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...
Author SHA1 Message Date
kcar 0ba72e4259 G1 add homework field to lessons API 2026-07-24 19:20:42 +01:00
kcarandClaude Opus 4.8 e48dd73fdf exam: capture sections + choice_groups + marks_confidence in extraction_meta (WS-2 R3)
api-ci-deploy / test-build-deploy (push) Has been cancelled
Persist the paper's question-layout signals (A-level Section A/B, EITHER/OR choice
groups, marks confidence) onto exam_templates.extraction_meta so the setup UI can
show them. Data was carried by the contract but dropped at persistence.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01GruxHXxfdp4kZCgAMVFgvV
2026-07-04 13:13:45 +00:00
kcarandClaude Opus 4.8 547836e04b exam: persist exam_response_areas.meta on canvas replace-save (WS-2 item 4)
api-ci-deploy / test-build-deploy (push) Has been cancelled
The full-replace save dropped the rich region meta (figure name/description, OMR
geometry). Add meta to ResponseAreaPayload + the replace insert so a named context
figure survives a round-trip. Pairs with the app carrying name/description through.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01GruxHXxfdp4kZCgAMVFgvV
2026-07-04 12:13:13 +00:00
kcarandClaude Opus 4.8 df128508a3 exam: persist command_word + preamble from analyse contract v2 (WS-2)
_map_service_contract_to_rows now carries the two v2 fields onto exam_questions
ghost rows (command_word on leaf parts, preamble jsonb). Requires supabase
migration 78; applied to dev .94.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01GruxHXxfdp4kZCgAMVFgvV
2026-07-04 11:56:40 +00:00
kcar 81bf44c6cc Merge P3+P4 app wiring
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-03 02:09:17 +00:00
kcarandClaude Opus 4.8 544d858f62 P3+P4 app: persist audit gate (extraction_meta) + digital-text endpoint
_run_service_extract_merge now records extraction_meta {engine, slug, audit
(cover-total reconciliation), counts} on the template (migration 76) — a durable
trust signal the setup UI shows. New GET /templates/{id}/digital-text proxies the
service's /api/replica for the paper (resolved via extraction_meta.slug), returning
the digital-replica markdown. exam_extract.get_replica client added.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-03 02:09:17 +00:00
kcar 7d1876b799 Merge P2 fix: extraction-service wiring
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-02 23:45:29 +00:00
kcarandClaude Opus 4.8 c79a161119 P2 fix: re-apply auto-map extraction-service wiring + compose env
The prior P2 merge lost the templates.py + compose changes (a git reset --hard in
the commit sequence discarded the tracked-file edits; only the two new files survived).
This re-applies: exam_extract import + _frac_box/_frac_y canvas adapters +
_extract_slug + _map_service_contract_to_rows + _run_service_extract_merge/_job +
the auto_map_template routing, and the EXAM_EXTRACT_URL compose env.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 23:45:29 +00:00
kcar 08af7c8ca1 Merge P2: auto-map via extraction service
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-02 23:41:37 +00:00
kcarandClaude Opus 4.8 98210f2cff P2: route exam auto-map through the extraction service (full recognition)
When EXAM_EXTRACT_URL is set, POST /templates/{id}/auto-map now runs the spike's
full recognition pipeline (via the P1 service) instead of the thin first-pass, as
an async job. New modules/services/exam_extract.py (HTTP client: POST paper, poll,
return the analyse contract). templates.py: _map_service_contract_to_rows adapts the
page-fraction analyse contract onto the app's 780-wide stacked canvas (fraction ×
rendered dims + page_top), re-namespaces the service's uuid5s per template (stable
re-map, no cross-template collision), and is FK-safe (drops orphan regions, de-parents
dangling parents). Rich meta (OMR boxes, select_n, unit/quantity, n_options) persists
to the new exam_response_areas.meta column (migration 75). Typed response_form + mcq
answer_type + kind:context reference links map natively (schema already allows them).

The thin path is preserved as fallback when EXAM_EXTRACT_URL is unset. Unit test
covers the mapping (coord conversion, id remap, FK-safety, meta passthrough).

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 23:41:37 +00:00
kcar d3d0639f44 Merge exam-bank corpus coverage endpoint
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-02 22:33:07 +00:00
kcarandClaude Opus 4.8 52801a5d34 Exam bank: corpus coverage endpoint (state of the collected exam bank)
GET /api/exam/corpus — read-only view over the seeded eb_specifications + eb_exams
catalogue: board → subject → spec → papers grouped by paper_code+session, each
showing which of QP/MS/ER exist AND are stored, with per-spec + global rollups
(specs, papers, sessions, QP/MS/ER counts). Surfaces the collected exam bank so
the app can display its state — e.g. AQA GCSE Physics 8463: 21 QP / 12 MS / 17 ER.

Validated against the live catalogue (60 specs, 1178 docs, 535 papers) + a unit
test (grouping, QP/MS/ER presence, stored-vs-catalogued). As-user (catalogue is
public reference data).

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 22:33:07 +00:00
kcar 6a6d12875d Merge mode-3 question bank + custom-paper endpoints
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-02 22:05:39 +00:00
kcarandClaude Opus 4.8 df827b990c Mode-3: question bank + custom-paper assembly endpoints
GET /api/exam/bank — leaf questions across the caller's institute templates
(RLS-scoped) with source-paper context + spec_ref/subject filters and facets;
the spec-planning surface for build-your-own.

POST /api/exam/custom-papers {title, subject?, question_ids[]} — copy-on-assemble:
create a new exam_template owned by the caller and insert COPIES of the selected
leaf questions (new ids, requested order, carrying marks/answer_type/spec_ref/
bounds + their response areas), then project to Neo4j. A custom paper is a normal
template, so it flows through setup/marking/results/projection unchanged. The
shared-question decouple is Phase-2 (design: ~/cc/ideas/2026-07-02-mode3-...).

Tests (4, pass in-container): bank lists leaves + facets (excludes containers),
spec_ref filter, custom-paper copies in order with fresh ids, 400/404 guards.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 22:05:39 +00:00
kcar 4f66fb83ce Merge fx-3-image-only-projection
api-ci-deploy / test-build-deploy (push) Has been cancelled
2026-07-02 21:48:08 +00:00
kcar a0f77333b9 Merge fx-2-born-digital-marks 2026-07-02 21:48:08 +00:00
kcar e4b0477b77 Merge fx-1-auto-map-pk 2026-07-02 21:48:08 +00:00
kcar e95b148e0f Merge FX-7: marking completion status + max_marks validation 2026-07-02 21:48:01 +00:00
kcar b0b59077bc Merge FX-6: seed SpecPoint catalogue for all 6 test specs 2026-07-02 21:48:01 +00:00
CC WorkerandClaude Opus 4.8 931e254b93 FX-7: marking completion status + max_marks validation
batches.py upsert_mark previously never advanced a submission or batch to
'complete', and never validated an award against the question's max.

- Reject (422) an awarded_marks that exceeds the question's max_marks — only when
  a max is actually set (0/None = not-yet-scored AI/unmapped question, unvalidatable).
- _advance_completion: a submission with a mark for every markable (leaf) question
  → 'complete'; a batch whose every non-absent submission is complete → 'complete'.
  Container questions and absent students are excluded; the helper only promotes,
  never regresses, so it is safe on every upsert.

Adds test_upsert_mark_rejects_over_max and test_upsert_mark_completes_submission_and_batch.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 21:35:24 +00:00
CC WorkerandClaude Opus 4.8 cce46305c9 FX-2: surface born-digital per-part marks from auto-map
The board grammar already parses per-part marks ([N marks] / "Total for Question
N is M marks"), but they were dropped building the first-pass template and the
row mapper hardcoded max_marks=0 — so every born-digital paper came back with
zero marks for a teacher to re-key by hand.

Thread the parsed mark through: bands.py derive_bands now carries each part's
`marks`, template.build passes it into part_bands, and _map_first_pass_to_rows
reads it via a defensive _safe_marks (non-negative int; unknown/None -> 0, so
image-only OCR — which has no marks yet — is unchanged). Containers still roll up
from parts. Adds test_auto_map_surfaces_born_digital_part_marks.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 21:30:28 +00:00
CC WorkerandClaude Opus 4.8 47e45f59e8 FX-6: seed SpecPoint catalogue for all 6 test specs (ASSESSES beyond AQA physics)
Only AQA GCSE Physics 8463 (4.1-4.8) was seeded, so any other board/spec — or
any spec_ref that didn't match those 8 — projected zero (:Part)-[:ASSESSES]->
(:SpecPoint) edges, silently. Seed the full top-level topic catalogue for the 6
current test specs (GCSE + A-level Physics/Chemistry/Biology, 44 SpecPoints) and
loop the Specification/SpecPoint MERGE over all of them (board created once).

Idempotent; deterministic uuid5 keys unchanged. Sub-point granularity remains a
later data task. Run: python3 -c "from run.initialization.init_exam_graph import
init; import json; print(json.dumps(init()))" in the ccapi container.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 21:25:23 +00:00
CC WorkerandClaude Opus 4.8 41614b78ef FX-3: project image-only papers to Neo4j after auto-map
Only the born-digital fast path enqueued project_template_safe; the async OCR
job (_run_auto_map_job) — where image-only papers, R3's primary target, are
routed — never projected, so those papers never reached the graph after
auto-map. Project at the end of the async job too.

Adds test_auto_map_ocr_path_projects_to_neo4j.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 21:22:54 +00:00
CC WorkerandClaude Opus 4.8 1671518ca8 FX-1: auto-map re-run must not PK-collide with confirmed ghosts
_refresh_ai_rows deleted only unconfirmed AI rows, then bulk-inserted freshly
generated rows keyed by a deterministic uuid5 of (template_id, semantic key).
A confirmed ghost keeps that id, so a re-run re-emitted it → primary-key
conflict that failed the whole insert batch (reachable: auto-map is blocked only
when marks exist, not when ghosts are confirmed).

Fix: after the delete, read the ids that survived (confirmed-AI + manual) and
skip re-inserting any freshly generated row whose id matches — preserving the
teacher's curated row and making the insert PK-safe.

