| """BBox DocVQA importer — optional, dual-gate source. |
| |
| This source is only enabled when *both* the license and storage approval gates |
| are cleared (``docs/01`` §3.5, ``docs/02`` §4). The core pipeline must run |
| without it, so the importer exposes :func:`is_enabled` and the driver skips it |
| with a reason when a gate is still blocked — it is never silently substituted or |
| faked. Rows carry an evidence bounding box recorded in provenance for later |
| grounding. |
| """ |
|
|
| from __future__ import annotations |
|
|
| from collections.abc import Mapping |
| from typing import Any |
|
|
| from ..hashing import canonical_json, sha256_bytes |
| from .base import ( |
| ImageResolver, |
| ImageStore, |
| IngestError, |
| NormalizedItem, |
| Policy, |
| make_item, |
| ) |
|
|
| NAME = "bbox_docvqa_train" |
| POLICY: Policy = "c2_train_candidate" |
| ALLOWED_SPLIT = "train" |
| REQUIRED_GATES = ("bbox_docvqa_license", "bbox_docvqa_storage") |
|
|
|
|
| def is_enabled(approval: Mapping[str, Mapping[str, Any]]) -> bool: |
| """True only when both required gates are approved.""" |
| return all(approval.get(gate, {}).get("status") == "approved" for gate in REQUIRED_GATES) |
|
|
|
|
| def block_reason(approval: Mapping[str, Mapping[str, Any]]) -> str | None: |
| """Return why the importer is disabled, or ``None`` when enabled.""" |
| unmet = [g for g in REQUIRED_GATES if approval.get(g, {}).get("status") != "approved"] |
| if not unmet: |
| return None |
| return f"approval gates not approved: {', '.join(unmet)}" |
|
|
|
|
| def normalize( |
| row: Mapping[str, Any], |
| images: ImageStore, |
| resolve: ImageResolver, |
| *, |
| revision: str, |
| split: str, |
| config: str = "default", |
| ) -> NormalizedItem: |
| """Normalize one BBox DocVQA native row to a :class:`NormalizedItem`.""" |
| if split != ALLOWED_SPLIT: |
| raise IngestError( |
| f"bbox_docvqa_train: only split {ALLOWED_SPLIT!r} may be ingested, got {split!r}" |
| ) |
| question = str(row["question"]) |
| answers = row["answers"] |
| if isinstance(answers, (list, tuple)): |
| answer_raw = str(answers[0]) if answers else "" |
| else: |
| answer_raw = str(answers) |
| if not answer_raw: |
| raise IngestError(f"bbox_docvqa_train: row {row.get('id', '?')!r} has no answer") |
| image_ref = str(row["image"]) |
| rel, digest = images.store(resolve(image_ref)) |
| extra: dict[str, Any] = {} |
| box = row.get("evidence_box") |
| if box is not None: |
| extra["evidence_box_sha256"] = sha256_bytes(canonical_json(box).encode("utf-8")) |
| extra["evidence_box"] = list(box) |
| native_id = str(row.get("id", row.get("index"))) |
| return make_item( |
| source=NAME, |
| source_revision=revision, |
| source_config=config, |
| source_split=split, |
| source_native_id=native_id, |
| question=question, |
| choices=(), |
| answer_raw=answer_raw, |
| answer_canonical=answer_raw, |
| answer_type="short_text", |
| image_paths=(rel,), |
| image_sha256=(digest,), |
| policy=POLICY, |
| native_row=row, |
| extra_provenance=extra, |
| ) |
|
|
