pdf-inspector/napi

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.

Features

• Smart classification — text-based / scanned / image-based / mixed in ~10–50ms, with a confidence score and per-page OCR routing.
• Region-based extraction — pull text from bounding boxes with per-region quality checks (needsOcr).
• Layout-aware — multi-column reading order, position and font info per text item, RTL support.
• Robust text decoding — CID/Type0 fonts via ToUnicode CMaps, plus automatic flagging of broken encodings so callers can fall back to OCR.
• Lightweight — native Rust core via napi-rs, no ML models, no external services; ~5–6 MB platform binary, TypeScript definitions included.

Benchmark

opendataloader-bench corpus (200 PDFs), direct-extraction engines only — no OCR, no ML. Scores 0–1, higher is better:

Engine	Overall	Reading order	Tables (TEDS)	Headings	Speed
pdf-inspector	0.83	0.88	0.66	0.74	4s
opendataloader	0.84	0.91	0.49	0.74	11s
pymupdf4llm	0.73	0.89	0.40	0.41	18s

OCR/ML engines (docling, marker, mineru) score 0.83–0.88 overall but take 2–180 minutes on the same corpus. Full numbers in the repo README.

Install

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

Prebuilt binaries for Linux x64, macOS ARM64, and Windows x64 — npm installs only the one matching your platform. 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). When the cause is a suspected garbled text layer, ocrReason is set to "suspected_garbled_text".

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
  ocrReason?: string        // "suspected_garbled_text" when known
}

Platforms

Prebuilt binaries ship as platform-specific packages installed automatically via optionalDependencies:

Platform	Architecture	Package
Linux	x64 (glibc)	@firecrawl/pdf-inspector-linux-x64-gnu
macOS	ARM64	@firecrawl/pdf-inspector-darwin-arm64
Windows	x64	@firecrawl/pdf-inspector-win32-x64-msvc

License

MIT