Adds test_auto_map_rerun_after_confirm_does_not_pk_collide, which confirms a
ghost at its REAL generated id (the prior test used an arbitrary id that never
collided) and asserts the row survives exactly once with confirmed=True.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-07-02 21:02:10 +00:00
CC WorkerandClaude Opus 4.8 6c73174829 fix(exam): match app's per-page ceil so shapes don't drift up on long papers
api-ci-deploy / test-build-deploy (push) Has been cancelled
The app sets canvas.height = Math.ceil(viewport.height) per page and stacks pages by those
heights; the backend page_top used the raw float, so it fell ~1px/page short, compounding to a
visible upward shape shift on later pages (~36px over 40 pages). Ceil rendered_h to match exactly.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-06-08 20:11:28 +00:00
CC WorkerandClaude Opus 4.8 5434a5bf21 fix(exam): emit auto-map canvas coords in the frontend 780-wide page space
api-ci-deploy / test-build-deploy (push) Has been cancelled
_pdf_page_geometry left rendered_w/h in PDF points (~595x842), but the app renders each PDF
page at PAGE_WIDTH=780 with proportional height and places shapes at the raw bounds. Result:
every detected region rendered shrunk (~0.76x) and shifted up-left. Set rendered_w=780 +
rendered_h=780*aspect (matches pdfLoader + pageGeometryFromImages), and scale px/point TOPLEFT
boxes into that space (was a hardcoded 0.5). Path-2 point boxes auto-correct via rendered_w/page_pt_w.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-06-08 19:18:09 +00:00
CC WorkerandClaude Opus 4.8 44ccba2151 fix(exam): guarantee auto-map child rows reference an inserted question
api-ci-deploy / test-build-deploy (push) Has been cancelled
On papers where band detection yields few/no questions but opencv/gemma still emit response
regions, those regions referenced a synthetic default_qid that was never inserted -> FK violation
(exam_response_areas/exam_boundaries -> exam_questions). Ensure the fallback container question
exists and reattach orphan child rows to it.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-06-08 18:45:09 +00:00
CC WorkerandClaude Opus 4.8 e83873e822 fix(exam): dedupe all AI auto-map rows by id before insert
api-ci-deploy / test-build-deploy (push) Has been cancelled
B1-4 live-route validation: continuation bands re-emit the same stable AI id for
response_areas/boundaries/layout (not just questions), causing duplicate-pkey insert
failures. Add _dedupe_rows_by_id applied to all four tables in _refresh_ai_rows.

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-06-08 18:02:51 +00:00
21 changed files with 1120 additions and 49 deletions
+4 -1
View File
@@ -67,11 +67,13 @@ def derive_bands(result, doc=None, rapid_glob=None):
topnum = _topnumber_boxes(docs)
# gather parts with geometry, grouped by page
by_page = defaultdict(list) # page -> [(q, label, t, b)]
part_marks = {} # (question, part label) -> parsed marks (born-digital grammar)
for q in result.get("questions", []):
for p in q["parts"]:
bb, pg = p.get("bbox"), p.get("page")
if bb and pg:
by_page[pg].append((q["question"], p["label"], bb["t"], bb["b"]))
part_marks[(q["question"], p["label"])] = p.get("marks")
# global first page each question appears on (to mark the true start vs continuation pages)
q_first_page = {}
@@ -104,7 +106,8 @@ def derive_bands(result, doc=None, rapid_glob=None):
for (q, lab), st, en, _ in _ends(part_items):
qen = main_band.get(q, (st, 0))[1] # don't run past the question end
part.append({"label": lab, "question": q,
"y_start": round(st, 1), "y_end": round(max(en, qen), 1)})
"y_start": round(st, 1), "y_end": round(max(en, qen), 1),
"marks": part_marks.get((q, lab))})
pages[pg] = {"main": main, "part": part}
return {"board": result.get("board"), "paper_code": result.get("paper_code"),
+1
View File
@@ -159,6 +159,7 @@ def build(structured, bands, furniture, pdf=None, page_roles=None):
"y_start": p["y_start"], "y_end": p["y_end"],
"label_box": part_bbox.get(p["label"]), # anchor, not the part extent
"box": synthesize_part_box(p, xband),
"marks": p.get("marks"), # parsed per-part marks (born-digital)
"source": "auto", "confirmed": False,
})
pr = page_roles.get(pgs) or page_roles.get(pg) or {}
@@ -0,0 +1,14 @@
-- G1: Homework as a first-class lesson/planner field.
-- Apply to DEV Supabase only before promoting app/api changes.
alter table if exists public.taught_lessons
add column if not exists homework text not null default '';
alter table if exists public.planned_lessons
add column if not exists homework text not null default '';
comment on column public.taught_lessons.homework is
'Teacher-authored homework for this taught lesson; surfaced in lesson/timetable views.';
comment on column public.planned_lessons.homework is
'Default homework carried by a lesson plan and copied to a taught lesson when delivered.';
+2
View File
@@ -55,6 +55,8 @@ services:
- CC_COMPOSE_SERVICE=backend-dev
- RUN_INIT=false
- INIT_MODE=infra
# P2: route exam auto-map through the spike's full recognition pipeline (extraction service)
- EXAM_EXTRACT_URL=${EXAM_EXTRACT_URL:-http://192.168.0.203:8899}
ports:
- "18000:8000"
depends_on:
@@ -53,6 +53,7 @@ class PlannedLessonNode(CCBaseNode):
subject: str
teacher_code: str
planning_status: str
homework: Optional[str] = None
topic_code: Optional[str] = None
topic_name: Optional[str] = None
lesson_code: Optional[str] = None
+86
View File
@@ -0,0 +1,86 @@
"""Client for the exam extraction SERVICE (docling-exam-spike, P1).
The service runs the spike's FULL recognition pipeline (textlayer → question tree → OMR/figure/table
sidecars → structure fusion → analyse) and returns the ghost-region contract the app already consumes.
This module is a thin HTTP client: POST the paper, poll, return the `analyse` suggestions. The app's
auto-map merges them (coordinate-adapted, id-remapped) in routers/exam/templates.py.
Config: EXAM_EXTRACT_URL (e.g. http://192.168.0.203:8899). If unset, the app keeps its thin first-pass.
"""
from __future__ import annotations
import base64
import os
import time
from typing import Any, Dict, Optional
import requests
from modules.logger_tool import initialise_logger
logger = initialise_logger(__name__, os.getenv("LOG_LEVEL"), os.getenv("LOG_PATH"), "default", True)
class ExtractError(RuntimeError):
pass
def service_url() -> Optional[str]:
url = os.getenv("EXAM_EXTRACT_URL")
return url.rstrip("/") if url else None
def is_enabled() -> bool:
return bool(service_url())
def _get(base: str, slug: str, timeout: int = 30) -> Dict[str, Any]:
r = requests.get(f"{base}/api/extract/{slug}", timeout=timeout)
r.raise_for_status()
return r.json()
def get_replica(slug: str, timeout: int = 30) -> Dict[str, Any]:
"""The digital-replica markdown for a paper (P4): {slug, title, n_questions, total_marks, markdown,
questions:[{label, marks, markdown}]}. Raises ExtractError if the paper has no replica yet."""
base = service_url()
if not base:
raise ExtractError("EXAM_EXTRACT_URL not configured")
r = requests.get(f"{base}/api/replica/{slug}", timeout=timeout)
if r.status_code == 404:
raise ExtractError(f"no digital replica for {slug}")
r.raise_for_status()
return r.json()
def extract_suggestions(slug: str, pdf_bytes: bytes, *, force: bool = False,
poll_timeout: int = 1500, poll_interval: int = 5) -> Dict[str, Any]:
"""POST the paper to the service and poll until the analyse contract is ready.
Returns the full analyse payload: {status, coordinate_space:'page_fraction', margins,
suggestions:{questions[], response_areas[], boundaries[]}, meta}. Raises ExtractError on
failure/timeout. A cold paper is ~15 min (Docling per masked page); cached papers return instantly.
"""
base = service_url()
if not base:
raise ExtractError("EXAM_EXTRACT_URL not configured")
payload = {"slug": slug, "pdf_b64": base64.b64encode(pdf_bytes).decode(), "force": force}
r = requests.post(f"{base}/api/extract", json=payload, timeout=120)
r.raise_for_status()
started = r.json()
if not started.get("ok", True):
raise ExtractError(started.get("error") or "service rejected the request")
# cached → fetch the contract straight away; otherwise poll the running job
deadline = time.time() + poll_timeout
while True:
d = _get(base, slug)
status = d.get("status")
if status == "complete":
if not (d.get("suggestions") or {}):
raise ExtractError("service returned complete with no suggestions")
return d
if status == "error":
raise ExtractError(f"extraction failed: {d.get('error')}")
if time.time() >= deadline:
raise ExtractError(f"extraction timed out after {poll_timeout}s (slug={slug})")
time.sleep(poll_interval)
+18 -2
View File
@@ -83,6 +83,7 @@ class CreatePlanRequest(BaseModel):
estimated_duration_minutes: Optional[int] = None
objectives: Optional[List[Dict[str, Any]]] = None
activities: Optional[List[Dict[str, Any]]] = None
homework: Optional[str] = None
status: Optional[str] = "draft"
tags: Optional[List[str]] = None
topic_code: Optional[str] = None
@@ -99,6 +100,7 @@ class UpdatePlanRequest(BaseModel):
estimated_duration_minutes: Optional[int] = None
objectives: Optional[List[Dict[str, Any]]] = None
activities: Optional[List[Dict[str, Any]]] = None
homework: Optional[str] = None
status: Optional[str] = None
tags: Optional[List[str]] = None
topic_code: Optional[str] = None
@@ -249,6 +251,7 @@ async def create_plan(
"status": body.status or "draft",
"objectives": body.objectives or [],
"activities": body.activities or [],
"homework": body.homework or "",
"tags": body.tags or [],
}
for field in (
@@ -362,7 +365,7 @@ async def update_plan(
updates: Dict[str, Any] = {}
for field in (
"title", "class_id", "subject", "year_group", "estimated_duration_minutes",
"objectives", "activities", "status", "tags", "topic_code",
"objectives", "activities", "homework", "status", "tags", "topic_code",
"whiteboard_room_id", "course_id", "sequence_number",
):
val = getattr(body, field)
@@ -425,7 +428,7 @@ async def deliver_plan(
plan_res = (
sb.supabase.table("planned_lessons")
.select("id, whiteboard_room_id")
.select("id, whiteboard_room_id, homework")
.eq("id", plan_id)
.eq("institute_id", institute_id)
.single()
@@ -456,6 +459,19 @@ async def deliver_plan(
res = sb.supabase.table("lesson_deliveries").insert(row).execute()
delivery = (res.data or [{}])[0]
# If the plan has default homework and was delivered into a taught lesson,
# copy it onto the lesson so homework appears in daily/timetable views.
plan_homework = plan_res.data.get("homework")
if body.taught_lesson_id and plan_homework is not None:
try:
sb.supabase.table("taught_lessons").update({
"homework": plan_homework,
"updated_at": datetime.utcnow().isoformat(),
}).eq("id", body.taught_lesson_id).eq("teacher_id", user_id).execute()
except Exception as e:
logger.warning(f"Could not copy homework to taught_lesson {body.taught_lesson_id}: {e}")
logger.info(f"Lesson delivery created: {delivery.get('id')} for plan {plan_id} by {user_id}")
return delivery
@@ -4,7 +4,7 @@ Taught Lessons Router — materialization and lesson CRUD.
POST /materialize — slot template × academic_periods → taught_lessons rows
GET /lessons — teacher's lessons for a date range
GET /lessons/{id} — single lesson detail
PATCH /lessons/{id} — update lesson_plan, notes, status (teacher-owned)
PATCH /lessons/{id} — update lesson_plan, homework, notes, status (teacher-owned)
"""
import os
from collections import defaultdict
@@ -44,6 +44,7 @@ def _require_institute(user_id: str) -> str:
class UpdateLessonRequest(BaseModel):
lesson_plan: Optional[Dict[str, Any]] = None
homework: Optional[str] = None
notes: Optional[str] = None
status: Optional[str] = None # planned | in_progress | completed | cancelled | substituted
@@ -310,7 +311,7 @@ async def get_lessons(
lessons = (
sb.supabase.table("taught_lessons")
.select(
"id,date,period_code,week_cycle,day_of_week,status,lesson_plan,notes,whiteboard_room_id,"
"id,date,period_code,week_cycle,day_of_week,status,lesson_plan,homework,notes,whiteboard_room_id,"
"class_id,academic_period_id"
)
.eq("teacher_id", user_id)
@@ -418,13 +419,15 @@ async def update_lesson(
body: UpdateLessonRequest,
credentials: dict = Depends(SupabaseBearer()),
) -> Dict[str, Any]:
"""Teacher updates their own lesson content: plan, notes, status."""
