api/routers/exam/bank.py
Kevin Carter (via Claude) 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 <noreply@anthropic.com>
2026-07-02 22:05:39 +00:00

153 lines
6.7 KiB
Python

"""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)}