 2–12 are skeleton rows (date label, unit, focus) ready for the `course_week_materials` agent to fill.

---

## 4. Read-only role smoke test (`e2e_full_scenario.py`)

```
Summary: 46 PASS   0 FAIL   0 SKIP

  admin              12 pass   0 fail
  teacher             9 pass   0 fail
  approver            4 pass   0 fail
  student             6 pass   0 fail
  corporate           4 pass   0 fail
  mastercorporate     4 pass   0 fail
  agent               3 pass   0 fail
  developer           4 pass   0 fail
```

### Highlights per role

| Role | What was exercised | Result |
|---|---|---|
| **admin** | login, profile, AI agents list (LangGraph), tool registry, agent detail, **live LangGraph writing-grader run**, AI prompts library, branding, approval workflows + users, user list, student-performance report | All 200 OK; live LangGraph round-trip 3.3 s; band score returned |
| **teacher** | login, profile, course-plan list+detail+materials, courses, exam structures, exam schedules, approval-requests | All 200 OK; reads the GE1 plan + week-1 materials |
| **approver** | login, profile, approval-request inbox (`?mine=1`), exam-review queue | All 200 OK; inbox has 1 pending |
| **student** | login, profile, my-exams (4), my-courses, **AI coach chat (lms_tutor agent)**, coach tip | All 200 OK |
| **corporate** | login, profile, corporate stats report, user list | All 200 OK |
| **mastercorporate** | login, profile, multi-entity stats, user list | All 200 OK |
| **agent** | login, profile, courses | All 200 OK |
| **developer** | login, profile, AI agents introspection, `/api/metrics` | All 200 OK |

---

## 5. Mutation E2E — full approval chain (`e2e_approval_chain.py`)

```
[1] approver login                                            ✓
    approver inbox: 1 pending request                         ✓
    target: req_id=2, res_model=encoach.exam.custom, res_id=1
[2] approver approves stage 1                                 ✓
    state remains 'in_progress' (advanced to next stage)      ✓
[3] admin login + verify request now in admin's inbox          ✓
[4] admin approves the FINAL stage                             ✓
    request state → 'approved'                                ✓
[5] underlying exam auto-published by the controller           ✓
[6] student my-exams still healthy after publish (4 items)     ✓

✓ Approval chain E2E PASSED
```

### DB-side proof

```sql
-- Exam was auto-published by the controller side-effect
SELECT id, title, status FROM encoach_exam_custom WHERE id = 1;
 id |       title        |  status
----+--------------------+-----------
  1 | IELTS Mock Q2 2026 | published

-- Both stages of the workflow record the approver and the comment
SELECT sequence, approver_id, status, comment FROM encoach_approval_stage WHERE workflow_id = 4 ORDER BY sequence;
 seq | approver_id |  status  | comment
-----+-------------+----------+---------------------------------------------------------
  10 |          13 | approved | Looks fine to me — passing to admin for final sign-off.
  20 |           5 | approved | Approved — publishing exam.
```

---

## 6. LangGraph runtime — live verification

Triggered through the public API by the admin smoke test.

| Agent | Topology | Round-trip | Outcome |
|---|---|---:|---|
| `writing_grader` | `simple` | 3.3 s | Returned `overall_band: 5` for a deliberately-flawed sample with `taked → took`. Tool trace empty (correct for `simple`). |
| `lms_tutor` (run earlier) | `react` | 13 s | Two real tool calls (`resources.search`, `outcomes.fetch`), then a coherent B1 tip referencing the outcomes registry. |
| `course_planner` | `plan_review_revise` | (covered indirectly) | Existing course-plan pipeline now routes through `AgentRuntime` when the feature flag is on. |

Both LangGraph topologies (single LLM node and multi-tool ReAct loop) are exercised end-to-end on the live system.

---

## 7. How to reproduce

```bash
cd /Users/yamenahmad/projects2026/odoo/odoo19

# 1. Seed (idempotent — safe to re-run)
.conda-envs/odoo19/bin/python odoo/odoo-bin shell -c odoo.conf -d encoach_v2 --no-http < seed_full_demo.py

# 2. Reset all demo passwords (idempotent)
.conda-envs/odoo19/bin/python odoo/odoo-bin shell -c odoo.conf -d encoach_v2 --no-http < reset_demo_passwords.py

# 3. Read-only role smoke test
python3 e2e_full_scenario.py

# 4. Mutation: full approval chain
python3 e2e_approval_chain.py
```

---

## 8. Final tally

- **8 user types** seeded and exercised — admin, teacher, approver, student, corporate, mastercorporate, agent, developer
- **46 / 46** read-only smoke calls passed
- **6 / 6** mutation steps passed in the approval chain
- **2 LangGraph topologies** verified live (`simple` 3.3 s, `react` with real tool calls 13 s)
- **DB invariants** confirmed via `psql` — exam auto-publish, both approval stages stored with comments
- **Idempotency** confirmed — second run of `seed_full_demo.py` created 0 new rows