"""Teacher updates their own lesson content: plan, homework, notes, status."""
user_id = credentials.get("sub", "")
sb = _sb()
updates: Dict[str, Any] = {}
if body.lesson_plan is not None:
updates["lesson_plan"] = body.lesson_plan
if body.homework is not None:
updates["homework"] = body.homework
if body.notes is not None:
updates["notes"] = body.notes
if body.status is not None:
@@ -508,7 +511,7 @@ async def get_student_lessons(
lessons = (
sb.supabase.table("taught_lessons")
.select(
"id,date,period_code,week_cycle,day_of_week,status,lesson_plan,notes,whiteboard_room_id,"
"id,date,period_code,week_cycle,day_of_week,status,lesson_plan,homework,notes,whiteboard_room_id,"
"class_id,academic_period_id,teacher_id"
)
.in_("class_id", class_ids)
@@ -675,7 +675,7 @@ def _sync_taught_lessons_to_neo4j(
"""
lessons = (
sb.supabase.table("taught_lessons")
.select("id,neo4j_node_id,academic_period_id,teacher_id,date,period_code,week_cycle,day_of_week,status")
.select("id,neo4j_node_id,academic_period_id,teacher_id,date,period_code,week_cycle,day_of_week,status,homework")
.eq("institute_id", institute_id)
.execute()
.data or []
@@ -728,6 +728,7 @@ def _sync_taught_lessons_to_neo4j(
SET tl.date = date($date), tl.period_code = $pcode,
tl.week_cycle = $wc, tl.day_of_week = $dow,
tl.status = $status,
tl.homework = $homework,
tl.node_storage_path = $path
""",
id=tl_id,
@@ -736,6 +737,7 @@ def _sync_taught_lessons_to_neo4j(
wc=lesson.get("week_cycle", ""),
dow=lesson.get("day_of_week", ""),
status=lesson.get("status", "planned"),
homework=lesson.get("homework") or "",
path=f"taught_lessons/{tl_id}",
)
count += 1
+4
View File
@@ -8,9 +8,13 @@ from fastapi import APIRouter
from routers.exam.templates import router as templates_router
from routers.exam.batches import router as batches_router
from routers.exam.bank import router as bank_router
from routers.exam.corpus import router as corpus_router
router = APIRouter()
router.include_router(templates_router)
router.include_router(batches_router)
router.include_router(bank_router)
router.include_router(corpus_router)
__all__ = ["router"]
+152
View File
@@ -0,0 +1,152 @@
"""Question bank + custom-paper assembly (/api/exam/bank, /api/exam/custom-papers) — mode 3.
Build-your-own-from-the-spec. The BANK is a browsable index over the leaf questions across the templates
the caller can see (RLS-scoped, institute-wide); a CUSTOM PAPER is a normal exam_template whose questions
are COPIES of the selected bank questions, so it flows through the existing setup / marking / projection
pipeline unchanged. Copy-on-assemble (v1) avoids decoupling question identity from a template; a shared-
question model is Phase-2. Design: ~/cc/ideas/2026-07-02-mode3-question-bank-design.md.
All access is as-the-user (E1): the bank query returns only questions in templates RLS lets the caller see,
and a custom paper is created owned by the caller + institute-scoped (writes pass the same RLS with-check).
"""
from __future__ import annotations
import os
import uuid
from typing import Any, Dict, List, Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from modules.database.services.exam_projection import project_template_safe
from modules.logger_tool import initialise_logger
from routers.exam.dependencies import ExamContext, get_exam_context
logger = initialise_logger(__name__, os.getenv("LOG_LEVEL"), os.getenv("LOG_PATH"), "default", True)
router = APIRouter()
def _rows(result: Any) -> List[Dict[str, Any]]:
data = getattr(result, "data", None)
if not data:
return []
return data if isinstance(data, list) else [data]
def _first(result: Any) -> Optional[Dict[str, Any]]:
rows = _rows(result)
return rows[0] if rows else None
@router.get("/bank")
async def list_bank(
spec_ref: Optional[str] = None,
subject: Optional[str] = None,
ctx: ExamContext = Depends(get_exam_context),
) -> Dict[str, Any]:
"""Leaf questions across the caller's institute templates, with their source-paper context.
Filter by `spec_ref` (spec point) and/or `subject`. Facets over the full visible set drive the UI
filters (so filtering by one axis doesn't hide the others' options). This is the spec-planning surface:
a teacher picks a spec point gets every question tagged it across their papers assembles a paper.
"""
sel = (
"id, template_id, label, max_marks, answer_type, spec_ref, bounds, page, "
"exam_templates(id, title, subject, exam_code)"
)
query = ctx.supabase.table("exam_questions").select(sel).eq("is_container", False)
if spec_ref:
query = query.eq("spec_ref", spec_ref)
rows = _rows(query.execute())
facets_spec: Dict[str, int] = {}
facets_subject: Dict[str, int] = {}
items: List[Dict[str, Any]] = []
for r in rows:
tmpl = r.get("exam_templates") or {}
subj = tmpl.get("subject")
if r.get("spec_ref"):
facets_spec[r["spec_ref"]] = facets_spec.get(r["spec_ref"], 0) + 1
if subj:
facets_subject[subj] = facets_subject.get(subj, 0) + 1
if subject and subj != subject:
continue
items.append({
"id": r["id"], "template_id": r["template_id"], "label": r.get("label"),
"max_marks": r.get("max_marks"), "answer_type": r.get("answer_type"),
"spec_ref": r.get("spec_ref"), "bounds": r.get("bounds"), "page": r.get("page"),
"paper": {"id": tmpl.get("id"), "title": tmpl.get("title"),
"subject": subj, "exam_code": tmpl.get("exam_code")},
})
return {"questions": items, "n": len(items),
"facets": {"spec_ref": facets_spec, "subject": facets_subject}}
class CustomPaperRequest(BaseModel):
title: str
subject: Optional[str] = None
institute_id: Optional[str] = None
question_ids: List[str]
@router.post("/custom-papers")
async def create_custom_paper(
body: CustomPaperRequest,
ctx: ExamContext = Depends(get_exam_context),
) -> Dict[str, Any]:
"""Assemble the selected bank questions into a new template (copy-on-assemble), then project it."""
if not body.question_ids:
raise HTTPException(status_code=400, detail="question_ids is required")
institute_id = ctx.resolve_institute(body.institute_id)
# RLS makes this return only leaf questions the caller may see; unknown/forbidden ids are silently dropped.
srcs = _rows(
ctx.supabase.table("exam_questions").select("*")
.in_("id", body.question_ids).eq("is_container", False).execute()
)
by_id = {s["id"]: s for s in srcs}
ordered = [by_id[qid] for qid in body.question_ids if qid in by_id] # preserve the caller's order
if not ordered:
raise HTTPException(status_code=404, detail="No accessible questions for the given ids")
template_id = str(uuid.uuid4())
ctx.supabase.table("exam_templates").insert({
"id": template_id, "title": body.title, "subject": body.subject,
"institute_id": institute_id, "teacher_id": ctx.user_id, "status": "draft",
}).execute()
id_map: Dict[str, str] = {}
q_rows: List[Dict[str, Any]] = []
for order, s in enumerate(ordered):
new_id = str(uuid.uuid4())
id_map[s["id"]] = new_id
q_rows.append({
"id": new_id, "template_id": template_id, "parent_id": None,
"label": s.get("label"), "order": order, "max_marks": s.get("max_marks") or 0,
"answer_type": s.get("answer_type"), "mcq_options": s.get("mcq_options"),
"mark_scheme": s.get("mark_scheme") or {}, "is_container": False,
"spec_ref": s.get("spec_ref"), "bounds": s.get("bounds"), "page": s.get("page"),
"source": "manual", "confirmed": True,
})
ctx.supabase.table("exam_questions").insert(q_rows).execute()
# Copy each selected question's response areas onto its new copy (geometry travels with the question).
ra_rows: List[Dict[str, Any]] = []
if id_map:
for ra in _rows(
ctx.supabase.table("exam_response_areas").select("*")
.in_("question_id", list(id_map.keys())).execute()
):
ra_rows.append({
"id": str(uuid.uuid4()), "question_id": id_map[ra["question_id"]], "template_id": template_id,
"page": ra.get("page"), "bounds": ra.get("bounds"), "kind": ra.get("kind"),
"response_form": ra.get("response_form"), "context_type": ra.get("context_type"),
"source": "manual", "confirmed": True,
})
if ra_rows:
ctx.supabase.table("exam_response_areas").insert(ra_rows).execute()
project_template_safe(template_id) # a custom paper is a normal paper in the graph
return {"id": template_id, "title": body.title, "subject": body.subject,
"n_questions": len(q_rows), "n_response_areas": len(ra_rows)}
+42
View File
@@ -245,6 +245,36 @@ async def batch_csv(
# ─── marks ───────────────────────────────────────────────────────────────────
def _advance_completion(ctx: ExamContext, batch_id: str, submission_id: str) -> None:
"""After a mark upsert, advance statuses: a submission with a mark for every markable (leaf)
question complete; a batch whose every non-absent submission is complete complete. Nothing
here regresses a status (only promotes to complete), so it is safe to run on every upsert."""
batch = _first(
ctx.supabase.table("marking_batches").select("id, template_id, status").eq("id", batch_id).limit(1).execute()
)
if not batch:
return
markable = {
q["id"] for q in _rows(
ctx.supabase.table("exam_questions").select("id, is_container").eq("template_id", batch["template_id"]).execute()
) if not q.get("is_container")
}
if not markable:
return
marked = {
m["question_id"] for m in _rows(
ctx.supabase.table("mark_entries").select("question_id").eq("submission_id", submission_id).execute()
)
}
if not markable.issubset(marked):
return
ctx.supabase.table("student_submissions").update({"status": "complete"}).eq("id", submission_id).execute()
subs = _rows(ctx.supabase.table("student_submissions").select("status").eq("batch_id", batch_id).execute())
active = [s for s in subs if s.get("status") != "absent"]
if active and all(s.get("status") == "complete" for s in active) and batch.get("status") != "complete":
ctx.supabase.table("marking_batches").update({"status": "complete"}).eq("id", batch_id).execute()
@router.put("/marks/{mark_id}")
async def upsert_mark(
mark_id: str,
@@ -259,6 +289,15 @@ async def upsert_mark(
if not submission:
raise HTTPException(status_code=404, detail="Submission not found")
# Reject an award that exceeds the question's max (only when a max is actually set; 0/None means
# "not scored yet" for AI/unmapped questions, so we can't validate those).
question = _first(
ctx.supabase.table("exam_questions").select("id, max_marks").eq("id", body.question_id).limit(1).execute()
)
max_marks = (question or {}).get("max_marks")
if isinstance(max_marks, (int, float)) and max_marks > 0 and body.awarded_marks is not None and body.awarded_marks > max_marks:
raise HTTPException(status_code=422, detail=f"awarded_marks {body.awarded_marks} exceeds max_marks {max_marks} for this question")
row = {
"id": mark_id,
"submission_id": body.submission_id,
@@ -285,6 +324,9 @@ async def upsert_mark(
if submission.get("status") in ("absent", "unmatched"):
ctx.supabase.table("student_submissions").update({"status": "marking"}).eq("id", body.submission_id).execute()
# Promote the submission/batch to complete once every markable question has a mark.
_advance_completion(ctx, submission["batch_id"], body.submission_id)
return upserted
+98
View File
@@ -0,0 +1,98 @@
"""Exam-bank corpus coverage (/api/exam/corpus) — the state of the collected exam bank.
