api/services/docling/bands.py

@@ -67,13 +67,11 @@ 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 = {}
@@ -106,8 +104,7 @@ 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"),

api/services/docling/template.py

@@ -159,7 +159,6 @@ 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 {}

docker-compose.dev.yml

@@ -55,8 +55,6 @@ 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:

modules/services/exam_extract.py

@@ -1,86 +0,0 @@
-"""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)

routers/exam/__init__.py

@@ -8,13 +8,9 @@ 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"]

routers/exam/bank.py

@@ -1,152 +0,0 @@
-"""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)}

routers/exam/corpus.py

@@ -1,98 +0,0 @@
-"""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}

routers/exam/schemas.py

@@ -80,9 +80,6 @@ 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)

routers/exam/templates.py

@@ -15,7 +15,6 @@ from __future__ import annotations
 import json
 import math
 import os
-import re
 import tempfile
 import time
 import uuid
@@ -31,7 +30,6 @@ 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 (
@@ -457,32 +455,6 @@ 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]])))
 
@@ -493,17 +465,6 @@ 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 []:
@@ -580,7 +541,7 @@ 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": _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"})
+            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"})
 
     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)):
@@ -641,13 +602,7 @@ def _refresh_ai_rows(ctx: ExamContext, template_id: str, rows: Dict[str, List[Di
     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")):
-        # A row that survived the delete above is confirmed-AI or manual — the teacher's curated version.
+        payload = _dedupe_rows_by_id(rows.get(key) or [])
-        # 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()
 
@@ -679,153 +634,12 @@ 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 ───────────────────────────────────────────────────────────────
 
 
@@ -1003,14 +817,6 @@ 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:
@@ -1049,24 +855,6 @@ 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,
@@ -1147,7 +935,6 @@ 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,

run/initialization/init_exam_graph.py

@@ -1,19 +1,17 @@
 """
 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
+Creates the shared, public exam database, its uniqueness constraints, and seeds the AQA exam
-+ the 6 current test specifications (GCSE & A-level Physics/Chemistry/Biology) with their top-level
+board + AQA GCSE Physics (8463) specification with its 8 top-level topic SpecPoints. Idempotent
-topic SpecPoints (44 in total). Idempotent (CREATE DATABASE IF NOT EXISTS / CREATE CONSTRAINT IF NOT
+(CREATE DATABASE IF NOT EXISTS / CREATE CONSTRAINT IF NOT EXISTS / MERGE).
-EXISTS / MERGE).
 
 Run inside the ccapi container:
     python3 -c "from run.initialization.init_exam_graph import init; import json; print(json.dumps(init()))"
 
-NOTE: only *top-level* topics are seeded (the granularity a teacher plans against). The full sub-point
+NOTE: the 8 SpecPoints seeded here are the real AQA GCSE Physics *top-level* topics. The full
-breakdown (e.g. 4.1.1.1 ...) is a later data-population task (sourceable from the AQA spec PDF via
+sub-point breakdown (e.g. 4.1.1.1 ...) is a later data-population task (sourceable from the AQA
-Docling). Seeding all 6 specs means a template's spec_ref finds a matching SpecPoint so
+spec PDF via Docling). spec_code AQA-PHYS-8463 is the standalone GCSE Physics code that matches
-(:Part)-[:ASSESSES]->(:SpecPoint) fires beyond GCSE Physics; spec_code (e.g. AQA-PHYS-8463) must match
+"AQA Physics Paper 1H"; the eb_exams/eb_specifications seed (card S4-3) must use the same code.
-the eb_exams/eb_specifications seed (card S4-3) and the app's deriveSpecCode.
 """
 import uuid
 from typing import Dict, Any
@@ -43,37 +41,6 @@ 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",
@@ -114,36 +81,35 @@ def init() -> Dict[str, Any]:
             s.run(c).consume()
             result["constraints"] += 1
 
-        # 3. board (once)
+        # 3. board + spec
         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()
-
-        # 4. each specification + its top-level spec points (idempotent MERGE)
-        for spec in SPECIFICATIONS:
-            spec_uid = _uid("Specification", spec["spec_code"])
         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"],
+            uid=spec_uid, sc=SPEC["spec_code"], ebc=SPEC["exam_board_code"],
-                subj=spec["subject_code"], award=spec["award_code"], title=spec["title"],
+            subj=SPEC["subject_code"], award=SPEC["award_code"], title=SPEC["title"],
-                nsp=f"{EXAM_DB}/Specification/{spec['spec_code']}",
+            nsp=f"{EXAM_DB}/Specification/{SPEC['spec_code']}",
         ).consume()
-            for ref, desc in spec["topics"]:
+
-                sp_uid = _uid("SpecPoint", spec["spec_code"], ref)
+        # 4. spec points
+        for ref, desc in SPEC_POINTS:
+            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"],
+                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}",
+                ebc=SPEC["exam_board_code"], nsp=f"{EXAM_DB}/SpecPoint/{SPEC['spec_code']}/{ref}",
             ).consume()
             result["spec_points"] += 1
 

tests/test_exam_bank.py

@@ -1,134 +0,0 @@
-"""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

tests/test_exam_corpus.py

@@ -1,48 +0,0 @@
-"""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}

tests/test_exam_extract_mapping.py

@@ -1,75 +0,0 @@
-"""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"]

tests/test_exam_templates.py

@@ -642,21 +642,6 @@ 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)
@@ -689,27 +674,6 @@ 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)
@@ -754,16 +718,4 @@ 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"]