Guard untyped bbox jsonb with shared normalizeImageBbox helper

scripts/enrich-documents.ts

@@ -293,6 +293,7 @@ async function classifyExistingImages(supabase: SupabaseAdmin, documentId: strin
  classifiedImageSkipReason,
  clinicalImagePolicyVersion,
  lightweightPerceptualHash,
+ normalizeImageBbox,
  },
  { classifyAndCaptionImageFromBase64 },
  ] = await Promise.all([import("@/lib/env"), import("@/lib/image-filtering"), import("@/lib/openai")]);
@@ -336,7 +337,7 @@ async function classifyExistingImages(supabase: SupabaseAdmin, documentId: strin
  imageHash,
  seenHashes,
  image: {
- bbox: image.bbox as [number, number, number, number] | null,
+ bbox: normalizeImageBbox(image.bbox),
  width: image.width,
  height: image.height,
  sourceKind: image.source_kind as

src/lib/image-filtering.ts

@@ -274,9 +274,16 @@ export function isClinicalImageEvidence(image: {
  return assessment.clinical_use_class === "clinical_evidence";
 }
 
-function bboxLooksLikeHeaderOrFooter(bbox: ExtractedImage["bbox"]) {
- if (!bbox) return false;
- const [, y0, , y1] = bbox;
+export function normalizeImageBbox(value: unknown): [number, number, number, number] | null {
+ if (!Array.isArray(value) || value.length !== 4) return null;
+ const coords = value.map((entry) => Number(entry));
+ return coords.every(Number.isFinite) ? (coords as [number, number, number, number]) : null;
+}
+
+function bboxLooksLikeHeaderOrFooter(bbox: unknown) {
+ const coords = normalizeImageBbox(bbox);
+ if (!coords) return false;
+ const [, y0, , y1] = coords;
  const height = Math.abs(y1 - y0);
  if (height > 110) return false;
  return y1 < 105 || y0 > 705;

src/lib/rag.ts

@@ -35,7 +35,7 @@ import { logger } from "@/lib/logger";
 import { queryCacheKeyForStorage, queryPrivacyMetadata, queryTextForStorage } from "@/lib/query-privacy";
 import { normalizeSourceMetadata } from "@/lib/source-metadata";
 import { isReviewedTablePromotable } from "@/lib/table-review";
-import { isClinicalImageEvidence } from "@/lib/image-filtering";
+import { isClinicalImageEvidence, normalizeImageBbox } from "@/lib/image-filtering";
 import { chooseAnswerRoute, hasDirectTitleSupport, shouldRetryWithStrongAfterFast } from "@/lib/rag-routing";
 import { fetchRelatedDocumentMetadata, fetchRelatedDocuments } from "@/lib/document-enrichment";
 import { boldHighYieldClinicalText, boldRagAnswerHighYieldText, rankAnswerEvidence } from "@/lib/answer-ranking";
@@ -3165,7 +3165,7 @@ async function attachPageVisualEvidence(
  page_number: image.page_number,
  storage_path: image.storage_path,
  caption: image.caption,
- bbox: image.bbox as ChunkImage["bbox"],
+ bbox: normalizeImageBbox(image.bbox),
  image_type: image.image_type as ChunkImage["image_type"],
  searchable: image.searchable,
  clinical_relevance_score: image.clinical_relevance_score,

tests/image-filtering.test.ts

@@ -5,6 +5,7 @@ import {
  classifiedImageSkipReason,
  isClinicalImageEvidence,
  lightweightPerceptualHash,
+ normalizeImageBbox,
 } from "../src/lib/image-filtering";
 
 describe("smart image filtering", () => {
@@ -42,6 +43,33 @@ describe("smart image filtering", () => {
  ).toBeNull();
  });
 
+ it("ignores object-shaped bbox jsonb instead of crashing", () => {
+ expect(
+ cheapImageSkipReason({
+ bytesLength: 20_000,
+ imageHash: "obj",
+ seenHashes: new Set(),
+ image: {
+ sourceKind: "embedded",
+ width: 600,
+ height: 400,
+ bbox: { x0: 20, y0: 20, x1: 180, y1: 80 } as unknown as [number, number, number, number],
+ },
+ }),
+ ).toBeNull();
+ });
+
+ it("normalizes bbox jsonb to a four-number tuple or null", () => {
+ expect(normalizeImageBbox([20, 20, 180, 80])).toEqual([20, 20, 180, 80]);
+ expect(normalizeImageBbox(["20", "20", "180", "80"])).toEqual([20, 20, 180, 80]);
+ expect(normalizeImageBbox({ x0: 20, y0: 20, x1: 180, y1: 80 })).toBeNull();
+ expect(normalizeImageBbox([20, 20, 180])).toBeNull();
+ expect(normalizeImageBbox([20, 20, 180, "wide"])).toBeNull();
+ expect(normalizeImageBbox([20, 20, 180, Number.NaN])).toBeNull();
+ expect(normalizeImageBbox("20,20,180,80")).toBeNull();
+ expect(normalizeImageBbox(null)).toBeNull();
+ });
+
  it("keeps relevant clinical classifications searchable", () => {
  expect(
  classifiedImageSkipReason({