Read-only view over the seeded exam-board catalogue (eb_specifications + eb_exams): board subject
specification papers, with per-session QP/MS/ER coverage and rollup counts. Shows what the app has
COLLECTED (question papers, mark schemes, examiner reports) so a teacher/admin can see the bank's state
and where science coverage is complete vs thin. Catalogue data is public reference read as-the-user.
"""
from __future__ import annotations
import os
import re
from typing import Any, Dict, List, Optional
from fastapi import APIRouter, Depends
from modules.logger_tool import initialise_logger
from routers.exam.dependencies import ExamContext, get_exam_context
logger = initialise_logger(__name__, os.getenv("LOG_LEVEL"), os.getenv("LOG_PATH"), "default", True)
router = APIRouter()
DOC_TYPES = ("QP", "MS", "ER")
def _rows(result: Any) -> List[Dict[str, Any]]:
data = getattr(result, "data", None)
if not data:
return []
return data if isinstance(data, list) else [data]
def _award_level(spec: Dict[str, Any]) -> str:
"""Best-effort GCSE / AS / A-level from the spec code (AQA GCSE = 8xxx, A-level/AS = 7xxx)."""
code = re.sub(r"\D", "", spec.get("award_code") or spec.get("spec_code") or "")
if code.startswith("8"):
return "GCSE"
if code.startswith("7"):
return "A-level"
return spec.get("award_level") or "Other"
@router.get("/corpus")
async def corpus_coverage(ctx: ExamContext = Depends(get_exam_context)) -> Dict[str, Any]:
specs = _rows(
ctx.supabase.table("eb_specifications")
.select("spec_code, exam_board_code, subject_code, award_code, first_teach").execute()
)
exams = _rows(
ctx.supabase.table("eb_exams")
.select("exam_code, spec_code, paper_code, tier, session, type_code, storage_loc").execute()
)
# group exam docs → per spec → per paper (paper_code + session) → which doc types are present
by_spec: Dict[str, Dict[str, Dict[str, Any]]] = {}
for e in exams:
sc = e.get("spec_code")
if not sc:
continue
key = f"{e.get('paper_code') or '?'}|{e.get('session') or '?'}"
paper = by_spec.setdefault(sc, {}).setdefault(key, {
"paper_code": e.get("paper_code"), "session": e.get("session"),
"tier": e.get("tier"), "docs": {}, "exam_codes": {},
})
dt = (e.get("type_code") or "").upper()
if dt in DOC_TYPES:
paper["docs"][dt] = bool(e.get("storage_loc"))
paper["exam_codes"][dt] = e.get("exam_code")
totals = {"specs": 0, "papers": 0, "sessions": 0, **{d: 0 for d in DOC_TYPES}}
boards: Dict[str, Dict[str, Any]] = {}
for s in specs:
sc = s["spec_code"]
papers_map = by_spec.get(sc, {})
if not papers_map:
continue
totals["specs"] += 1
board = s.get("exam_board_code") or "?"
level = _award_level(s)
papers = sorted(papers_map.values(), key=lambda p: (str(p["session"]), str(p["paper_code"])))
counts = {d: sum(1 for p in papers if p["docs"].get(d)) for d in DOC_TYPES}
for d in DOC_TYPES:
totals[d] += counts[d]
totals["papers"] += len(papers)
totals["sessions"] += len({p["session"] for p in papers})
spec_entry = {
"spec_code": sc, "subject": (s.get("subject_code") or "").title(), "level": level,
"board": board, "first_teach": s.get("first_teach"),
"n_papers": len(papers), "counts": counts, "papers": papers,
}
boards.setdefault(board, {"board": board, "specs": []})["specs"].append(spec_entry)
board_list = []
for board in sorted(boards):
specs_sorted = sorted(boards[board]["specs"], key=lambda x: (x["level"], x["subject"], x["spec_code"]))
board_list.append({"board": board, "n_specs": len(specs_sorted), "specs": specs_sorted})
return {"totals": totals, "boards": board_list}
+3
View File
@@ -80,6 +80,9 @@ class ResponseAreaPayload(BaseModel):
] = None
# Optional Context differentiation (v1 generic; future graph/chart/data_table/diagram/code_block/passage).
context_type: Optional[str] = None
# Rich recognition payload (75-exam-marker-region-meta.sql): figure name/description, OMR geometry, unit…
# Carried on canvas save so a named context figure survives a round-trip.
meta: Optional[Dict[str, Any]] = None
source: Literal["manual", "ai"] = "manual"
confirmed: bool = True
confidence: Optional[float] = Field(default=None, ge=0, le=1)
+280 -13
View File
@@ -13,7 +13,9 @@ join keys (spec §2).
from __future__ import annotations
import json
import math
import os
import re
import tempfile
import time
import uuid
@@ -29,6 +31,7 @@ from modules.database.services.exam_projection import project_template, project_
from modules.database.supabase.utils.client import SupabaseServiceRoleClient
from modules.database.supabase.utils.storage import StorageAdmin
from modules.upload_validation import read_pdf_upload_bytes
from modules.services import exam_extract
from modules.logger_tool import initialise_logger
from routers.exam.dependencies import ExamContext, get_exam_context, lookup_exam_code
from routers.exam.schemas import (
@@ -342,6 +345,13 @@ def _pdf_has_text_layer(pdf_bytes: bytes) -> bool:
pass
# Canvas page width the frontend renders each PDF page at (app src/utils/exam-canvas/model.ts
# PAGE_WIDTH). All auto-map canvas coords are emitted in this 780-wide, proportional-height space.
CANVAS_PAGE_WIDTH = 780.0
# Response/answer-region detector (api/services/docling/regions.py) renders at 144 DPI = 2 px / PDF point.
REGIONS_PX_PER_PT = 2.0
def _pdf_page_geometry(pdf_bytes: bytes) -> List[Dict[str, float]]:
with tempfile.NamedTemporaryFile(prefix="cc-auto-map-geom-", suffix=".pdf", delete=False) as fh:
fh.write(pdf_bytes)
@@ -355,14 +365,23 @@ def _pdf_page_geometry(pdf_bytes: bytes) -> List[Dict[str, float]]:
for page in doc:
media = page.mediabox
crop = page.cropbox
rendered_w = float(crop.width or page.rect.width or 595.0)
rendered_h = float(crop.height or page.rect.height or 842.0)
page_pt_w = float(crop.width or page.rect.width or 1.0)
page_pt_h = float(crop.height or page.rect.height or 1.0)
# Emit canvas coords in the FRONTEND render space: the app draws each page at
# CANVAS_PAGE_WIDTH (app model.ts PAGE_WIDTH=780) with proportional height and stacks
# pages by those heights. Previously rendered_w/h were left in PDF points (~595x842),
# so every shape landed shrunk (~0.76x) and shifted up-left on the 780-wide canvas.
rendered_w = CANVAS_PAGE_WIDTH
# Mirror the app's canvas.height = Math.ceil(viewport.height) EXACTLY (pdfLoader.ts),
# so page_top accumulates identically. Using the raw float drifts ~1px/page, compounding
# to a visible upward shift on later pages of long papers (~36px over 40 pages).
rendered_h = float(math.ceil(CANVAS_PAGE_WIDTH * page_pt_h / page_pt_w))
pages.append({
"media_x0": float(media.x0),
"crop_x0": float(crop.x0),
"crop_y0": float(crop.y0),
"page_pt_w": float(crop.width or page.rect.width or 1),
"page_pt_h": float(crop.height or page.rect.height or 1),
"page_pt_w": page_pt_w,
"page_pt_h": page_pt_h,
"rendered_w": rendered_w,
"rendered_h": rendered_h,
"page_top": page_top,
@@ -384,11 +403,12 @@ def _pdf_page_geometry(pdf_bytes: bytes) -> List[Dict[str, float]]:
def _page_geom(pages: List[Dict[str, float]], page_number: int) -> Dict[str, float]:
if 1 <= page_number <= len(pages):
return pages[page_number - 1]
_fallback_h = float(math.ceil(CANVAS_PAGE_WIDTH * 842.0 / 595.0))
return {
"media_x0": 0.0, "crop_x0": 0.0, "crop_y0": 0.0,
"page_pt_w": 595.0, "page_pt_h": 842.0,
"rendered_w": 595.0, "rendered_h": 842.0,
"page_top": (page_number - 1) * 842.0,
"rendered_w": CANVAS_PAGE_WIDTH, "rendered_h": _fallback_h,
"page_top": (page_number - 1) * _fallback_h,
}
@@ -397,12 +417,16 @@ def _box_to_canvas(box: Optional[Dict[str, Any]], page_number: int, pages: List[
return None
g = _page_geom(pages, page_number)
if box.get("coord_origin") == "TOPLEFT" and {"x", "y", "w", "h"}.issubset(box):
scale = 0.5 if box.get("unit") == "px" else 1.0
# Scale the box into the 780-wide canvas space. px boxes (opencv/gemma regions) are in
# rendered-image px at REGIONS_PX_PER_PT px/point; TOPLEFT point boxes are 1 px/point.
px_per_pt = REGIONS_PX_PER_PT if box.get("unit") == "px" else 1.0
sx = g["rendered_w"] / (g["page_pt_w"] * px_per_pt)
sy = g["rendered_h"] / (g["page_pt_h"] * px_per_pt)
return {
"x": round(float(box["x"]) * scale, 2),
"y": round(g["page_top"] + float(box["y"]) * scale, 2),
"w": round(float(box["w"]) * scale, 2),
"h": round(float(box["h"]) * scale, 2),
"x": round(float(box["x"]) * sx, 2),
"y": round(g["page_top"] + float(box["y"]) * sy, 2),
"w": round(float(box["w"]) * sx, 2),
"h": round(float(box["h"]) * sy, 2),
}
if not {"l", "t", "r", "b"}.issubset(box):
return None
@@ -433,6 +457,32 @@ def _y_to_canvas(y_value: float, page_number: int, pages: List[Dict[str, float]]
return round(g["page_top"] + (g["page_pt_h"] - (float(y_value) - g["crop_y0"])) / g["page_pt_h"] * g["rendered_h"], 2)
def _frac_box_to_canvas(bounds: Optional[Dict[str, Any]], page_number: int,
pages: List[Dict[str, float]]) -> Optional[Dict[str, float]]:
"""Page-fraction {x,y,w,h} (0..1 per page, from the extraction service) → 780-wide stacked canvas."""
