Files
pdf-inspector/napi
Abimael MartellandClaude Opus 4.7 7539868bf8 extract_tables: reject partial extractions in needs_ocr gate (#87)
After enabling the vector-grid detectors on the extract path (#85)
and broadening detection to full-page grids (#83), long-cell tables
(#84), and segment-only layouts (#86), one residual failure shape
remained: detectors finding a valid grid but only capturing a small
fraction of the region's actual text. Two recurring sub-shapes:

  - "header-only": detector captured the column-header band (often a
    multi-line year/units block) but missed every data row below.
    Common in financial statements, securities tables, budget
    appendices.
  - "sparse": detector returned a handful of fragmentary cells from a
    content-rich region, missing the bulk of the page.

Both pass the existing needs_ocr quality gates — the captured cells
are well-formed markdown — but the customer would receive a 5-row
fragment of a 50-row table. Today these regions fell back to GLM-OCR
by default; flipping `__nativeTableExtraction=true` would start
serving the partials.

Add `captured_only_a_fragment(md, region_text_chars)`: rejects when
the captured non-delimiter character count is less than 25% of the
text the page extractor saw inside the region. The 200-char region
floor keeps short legitimate tables (units, axis labels) from being
mis-flagged. Wired into the existing `evaluate` quality gate
alongside is_garbage_text / is_cid_garbage / detect_encoding_issues
/ looks_like_partial_table_ex.

Verified against three representative residual cases from shadow
logs (financial-statement header band, securities-table fragment,
ESIA sparse region): all flip from `needs_ocr=false` with partial
output to `needs_ocr=true` so GLM takes over. Existing full-table
fixtures (governmental ledger, PPRA-style key/value, archival
catalog) still pass through unchanged.

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-14 14:20:02 -04:00
..

PDF Inspector

Fast PDF classification and region-based text extraction for Node.js/Bun. Native Rust performance via napi-rs.

Built by Firecrawl for hybrid OCR pipelines — extract text from PDF structure where possible, fall back to OCR only when needed.

Install

npm install @firecrawl/pdf-inspector
# or
bun add @firecrawl/pdf-inspector

Prebuilt binaries included for linux-x64 and macOS ARM64. No Rust toolchain needed.

API

classifyPdf(buffer: Buffer): PdfClassification

Classify a PDF as TextBased, Scanned, Mixed, or ImageBased (~10-50ms). Returns which pages need OCR.

import { classifyPdf } from '@firecrawl/pdf-inspector'
import { readFileSync } from 'fs'

const pdf = readFileSync('document.pdf')
const result = classifyPdf(pdf)

console.log(result.pdfType)        // "TextBased" | "Scanned" | "Mixed" | "ImageBased"
console.log(result.pageCount)      // 42
console.log(result.pagesNeedingOcr) // [5, 12, 15] (0-indexed)
console.log(result.confidence)     // 0.875

extractTextInRegions(buffer: Buffer, pageRegions: PageRegions[]): PageRegionTexts[]

Extract text within bounding-box regions from a PDF. Designed for hybrid OCR pipelines where a layout model detects regions in rendered page images, and this function extracts text from the PDF structure for text-based pages — skipping GPU OCR.

Each region result includes a needsOcr flag that signals unreliable extraction (empty text, GID-encoded fonts, garbage text, encoding issues).

import { extractTextInRegions } from '@firecrawl/pdf-inspector'

const result = extractTextInRegions(pdf, [
  {
    page: 0, // 0-indexed
    regions: [
      [0, 0, 300, 400],    // [x1, y1, x2, y2] in PDF points, top-left origin
      [300, 0, 612, 400],
    ]
  }
])

for (const region of result[0].regions) {
  if (region.needsOcr) {
    // Unreliable text — send this region to OCR instead
  } else {
    console.log(region.text) // Extracted text in reading order
  }
}

Types

interface PdfClassification {
  pdfType: string          // "TextBased" | "Scanned" | "Mixed" | "ImageBased"
  pageCount: number
  pagesNeedingOcr: number[] // 0-indexed page numbers
  confidence: number        // 0.0 - 1.0
}

interface PageRegions {
  page: number              // 0-indexed
  regions: number[][]       // [[x1, y1, x2, y2], ...] in PDF points, top-left origin
}

interface PageRegionTexts {
  page: number
  regions: RegionText[]
}

interface RegionText {
  text: string
  needsOcr: boolean         // true when text is unreliable
}

Platforms

Platform Architecture Supported
Linux x64 Yes
macOS ARM64 Yes

License

MIT