feat(v3): restructure project + add complete frontend

- Restructure: move backend from new_project/ to backend/
- Add full React/TypeScript frontend (37 pages, 17 services, 16 type defs, 11 query hooks)
- Add docs/ with SRS specs, user stories, and workflow documentation
- Update .gitignore for new directory layout

Workflows implemented:
  WF1 User Signup, WF2 Placement Test, WF3 Exam Configuration,
  WF4 General English Exam, WF5 Course Generation,
  WF6 Entity Student Onboarding, AI Course Generation,
  Adaptive Learning Engine UI, White-Label Branding, Score Release

Made-with: Cursor

custom_addons/encoach_exam_template/models/passage.py

@@ -0,0 +1,46 @@
+from odoo import models, fields, api
+
+
+class EncoachPassage(models.Model):
+    _name = 'encoach.passage'
+    _description = 'Reading Passage'
+
+    exam_type = fields.Selection([
+        ('academic', 'Academic'),
+        ('general_training', 'General Training'),
+        ('general_english', 'General English'),
+    ], required=True)
+    section_num = fields.Integer(required=True)
+    topic_category = fields.Char(size=100, required=True)
+    body_text = fields.Text(required=True)
+    difficulty = fields.Selection([
+        ('easy', 'Easy'),
+        ('medium', 'Medium'),
+        ('hard', 'Hard'),
+    ], required=True)
+    status = fields.Selection([
+        ('draft', 'Draft'),
+        ('active', 'Active'),
+        ('retired', 'Retired'),
+        ('flagged', 'Flagged'),
+    ], default='draft', required=True)
+    word_count = fields.Integer(compute='_compute_word_count', store=True)
+    ai_generated = fields.Boolean(default=False)
+    approved = fields.Boolean(default=False)
+    ielts_certified = fields.Boolean(default=False)
+    generation_brief = fields.Text()
+    validation_errors = fields.Text()
+    cefr_level = fields.Selection([
+        ('pre_a1', 'Pre-A1'),
+        ('a1', 'A1'),
+        ('a2', 'A2'),
+        ('b1', 'B1'),
+        ('b2', 'B2'),
+        ('c1', 'C1'),
+        ('c2', 'C2'),
+    ])
+
+    @api.depends('body_text')
+    def _compute_word_count(self):
+        for record in self:
+            record.word_count = len(record.body_text.split()) if record.body_text else 0