if not bounds:
return None
g = _page_geom(pages, page_number)
try:
x, y, w, h = (float(bounds["x"]), float(bounds["y"]), float(bounds["w"]), float(bounds["h"]))
except (KeyError, TypeError, ValueError):
return None
return {
"x": round(x * g["rendered_w"], 2),
"y": round(g["page_top"] + y * g["rendered_h"], 2),
"w": round(w * g["rendered_w"], 2),
"h": round(h * g["rendered_h"], 2),
}
def _frac_y_to_canvas(y_frac: Any, page_number: int, pages: List[Dict[str, float]]) -> Optional[float]:
g = _page_geom(pages, page_number)
try:
return round(g["page_top"] + float(y_frac) * g["rendered_h"], 2)
except (TypeError, ValueError):
return None
def _ai_id(template_id: str, *parts: Any) -> str:
return str(uuid.uuid5(uuid.NAMESPACE_URL, "/".join(["cc-auto-map", template_id, *[str(p) for p in parts]])))
@@ -443,6 +493,17 @@ def _safe_confidence(value: Any = None) -> float:
return 0.75
def _safe_marks(value: Any = None) -> int:
"""Parsed per-part marks → a non-negative int; unknown/None → 0 (image-only OCR has no marks yet)."""
if isinstance(value, bool):
return 0
if isinstance(value, (int, float)):
return max(0, int(value))
if isinstance(value, str) and value.strip().isdigit():
return int(value.strip())
return 0
def _margin_values(first_pass: Dict[str, Any], page_number: int) -> Dict[str, Optional[float]]:
vals: Dict[str, Optional[float]] = {"left": None, "right": None, "top": None, "bottom": None}
for m in first_pass.get("margins") or []:
@@ -519,7 +580,7 @@ def _map_first_pass_to_rows(template_id: str, first_pass: Dict[str, Any], pdf_by
top = max(float(y1), float(y2)); bottom = min(float(y1), float(y2))
bounds = _box_to_canvas({"l": margins["left"], "r": margins["right"], "t": top, "b": bottom, "coord_origin": "BOTTOMLEFT"}, page_number, pages_geom)
bounds = bounds or _box_to_canvas(band.get("label_box"), page_number, pages_geom)
questions.append({"id": pid, "template_id": template_id, "parent_id": parent_id, "label": label, "order": len(questions), "max_marks": 0, "is_container": False, "bounds": bounds, "page": page_number, "source": "ai", "confirmed": False, "confidence": _safe_confidence(band.get("confidence")), "derivation": "docling-part-band-x-margins"})
questions.append({"id": pid, "template_id": template_id, "parent_id": parent_id, "label": label, "order": len(questions), "max_marks": _safe_marks(band.get("marks")), "is_container": False, "bounds": bounds, "page": page_number, "source": "ai", "confirmed": False, "confidence": _safe_confidence(band.get("confidence")), "derivation": "docling-part-band-x-margins"})
default_qid = questions[0]["id"] if questions else _ai_id(template_id, "question", "auto")
for page_key in sorted(pages_obj, key=lambda k: int(k)):
@@ -540,15 +601,53 @@ def _map_first_pass_to_rows(template_id: str, first_pass: Dict[str, Any], pdf_by
response_form = _response_form_from_region_type(region.get("region_type"))
if response_form:
response_areas.append({"id": _ai_id(template_id, "region", page_index, idx), "template_id": template_id, "question_id": first_part_by_page.get(page_index, default_qid), "page": page_index + 1, "bounds": bounds, "kind": "response", "response_form": response_form, "source": "ai", "confirmed": False, "confidence": _safe_confidence(region.get("confidence")), "derivation": region.get("detection_method") or "opencv-response-region"})
# Integrity guard: every response_area/boundary question_id must reference an inserted question
# (FK exam_response_areas/exam_boundaries -> exam_questions). On papers where band detection yields
# few/no questions but opencv/gemma still emit regions, those regions point at the synthetic
# default_qid which was never inserted. Ensure that fallback container question exists and reattach
# any orphan child rows to it, so persistence can't violate the FK.
qid_set = {q["id"] for q in questions}
orphans = [r for r in (response_areas + boundaries) if r.get("question_id") not in qid_set]
if orphans:
if default_qid not in qid_set:
questions.insert(0, {"id": default_qid, "template_id": template_id, "label": "Unassigned",
"order": 0, "max_marks": 0, "is_container": True, "source": "ai",
"confirmed": False, "confidence": 0.5,
"derivation": "auto-map-fallback-container"})
qid_set.add(default_qid)
for r in orphans:
r["question_id"] = default_qid
return {"questions": questions, "response_areas": response_areas, "boundaries": boundaries, "layout": layout}
def _dedupe_rows_by_id(rows: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Preserve first occurrence of stable AI row ids emitted by noisy OCR detectors."""
out: List[Dict[str, Any]] = []
seen: set[str] = set()
for row in rows:
row_id = row.get("id")
if row_id:
key = str(row_id)
if key in seen:
continue
seen.add(key)
out.append(row)
return out
def _refresh_ai_rows(ctx: ExamContext, template_id: str, rows: Dict[str, List[Dict[str, Any]]]) -> None:
sb = ctx.supabase
for table in ("exam_response_areas", "exam_boundaries", "exam_template_layout", "exam_questions"):
sb.table(table).delete().eq("template_id", template_id).eq("source", "ai").eq("confirmed", False).execute()
for table, key in (("exam_questions", "questions"), ("exam_response_areas", "response_areas"), ("exam_boundaries", "boundaries"), ("exam_template_layout", "layout")):
payload = rows.get(key) or []
# A row that survived the delete above is confirmed-AI or manual — the teacher's curated version.
# AI ids are a deterministic uuid5 of (template_id, semantic key), so a re-run re-emits the SAME id
# for a confirmed ghost; re-inserting it would PK-collide and fail the whole batch. Skip those ids so
# confirmed work is preserved and the insert is safe (fixes the re-map-after-confirm collision).
kept = sb.table(table).select("id").eq("template_id", template_id).execute()
kept_ids = {str(r["id"]) for r in (getattr(kept, "data", None) or []) if isinstance(r, dict) and r.get("id")}
payload = [r for r in _dedupe_rows_by_id(rows.get(key) or []) if str(r.get("id")) not in kept_ids]
if payload:
sb.table(table).insert(payload).execute()
@@ -580,12 +679,153 @@ def _run_auto_map_job(job_id: str, ctx: ExamContext, template_id: str, pdf_bytes
_set_auto_map_status(job_id, {"status": "running", "template_id": template_id})
try:
rows = _run_auto_map_merge(ctx, template_id, pdf_bytes, source_label)
# Project to Neo4j like the born-digital fast path does — otherwise image-only papers (R3's
# primary target, routed here because they need OCR) never reach the graph after auto-map.
project_template_safe(template_id)
_set_auto_map_status(job_id, {"status": "completed", "template_id": template_id, "counts": {k: len(v) for k, v in rows.items()}})
except Exception as exc:
logger.exception(f"auto-map job failed for template {template_id}: {exc}")
_set_auto_map_status(job_id, {"status": "failed", "template_id": template_id, "error": str(exc)})
_ALLOWED_RESPONSE_FORMS = {"lines", "answer-box", "working", "diagram", "tick-boxes", "table", "blanks"}
_ALLOWED_ANSWER_TYPES = {"written", "mcq", "short", "diagram"}
_ALLOWED_KINDS = {"response", "context", "question_number", "mark_area", "reference", "furniture"}
_BOARD_RE = re.compile(r"^(aqa|edexcel|ocr|wjec|eduqas|ccea)-")
def _extract_slug(ctx: ExamContext, template: Dict[str, Any]) -> str:
"""A stable, board-prefixed slug for the extraction-service cache. Prefer the catalogue exam_code
(e.g. 'AQA-8463-1H-2022JUN-QP' 'aqa-8463-1h-2022jun-qp' board 'aqa' for the right margins);
fall back to a template-id slug (structure.py then defaults to AQA content-box margins)."""
code = None
exam_id = template.get("exam_id")
if exam_id:
try:
row = _first(ctx.supabase.table("eb_exams").select("exam_code").eq("id", exam_id).limit(1).execute())
code = (row or {}).get("exam_code")
except Exception as exc:
logger.info(f"extract slug: eb_exams lookup failed for {exam_id}: {exc}")
slug = re.sub(r"[^a-z0-9._-]+", "-", (code or "").lower()).strip("-")
if _BOARD_RE.match(slug):
return slug
return f"aqa-tmpl-{str(template.get('id') or '')[:12]}"
def _map_service_contract_to_rows(template_id: str, contract: Dict[str, Any],
pdf_bytes: bytes) -> Dict[str, List[Dict[str, Any]]]:
"""Map the extraction service's page-fraction analyse contract onto the app's canvas-space ghost rows.
Coordinates: page-fraction the 780-wide stacked canvas. IDs: the service's deterministic uuid5s are
re-namespaced per template via _ai_id so two templates of the same paper don't collide and a re-map of
the same template re-emits stable ids (so _refresh_ai_rows preserves confirmed ghosts). FK-safe: parts
whose parent/owner question is absent are de-parented / dropped rather than crashing the insert.
"""
pages = _pdf_page_geometry(pdf_bytes)
sug = contract.get("suggestions") or {}
def qid(uid: Any) -> str:
return _ai_id(template_id, "svc-q", uid)
questions: List[Dict[str, Any]] = []
q_ids: set = set()
for q in sug.get("questions") or []:
uid = q.get("uid")
if not uid:
continue
rid = qid(uid)
q_ids.add(rid)
at = q.get("answer_type") if q.get("answer_type") in _ALLOWED_ANSWER_TYPES else None
questions.append({
"id": rid, "template_id": template_id,
"parent_id": qid(q["parent_uid"]) if q.get("parent_uid") else None,
"label": q.get("label") or "?", "order": q.get("order", len(questions)),
"max_marks": _safe_marks(q.get("max_marks")), "answer_type": at,
"is_container": bool(q.get("is_container")),
"bounds": _frac_box_to_canvas(q.get("bounds"), q.get("page") or 1, pages),
"page": q.get("page"), "source": "ai", "confirmed": False,
"confidence": _safe_confidence(q.get("confidence")), "derivation": "extract-service",
# analyse contract v2 (migration 78): command verb + stem prose per part
"command_word": (q.get("command_word") or None) if not q.get("is_container") else None,
"preamble": q.get("preamble") or None,
})
for q in questions: # FK safety: de-parent a dangling parent_id
if q["parent_id"] and q["parent_id"] not in q_ids:
q["parent_id"] = None
response_areas: List[Dict[str, Any]] = []
for ra in sug.get("response_areas") or []:
uid = ra.get("uid")
quid = qid(ra.get("question_uid") or "")
if not uid or quid not in q_ids: # orphan region → drop (FK safety)
continue
bounds = _frac_box_to_canvas(ra.get("bounds"), ra.get("page") or 1, pages)
if not bounds:
continue
kind = ra.get("kind") if ra.get("kind") in _ALLOWED_KINDS else "response"
form = ra.get("response_form") if ra.get("response_form") in _ALLOWED_RESPONSE_FORMS else None
response_areas.append({
"id": _ai_id(template_id, "svc-ra", uid), "template_id": template_id,
"question_id": quid, "page": ra.get("page"), "bounds": bounds,
"kind": kind, "response_form": form if kind == "response" else None,
"context_type": ra.get("context_type"), "meta": ra.get("meta") or {},
"source": "ai", "confirmed": False,
"confidence": _safe_confidence(ra.get("confidence")), "derivation": "extract-service",
})
boundaries: List[Dict[str, Any]] = []
for i, b in enumerate(sug.get("boundaries") or []):
quid = qid(b.get("question_uid") or "")
if quid not in q_ids:
continue
page_index = b.get("page_index")
y = _frac_y_to_canvas(b.get("y"), (page_index or 0) + 1, pages)
if y is None:
continue
boundaries.append({
"id": _ai_id(template_id, "svc-b", b.get("question_uid") or i), "template_id": template_id,
"question_id": quid, "label": b.get("label") or "", "page_index": page_index,
"y": y, "bounds": None, "source": "ai", "confirmed": False,
"confidence": _safe_confidence(b.get("confidence")), "derivation": "extract-service",
})
return {"questions": questions, "response_areas": response_areas, "boundaries": boundaries}
def _run_service_extract_merge(ctx: ExamContext, template_id: str, pdf_bytes: bytes, slug: str) -> Dict[str, List[Dict[str, Any]]]:
contract = exam_extract.extract_suggestions(slug, pdf_bytes)
rows = _map_service_contract_to_rows(template_id, contract, pdf_bytes)
_refresh_ai_rows(ctx, template_id, rows)
