feat(recibos): OCR capture for gas butano and municipal predial

Adds four parsers to the statement intake — GAS TIJUANA plus one per
municipality, because Tijuana, Rosarito and Ensenada issue three
completely different predial documents — and a text-layer fast path for
the born-digital invoices the gas company sends.

Measured against a new corpus of 14 documents / 29 pages: provider read
on 29/29, amount on 26/29, and 21/29 auto-matched against the dev
database (22/29 identified). The eight review cases are all legitimate.

Five things the corpus forced:

- Not every statement is a scan. The gas invoices are born-digital CFDIs
  whose text layer is exact; rasterising them only loses information (one
  sample turned `MEDIDOR: VM01014426` into `ar (LTR): 014420`). The new
  `OcrProvider.textPages` reads the embedded layer via `pdftotext
  -bbox-layout` — same poppler package as `pdftoppm`, so no new
  dependency — and OCR stays the fallback for real scans. Poppler's own
  `<line>` grouping follows text flow rather than the page, so words are
  regrouped by vertical position; without that, a two-column header
  leaves every label separated from the value printed beside it.

- The clave catastral is not two letters and six digits. Position three
  is a letter in 15 of the 932 stored claves, and digitising the whole
  tail mapped a real `MMB01041` to a nonexistent `MM801041`.

- Tijuana predial prints no clave at all. Its only identifier is an
  8-digit municipal account carried in a 32-digit payment barcode, which
  the legacy database never held, so it goes in `meterNumber` alongside
  gas — `accountNumber` holds `DATMEX.predial`, which is not a
  per-property key and must not be overwritten. Those pages start cold
  and are taught by the first confirm.

- On Rosarito and Ensenada the clave is the primary key, not a fallback:
  those receipts print nothing else, so a unique hit auto-matches. On a
  utility bill that merely happens to print one it stays a review hint.

- A misread `$` is the dangerous failure. An Ensenada receipt for
  $2,203.00 OCR'd as `82,203.00`, which would post a charge 37x too large
  and look ordinary in the ledger. Predial amounts now require a literal
  `$` and a page that cannot produce one goes to review.

The scoped match field is now one exported function rather than three
copies of `kind === "GAS" ? ... : ...`, since the lookup, the
blank-service fill and the confirm write-back have to agree or a
reference gets learned into a column nothing searches.

First tests in this package: 23 specs over the parsers and the text-layer
reader, every fixture a verbatim OCR excerpt from a real receipt. Adds
the jest config they need and a build tsconfig so they stay out of dist.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

apps/api/src/statements/statements.service.ts

@@ -16,7 +16,7 @@ import { BillingService } from "../billing/billing.service";
 import type { UploadedFileLike } from "../storage/upload-file";
 import { OCR_PROVIDER, type OcrProvider } from "./ocr/ocr.provider";
 import { parseStatement } from "./parsers/statement-parser";
-import { StatementMatcherService } from "./statement-matcher.service";
+import { StatementMatcherService, scopedRefField } from "./statement-matcher.service";
 import type { ConfirmBatchDto, ReviewDocumentDto } from "./statement.dto";
 
 /**
@@ -127,14 +127,23 @@ export class StatementsService {
       await this.storage.put(sourceKey, file.buffer, "application/pdf");
 
       const pages = await this.ocr.renderPages(file.buffer);
-      for (const image of pages) {
+      // Page images are still rendered and stored for every file, text layer or
+      // not: the review screen shows the reviewer the page, and "what the
+      // parser read" is only checkable against a picture of the paper.
+      const textLayer = await this.ocr.textPages(file.buffer).catch(() => []);
+
+      for (const [index, image] of pages.entries()) {
         pageNumber += 1;
         const storageKey = `statement/${batchId}/page-${pageNumber}.png`;
         await this.storage.put(storageKey, image, "image/png");
 
         try {
-          const ocr = await this.ocr.recognize(image);
+          const embedded = textLayer[index] ?? null;
+          const ocr = embedded ?? (await this.ocr.recognize(image));
           const parsed = parseStatement(ocr);
+          if (embedded) {
+            parsed.notes.unshift("texto leído del PDF original, sin OCR");
+          }
           const match = await this.matcher.match(parsed, serviceKind);
 
           const notes = [...parsed.notes, match.note].filter(Boolean);
@@ -295,8 +304,8 @@ export class StatementsService {
         where: { id: doc.batchId },
         select: { serviceKind: true },
       });
-      if (batch) {
-        const field = batch.serviceKind === "GAS" ? "meterNumber" : "accountNumber";
+      const field = batch && scopedRefField(batch.serviceKind);
+      if (batch && field) {
         const blank = await this.prisma.propertyService.findMany({
           where: {
             kind: batch.serviceKind,
@@ -434,7 +443,8 @@ export class StatementsService {
     docs: { matchedPropertyServiceId: string | null; extractedAccountRef: string | null }[],
     kind: ServiceKind,
   ) {
-    const field = kind === "GAS" ? "meterNumber" : "accountNumber";
+    const field = scopedRefField(kind);
+    if (!field) return;
     for (const d of docs) {
       if (!d.matchedPropertyServiceId || !d.extractedAccountRef) continue;
       await this.prisma.propertyService.updateMany({