meta = contract.get("meta") or {}
# P3: record provenance + the audit cover-reconciliation gate so the setup UI can flag under-reads,
# and store the slug so the digital-text view can resolve this paper's replica.
updates: Dict[str, Any] = {"extraction_meta": {
"engine": "extract-service", "slug": slug, "audit": meta.get("audit") or {},
"counts": {k: len(v) for k, v in rows.items()},
# question-layout signals for the setup UI: paper sections (e.g. A-level Section A/B) + EITHER/OR choices
"sections": meta.get("sections") or [],
"choice_groups": meta.get("choice_groups") or [],
"marks_confidence": meta.get("marks_confidence"),
}}
n_pages = meta.get("n_pages") or meta.get("pages")
if n_pages:
updates["page_count"] = n_pages
ctx.supabase.table("exam_templates").update(updates).eq("id", template_id).execute()
return rows
def _run_service_extract_job(job_id: str, ctx: ExamContext, template_id: str, pdf_bytes: bytes, slug: str) -> None:
_set_auto_map_status(job_id, {"status": "running", "template_id": template_id, "engine": "extract-service", "slug": slug})
try:
rows = _run_service_extract_merge(ctx, template_id, pdf_bytes, slug)
project_template_safe(template_id)
_set_auto_map_status(job_id, {"status": "completed", "template_id": template_id,
"engine": "extract-service", "counts": {k: len(v) for k, v in rows.items()}})
except Exception as exc:
logger.exception(f"extract-service job failed for template {template_id}: {exc}")
_set_auto_map_status(job_id, {"status": "failed", "template_id": template_id, "engine": "extract-service", "error": str(exc)})
# ─── templates ───────────────────────────────────────────────────────────────
@@ -763,6 +1003,14 @@ async def auto_map_template(
raise HTTPException(status_code=409, detail="Template has recorded marks; auto-map structural refresh is blocked.")
bucket, path, pdf_bytes = _resolve_template_source(ctx, template)
source_label = f"{bucket}/{path}"
# Extraction-service path (P2): when EXAM_EXTRACT_URL is set, route auto-map through the spike's full
# recognition pipeline instead of the thin first-pass. Always async — a cold paper is ~15 min.
if exam_extract.is_enabled():
slug = _extract_slug(ctx, template)
job_id = str(uuid.uuid4())
_set_auto_map_status(job_id, {"status": "queued", "template_id": template_id, "engine": "extract-service", "slug": slug})
background_tasks.add_task(_run_service_extract_job, job_id, ctx, template_id, pdf_bytes, slug)
return JSONResponse(status_code=202, content={"status": "accepted", "job_id": job_id, "engine": "extract-service"})
try:
fast_path = _pdf_has_text_layer(pdf_bytes)
except Exception as exc:
@@ -801,6 +1049,24 @@ async def auto_map_status(
return body
@router.get("/templates/{template_id}/digital-text")
async def template_digital_text(
template_id: str,
ctx: ExamContext = Depends(get_exam_context),
) -> Dict[str, Any]:
"""P4: the digital-replica markdown for this template's paper (stem text, parts, marks, answer-space
placeholders, spec refs). Resolves the paper via the slug the extraction used."""
template = _fetch_template_or_404(ctx, template_id)
_require_source_visibility_or_404(ctx, template)
if not exam_extract.is_enabled():
raise HTTPException(status_code=503, detail="Extraction service not configured")
slug = (template.get("extraction_meta") or {}).get("slug") or _extract_slug(ctx, template)
try:
return exam_extract.get_replica(slug)
except exam_extract.ExtractError as exc:
raise HTTPException(status_code=404, detail=f"No digital text yet — run auto-map first ({exc})")
@router.put("/templates/{template_id}")
async def replace_template(
template_id: str,
@@ -881,6 +1147,7 @@ async def replace_template(
"kind": ra.kind,
"response_form": ra.response_form,
"context_type": ra.context_type, # 73: optional Context differentiation
"meta": ra.meta, # 75: rich recognition payload (name/description/OMR/…)
"source": ra.source,
"confirmed": ra.confirmed,
"confidence": ra.confidence,
+62 -28
View File
@@ -1,17 +1,19 @@
"""
init_exam_graph.py Initialise the cc.public.exams Neo4j knowledge graph.
Creates the shared, public exam database, its uniqueness constraints, and seeds the AQA exam
board + AQA GCSE Physics (8463) specification with its 8 top-level topic SpecPoints. Idempotent
(CREATE DATABASE IF NOT EXISTS / CREATE CONSTRAINT IF NOT EXISTS / MERGE).
Creates the shared, public exam database, its uniqueness constraints, and seeds the AQA exam board
+ the 6 current test specifications (GCSE & A-level Physics/Chemistry/Biology) with their top-level
topic SpecPoints (44 in total). Idempotent (CREATE DATABASE IF NOT EXISTS / CREATE CONSTRAINT IF NOT
EXISTS / MERGE).
Run inside the ccapi container:
python3 -c "from run.initialization.init_exam_graph import init; import json; print(json.dumps(init()))"
NOTE: the 8 SpecPoints seeded here are the real AQA GCSE Physics *top-level* topics. The full
sub-point breakdown (e.g. 4.1.1.1 ...) is a later data-population task (sourceable from the AQA
spec PDF via Docling). spec_code AQA-PHYS-8463 is the standalone GCSE Physics code that matches
"AQA Physics Paper 1H"; the eb_exams/eb_specifications seed (card S4-3) must use the same code.
NOTE: only *top-level* topics are seeded (the granularity a teacher plans against). The full sub-point
breakdown (e.g. 4.1.1.1 ...) is a later data-population task (sourceable from the AQA spec PDF via
Docling). Seeding all 6 specs means a template's spec_ref finds a matching SpecPoint so
(:Part)-[:ASSESSES]->(:SpecPoint) fires beyond GCSE Physics; spec_code (e.g. AQA-PHYS-8463) must match
the eb_exams/eb_specifications seed (card S4-3) and the app's deriveSpecCode.
"""
import uuid
from typing import Dict, Any
@@ -41,6 +43,37 @@ SPEC_POINTS = [
("4.8", "Space physics"),
]
# Full AQA catalogue for the current test specs (top-level topics; ref = topic number). Seeding all of
# them means a template's spec_ref finds a matching SpecPoint so (:Part)-[:ASSESSES]->(:SpecPoint) fires
# beyond AQA GCSE Physics. Sub-point granularity (e.g. 4.1.1.1) remains a later data-population task.
SPECIFICATIONS = [
{**SPEC, "topics": SPEC_POINTS},
{"spec_code": "AQA-CHEM-8462", "exam_board_code": "AQA", "subject_code": "CHEM", "award_code": "GCSE",
"title": "AQA GCSE Chemistry (8462)", "topics": [
("4.1", "Atomic structure and the periodic table"), ("4.2", "Bonding, structure, and the properties of matter"),
("4.3", "Quantitative chemistry"), ("4.4", "Chemical changes"), ("4.5", "Energy changes"),
("4.6", "The rate and extent of chemical change"), ("4.7", "Organic chemistry"), ("4.8", "Chemical analysis"),
("4.9", "Chemistry of the atmosphere"), ("4.10", "Using resources")]},
{"spec_code": "AQA-BIOL-8461", "exam_board_code": "AQA", "subject_code": "BIOL", "award_code": "GCSE",
"title": "AQA GCSE Biology (8461)", "topics": [
("4.1", "Cell biology"), ("4.2", "Organisation"), ("4.3", "Infection and response"), ("4.4", "Bioenergetics"),
("4.5", "Homeostasis and response"), ("4.6", "Inheritance, variation and evolution"), ("4.7", "Ecology")]},
{"spec_code": "AQA-PHYS-7408", "exam_board_code": "AQA", "subject_code": "PHYS", "award_code": "A-level",
"title": "AQA A-level Physics (7408)", "topics": [
("3.1", "Measurements and their errors"), ("3.2", "Particles and radiation"), ("3.3", "Waves"),
("3.4", "Mechanics and materials"), ("3.5", "Electricity"), ("3.6", "Further mechanics and thermal physics"),
("3.7", "Fields and their consequences"), ("3.8", "Nuclear physics")]},
{"spec_code": "AQA-CHEM-7405", "exam_board_code": "AQA", "subject_code": "CHEM", "award_code": "A-level",
"title": "AQA A-level Chemistry (7405)", "topics": [
("3.1", "Physical chemistry"), ("3.2", "Inorganic chemistry"), ("3.3", "Organic chemistry")]},
{"spec_code": "AQA-BIOL-7402", "exam_board_code": "AQA", "subject_code": "BIOL", "award_code": "A-level",
"title": "AQA A-level Biology (7402)", "topics": [
("3.1", "Biological molecules"), ("3.2", "Cells"), ("3.3", "Organisms exchange substances with their environment"),
("3.4", "Genetic information, variation and relationships between organisms"),
("3.5", "Energy transfers in and between organisms"), ("3.6", "Organisms respond to changes"),
("3.7", "Genetics, populations, evolution and ecosystems"), ("3.8", "The control of gene expression")]},
]
CONSTRAINTS = [
"CREATE CONSTRAINT exam_board_uid IF NOT EXISTS FOR (n:ExamBoard) REQUIRE n.uuid_string IS UNIQUE",
"CREATE CONSTRAINT spec_uid IF NOT EXISTS FOR (n:Specification) REQUIRE n.uuid_string IS UNIQUE",
@@ -81,37 +114,38 @@ def init() -> Dict[str, Any]:
s.run(c).consume()
result["constraints"] += 1
# 3. board + spec
# 3. board (once)
board_uid = _uid("ExamBoard", BOARD["code"])
spec_uid = _uid("Specification", SPEC["spec_code"])
s.run(
"MERGE (b:ExamBoard {uuid_string:$uid}) "
"SET b.code=$code, b.name=$name, b.node_storage_path=$nsp",
uid=board_uid, code=BOARD["code"], name=BOARD["name"],
nsp=f"{EXAM_DB}/ExamBoard/{BOARD['code']}",
).consume()
s.run(
"MERGE (sp:Specification {uuid_string:$uid}) "
"SET sp.spec_code=$sc, sp.exam_board_code=$ebc, sp.subject_code=$subj, "
" sp.award_code=$award, sp.title=$title, sp.node_storage_path=$nsp "
"WITH sp MATCH (b:ExamBoard {code:$ebc}) MERGE (b)-[:PUBLISHES]->(sp)",
uid=spec_uid, sc=SPEC["spec_code"], ebc=SPEC["exam_board_code"],
subj=SPEC["subject_code"], award=SPEC["award_code"], title=SPEC["title"],
nsp=f"{EXAM_DB}/Specification/{SPEC['spec_code']}",
).consume()
# 4. spec points
for ref, desc in SPEC_POINTS:
sp_uid = _uid("SpecPoint", SPEC["spec_code"], ref)
# 4. each specification + its top-level spec points (idempotent MERGE)
for spec in SPECIFICATIONS:
spec_uid = _uid("Specification", spec["spec_code"])
s.run(
"MERGE (p:SpecPoint {uuid_string:$uid}) "
"SET p.ref=$ref, p.description=$desc, p.spec_code=$sc, "
" p.exam_board_code=$ebc, p.node_storage_path=$nsp "
"WITH p MATCH (s:Specification {spec_code:$sc}) MERGE (s)-[:HAS_SPEC_POINT]->(p)",
uid=sp_uid, ref=ref, desc=desc, sc=SPEC["spec_code"],
ebc=SPEC["exam_board_code"], nsp=f"{EXAM_DB}/SpecPoint/{SPEC['spec_code']}/{ref}",
"MERGE (sp:Specification {uuid_string:$uid}) "
"SET sp.spec_code=$sc, sp.exam_board_code=$ebc, sp.subject_code=$subj, "
" sp.award_code=$award, sp.title=$title, sp.node_storage_path=$nsp "
"WITH sp MATCH (b:ExamBoard {code:$ebc}) MERGE (b)-[:PUBLISHES]->(sp)",
uid=spec_uid, sc=spec["spec_code"], ebc=spec["exam_board_code"],
subj=spec["subject_code"], award=spec["award_code"], title=spec["title"],
nsp=f"{EXAM_DB}/Specification/{spec['spec_code']}",
).consume()
result["spec_points"] += 1
for ref, desc in spec["topics"]:
sp_uid = _uid("SpecPoint", spec["spec_code"], ref)
s.run(
"MERGE (p:SpecPoint {uuid_string:$uid}) "
"SET p.ref=$ref, p.description=$desc, p.spec_code=$sc, "
" p.exam_board_code=$ebc, p.node_storage_path=$nsp "
"WITH p MATCH (s:Specification {spec_code:$sc}) MERGE (s)-[:HAS_SPEC_POINT]->(p)",
uid=sp_uid, ref=ref, desc=desc, sc=spec["spec_code"],
ebc=spec["exam_board_code"], nsp=f"{EXAM_DB}/SpecPoint/{spec['spec_code']}/{ref}",
).consume()
result["spec_points"] += 1
counts = s.run(
"MATCH (b:ExamBoard) WITH count(b) AS boards "
+134
View File
@@ -0,0 +1,134 @@
"""Tests for the question-bank + custom-paper assembly router (/api/exam/bank, /custom-papers) — mode 3.
Same FakeSupabase + dependency-override pattern as test_exam_templates.py; the as-user RLS itself is
verified against the live dev DB (.94), not here.
"""
import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
import routers.exam.bank as bank_mod
from routers.exam.bank import router
from routers.exam.dependencies import ExamContext, get_exam_context
TEACHER = "00000000-0000-0000-0000-000000000001"
INST_A = "10000000-0000-0000-0000-000000000001"
@pytest.fixture(autouse=True)
def _stub_projection(monkeypatch):
monkeypatch.setattr(bank_mod, "project_template_safe", lambda tid: None)
class FakeResult:
def __init__(self, data):
self.data = data
class FakeQuery:
def __init__(self, store, table):
self.store = store
self.table = table
self.rows = list(store.get(table, []))
self._op = None
self._payload = None
def select(self, *_a, **_k):
self._op = "select"
return self
def insert(self, payload):
self._op = "insert"
self._payload = payload
return self
def eq(self, key, value):
self.rows = [r for r in self.rows if r.get(key) == value]
return self
def in_(self, key, values):
values = set(values)
self.rows = [r for r in self.rows if r.get(key) in values]
return self
def execute(self):
backing = self.store.setdefault(self.table, [])
if self._op == "insert":
payloads = self._payload if isinstance(self._payload, list) else [self._payload]
inserted = []
for p in payloads:
row = dict(p)
row.setdefault("id", f"gen-{self.table}-{len(backing)}")
backing.append(row)
inserted.append(row)
return FakeResult(inserted)
return FakeResult(self.rows)
class FakeSupabase:
def __init__(self, store):
self.store = store
def table(self, name):
return FakeQuery(self.store, name)
def make_client(store, user_id=TEACHER, institute_ids=(INST_A,)):
app = FastAPI()
app.include_router(router, prefix="/api/exam")
app.dependency_overrides[get_exam_context] = lambda: ExamContext(user_id, "tok", FakeSupabase(store), list(institute_ids))
return TestClient(app), store
def test_bank_lists_leaf_questions_with_facets_excluding_containers():
store = {"exam_questions": [
{"id": "c1", "template_id": "t1", "label": "Q1", "is_container": True, "spec_ref": None,
"exam_templates": {"id": "t1", "title": "Physics 1H", "subject": "physics", "exam_code": "AQA-PHYS-8463"}},
{"id": "q1", "template_id": "t1", "label": "01.1", "is_container": False, "max_marks": 3, "spec_ref": "4.2",
"exam_templates": {"id": "t1", "title": "Physics 1H", "subject": "physics", "exam_code": "AQA-PHYS-8463"}},
{"id": "q2", "template_id": "t1", "label": "01.2", "is_container": False, "max_marks": 2, "spec_ref": "4.2",
"exam_templates": {"id": "t1", "title": "Physics 1H", "subject": "physics", "exam_code": "AQA-PHYS-8463"}},
]}
c, _ = make_client(store)
body = c.get("/api/exam/bank").json()
labels = {q["label"] for q in body["questions"]}
assert labels == {"01.1", "01.2"} # container excluded
assert body["facets"]["spec_ref"] == {"4.2": 2}
assert body["questions"][0]["paper"]["exam_code"] == "AQA-PHYS-8463"
def test_bank_filters_by_spec_ref():
store = {"exam_questions": [
{"id": "q1", "template_id": "t1", "label": "a", "is_container": False, "spec_ref": "4.2", "exam_templates": {"subject": "physics"}},
{"id": "q2", "template_id": "t1", "label": "b", "is_container": False, "spec_ref": "4.5", "exam_templates": {"subject": "physics"}},
]}
c, _ = make_client(store)
body = c.get("/api/exam/bank?spec_ref=4.2").json()
assert [q["id"] for q in body["questions"]] == ["q1"]
def test_custom_paper_copies_selected_questions_in_order():
store = {"exam_questions": [
{"id": "q1", "template_id": "t1", "label": "01.1", "is_container": False, "max_marks": 3, "spec_ref": "4.2", "answer_type": "short"},
{"id": "q2", "template_id": "t2", "label": "05.1", "is_container": False, "max_marks": 6, "spec_ref": "4.5", "answer_type": "written"},
]}
c, store = make_client(store)
r = c.post("/api/exam/custom-papers", json={"title": "Electricity mini-test", "subject": "physics", "question_ids": ["q2", "q1"]})
assert r.status_code == 200
body = r.json()
assert body["n_questions"] == 2
# a new template row was created, owned + institute-scoped
new_tpls = [t for t in store["exam_templates"] if t["id"] == body["id"]]
assert new_tpls and new_tpls[0]["teacher_id"] == TEACHER and new_tpls[0]["institute_id"] == INST_A
# two COPIES exist under the new template, order preserving the requested [q2, q1], with fresh ids
copies = sorted([q for q in store["exam_questions"] if q["template_id"] == body["id"]], key=lambda q: q["order"])
assert [q["label"] for q in copies] == ["05.1", "01.1"]
assert all(q["id"] not in ("q1", "q2") for q in copies) # not the originals
assert copies[0]["max_marks"] == 6 and copies[0]["spec_ref"] == "4.5"
def test_custom_paper_requires_accessible_questions():
c, _ = make_client({"exam_questions": []})
assert c.post("/api/exam/custom-papers", json={"title": "x", "question_ids": ["nope"]}).status_code == 404
assert c.post("/api/exam/custom-papers", json={"title": "x", "question_ids": []}).status_code == 400
+24
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@@ -249,6 +249,30 @@ def test_upsert_mark_submission_404():
assert c.put("/api/exam/marks/mk-x", json={"submission_id": "nope", "question_id": "q1", "awarded_marks": 1}).status_code == 404
def test_upsert_mark_rejects_over_max():
c = make_client(_batch_with_cohort()) # q1 max_marks = 3
r = c.put("/api/exam/marks/mk-over", json={"submission_id": "sub2", "question_id": "q1", "awarded_marks": 4})
assert r.status_code == 422
def test_upsert_mark_completes_submission_and_batch():
store = base_store(
marking_batches=[{"id": "b1", "template_id": TPL, "institute_id": INST_A, "teacher_id": TEACHER, "status": "marking"}],
exam_questions=[
{"id": "q0", "template_id": TPL, "label": "Q1", "max_marks": 0, "order": 0, "is_container": True},
{"id": "q1", "template_id": TPL, "label": "01", "max_marks": 3, "order": 1, "is_container": False},
{"id": "q2", "template_id": TPL, "label": "02", "max_marks": 5, "order": 2, "is_container": False},
],
student_submissions=[{"id": "sub1", "batch_id": "b1", "student_id": "s1", "status": "marking"}],
mark_entries=[{"id": "m1", "batch_id": "b1", "submission_id": "sub1", "question_id": "q1", "awarded_marks": 2}],
)
c = make_client(store)
# marking the last leaf question completes the submission (container q0 doesn't block) and the batch
assert c.put("/api/exam/marks/m2", json={"submission_id": "sub1", "question_id": "q2", "awarded_marks": 4}).status_code == 200
assert next(s for s in store["student_submissions"] if s["id"] == "sub1")["status"] == "complete"
assert next(b for b in store["marking_batches"] if b["id"] == "b1")["status"] == "complete"
# ─── scans (E3 guards) ───────────────────────────────────────────────────────
def _batch_store():
+48
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@@ -0,0 +1,48 @@
"""Test the exam-bank corpus coverage grouping (/api/exam/corpus)."""
from fastapi import FastAPI
from fastapi.testclient import TestClient
from routers.exam.corpus import router
from routers.exam.dependencies import ExamContext, get_exam_context
TEACHER = "00000000-0000-0000-0000-000000000001"
INST_A = "10000000-0000-0000-0000-000000000001"
class FakeResult:
def __init__(self, data): self.data = data
class FakeQuery:
def __init__(self, store, table): self.store, self.table = store, table
def select(self, *_a, **_k): return self
def execute(self): return FakeResult(list(self.store.get(self.table, [])))
class FakeSupabase:
def __init__(self, store): self.store = store
def table(self, name): return FakeQuery(self.store, name)
def _client(store):
app = FastAPI(); app.include_router(router, prefix="/api/exam")
app.dependency_overrides[get_exam_context] = lambda: ExamContext(TEACHER, "tok", FakeSupabase(store), [INST_A])
return TestClient(app)
def test_corpus_groups_papers_by_session_with_qp_ms_er_coverage():
store = {
"eb_specifications": [{"spec_code": "AQA-PHYS-8463", "exam_board_code": "AQA", "subject_code": "PHYSICS", "award_code": "8463", "first_teach": "2016"}],
"eb_exams": [
{"exam_code": "a", "spec_code": "AQA-PHYS-8463", "paper_code": "8463/1H", "session": "2022-Jun", "type_code": "QP", "storage_loc": "cc.examboards/a.pdf"},
{"exam_code": "b", "spec_code": "AQA-PHYS-8463", "paper_code": "8463/1H", "session": "2022-Jun", "type_code": "MS", "storage_loc": "cc.examboards/b.pdf"},
{"exam_code": "c", "spec_code": "AQA-PHYS-8463", "paper_code": "8463/1H", "session": "2022-Jun", "type_code": "ER", "storage_loc": None},
{"exam_code": "d", "spec_code": "AQA-PHYS-8463", "paper_code": "8463/2H", "session": "2023-Jun", "type_code": "QP", "storage_loc": "cc.examboards/d.pdf"},
],
}
body = _client(store).get("/api/exam/corpus").json()
assert body["totals"]["specs"] == 1 and body["totals"]["papers"] == 2
spec = body["boards"][0]["specs"][0]
assert spec["level"] == "GCSE" and spec["subject"] == "Physics"
assert spec["counts"] == {"QP": 2, "MS": 1, "ER": 0} # ER present but not stored → not counted
p = next(p for p in spec["papers"] if p["paper_code"] == "8463/1H")
assert p["docs"] == {"QP": True, "MS": True, "ER": False}
+75
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@@ -0,0 +1,75 @@
"""Test the extraction-service contract → app ghost-row mapping (P2).
Mocks the PDF geometry so the mapper is tested in isolation: page-fraction 780-canvas conversion,
per-template uuid remap, FK-safety (orphan regions / dangling parents), and rich meta passthrough.
"""
import routers.exam.templates as T
TID = "11111111-1111-1111-1111-111111111111"
# two pages, each rendered 780 wide × 1000 tall; page 2 stacked below page 1
_GEOM = [
{"rendered_w": 780.0, "rendered_h": 1000.0, "page_top": 0.0, "page_pt_w": 595.0, "page_pt_h": 842.0, "crop_x0": 0.0, "crop_y0": 0.0},
{"rendered_w": 780.0, "rendered_h": 1000.0, "page_top": 1000.0, "page_pt_w": 595.0, "page_pt_h": 842.0, "crop_x0": 0.0, "crop_y0": 0.0},
]
_CONTRACT = {
"coordinate_space": "page_fraction",
"suggestions": {
"questions": [
{"uid": "Q1", "label": "1", "order": 0, "max_marks": 5, "is_container": True, "page": 1},
{"uid": "Q1a", "parent_uid": "Q1", "label": "1(a)", "order": 1, "max_marks": 3,
"answer_type": "short", "is_container": False, "page": 1},
{"uid": "Q1b", "parent_uid": "Q1", "label": "1(b)", "order": 2, "max_marks": 2,
"answer_type": "mcq", "is_container": False, "page": 2},
],
"response_areas": [
{"uid": "RA1", "question_uid": "Q1a", "page": 1, "kind": "response", "response_form": "answer-box",
"confidence": 0.9, "bounds": {"x": 0.1, "y": 0.2, "w": 0.5, "h": 0.05},
"meta": {"unit": "m/s", "quantity": "v", "n_lines": 1}},
{"uid": "RA2", "question_uid": "Q1b", "page": 2, "kind": "response", "response_form": "tick-boxes",
"bounds": {"x": 0.2, "y": 0.3, "w": 0.4, "h": 0.2},
"meta": {"select_n": 2, "n_options": 5, "boxes": [{"x0": 0.2, "y0": 0.3, "fill": 0.8}]}},
{"uid": "CTX1", "question_uid": "Q1b", "page": 2, "kind": "context", "response_form": None,
"bounds": {"x": 0.1, "y": 0.1, "w": 0.6, "h": 0.15}},
{"uid": "ORPH", "question_uid": "GHOST", "page": 1, "kind": "response", "response_form": "lines",
"bounds": {"x": 0.1, "y": 0.5, "w": 0.5, "h": 0.1}}, # orphan owner → must be dropped
],
"boundaries": [
{"question_uid": "Q1", "label": "1", "page_index": 0, "y": 0.18, "confidence": 0.85},
],
},
"meta": {"n_pages": 2},
}
def test_contract_maps_to_canvas_rows(monkeypatch):
monkeypatch.setattr(T, "_pdf_page_geometry", lambda _b: _GEOM)
rows = T._map_service_contract_to_rows(TID, _CONTRACT, b"%PDF-1.4")
q = rows["questions"]
assert len(q) == 3
container = next(x for x in q if x["label"] == "1")
a = next(x for x in q if x["label"] == "1(a)")
assert container["is_container"] is True and container["parent_id"] is None
assert a["parent_id"] == container["id"] # parent remapped to the container's per-template id
assert a["answer_type"] == "short" and a["max_marks"] == 3
assert all(x["source"] == "ai" and x["confirmed"] is False for x in q)
ra = rows["response_areas"]
assert len(ra) == 3 # orphan (owner GHOST) dropped
ids = {r["id"] for r in ra}
assert len(ids) == 3 # ids unique
box = next(r for r in ra if r["response_form"] == "answer-box")
# page-fraction → 780-canvas: x=0.1*780=78, y=0.2*1000=200, w=0.5*780=390, h=0.05*1000=50
assert box["bounds"] == {"x": 78.0, "y": 200.0, "w": 390.0, "h": 50.0}
assert box["meta"]["unit"] == "m/s" # rich meta preserved
tick = next(r for r in ra if r["response_form"] == "tick-boxes")
# page 2 y stacked: 0.3*1000 + page_top(1000) = 1300
assert tick["bounds"]["y"] == 1300.0 and tick["meta"]["select_n"] == 2
ctx = next(r for r in ra if r["kind"] == "context")
assert ctx["response_form"] is None # context carries no answer form
assert all(r["question_id"] in {x["id"] for x in q} for r in ra) # FK-safe
b = rows["boundaries"]
assert len(b) == 1 and b[0]["y"] == 180.0 and b[0]["question_id"] == container["id"]
+62
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@@ -642,6 +642,35 @@ def test_auto_map_fast_path_merges_ai_rows_and_returns_detail(monkeypatch):
assert store["exam_boundaries"] and store["exam_boundaries"][0]["derivation"] == "docling-main-band"
def test_auto_map_surfaces_born_digital_part_marks(monkeypatch):
# Regression: the born-digital grammar parses per-part marks, but the row mapper hardcoded
# max_marks=0. A part band carrying `marks` must flow through to the question row's max_marks.
store = _template_with_source()
store.update({"exam_questions": [], "exam_response_areas": [], "exam_boundaries": [], "exam_template_layout": []})
client, store = make_client(store=store)
fp = _first_pass_template()
fp["pages"]["1"]["part_bands"][0]["marks"] = 4
_patch_auto_map(monkeypatch, store, fast=True)
monkeypatch.setattr(templates_mod, "auto_map", lambda *_a, **_k: fp) # override with the marked part band
assert client.post("/api/exam/templates/t1/auto-map").status_code == 200
part = next(q for q in store["exam_questions"] if q.get("label") == "01.1")
assert part["max_marks"] == 4
def test_auto_map_deduplicates_repeated_response_area_ids(monkeypatch):
store = _template_with_source()
client, store = make_client(store=store)
_patch_auto_map(monkeypatch, store, fast=True)
dup = {"page_index": 0, "bbox": {"l": 50, "t": 700, "r": 100, "b": 680, "coord_origin": "BOTTOMLEFT"}, "region_type": "answer_lines", "confidence": 0.9}
monkeypatch.setattr(templates_mod, "detect_response_regions_from_pdf", lambda *_a, **_k: [dup, dict(dup)])
resp = client.post("/api/exam/templates/t1/auto-map")
assert resp.status_code == 200
response_area_ids = [r["id"] for r in store["exam_response_areas"]]
assert len(response_area_ids) == len(set(response_area_ids))
def test_auto_map_preserves_manual_and_confirmed_rows_on_rerun(monkeypatch):
store = _template_with_source()
store.update({
@@ -660,6 +689,27 @@ def test_auto_map_preserves_manual_and_confirmed_rows_on_rerun(monkeypatch):
assert "old-ai" not in ids
def test_auto_map_rerun_after_confirm_does_not_pk_collide(monkeypatch):
# Regression: a confirmed ghost keeps its DETERMINISTIC uuid5 id, which auto-map re-emits on a
# re-run — the old code re-inserted that id and PK-collided. Use the real generated id (not an
# arbitrary one, unlike the test above) so the collision path is actually exercised.
store = _template_with_source()
store.update({"exam_questions": [], "exam_response_areas": [], "exam_boundaries": [], "exam_template_layout": []})
client, store = make_client(store=store)
_patch_auto_map(monkeypatch, store, fast=True)
assert client.post("/api/exam/templates/t1/auto-map").status_code == 200
ghost_id = next(q["id"] for q in store["exam_questions"] if q["source"] == "ai")
# teacher confirms that ghost (row kept, deterministic id unchanged)
for q in store["exam_questions"]:
if q["id"] == ghost_id:
q["confirmed"] = True
# re-run auto-map: must not re-insert the same id, and must preserve the teacher's confirmation
assert client.post("/api/exam/templates/t1/auto-map").status_code == 200
same = [r for r in store["exam_questions"] if r["id"] == ghost_id]
assert len(same) == 1, "confirmed ghost must not be duplicated (PK collision) on re-run"
assert same[0]["confirmed"] is True, "teacher's confirmation must survive a re-run"
def test_auto_map_non_owner_is_403_before_download(monkeypatch):
store = _template_with_source(owner=OTHER_TEACHER)
client, store = make_client(user_id=TEACHER, institute_ids=(INST_A,), store=store)
@@ -704,4 +754,16 @@ def test_auto_map_ocr_returns_job_id_and_status_completes(monkeypatch):
body = status.json()
assert body["status"] == "completed"
assert body["counts"]["questions"] >= 2
def test_auto_map_ocr_path_projects_to_neo4j(monkeypatch, _stub_projection):
# Image-only papers route through the async OCR job; regression: that path must project to Neo4j
# like the born-digital fast path, or the graph is never built for the primary target.
store = _template_with_source()
client, store = make_client(store=store)
_patch_auto_map(monkeypatch, store, fast=False)
resp = client.post("/api/exam/templates/t1/auto-map")
assert resp.status_code == 202
# the BackgroundTask runs after the response under TestClient
assert "t1" in _stub_projection
assert body["template"]["layout"]