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pdf-inspector/napi/src/lib.rs
T
Abimael MartellandClaude Opus 4.6 20f24d1f8d
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extractPagesMarkdown: return classification metadata (0.7.0) (#32)
Combine per-page markdown extraction with layout classification into a
single parse. extractPagesMarkdown now returns PagesExtractionResult with
pages_with_tables, pages_with_columns, pages_needing_ocr, and is_complex
alongside the per-page markdown — eliminating redundant PDF parses for
callers that need both.

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 13:08:07 -07:00

415 lines
13 KiB
Rust

#![deny(clippy::all)]
use napi::bindgen_prelude::*;
use napi_derive::napi;
use std::collections::HashSet;
use std::panic;
// ---------------------------------------------------------------------------
// Enums
// ---------------------------------------------------------------------------
/// PDF document type classification.
#[napi(string_enum)]
pub enum PdfType {
TextBased,
Scanned,
ImageBased,
Mixed,
}
/// Type of a positioned text item.
#[napi(string_enum)]
pub enum ItemType {
Text,
Image,
Link,
FormField,
}
// ---------------------------------------------------------------------------
// Result types
// ---------------------------------------------------------------------------
/// Full PDF processing result with markdown and metadata.
#[napi(object)]
pub struct PdfResult {
pub pdf_type: PdfType,
pub markdown: Option<String>,
pub page_count: u32,
pub processing_time_ms: u32,
/// 1-indexed page numbers that need OCR.
pub pages_needing_ocr: Vec<u32>,
pub title: Option<String>,
pub confidence: f64,
pub is_complex_layout: bool,
pub pages_with_tables: Vec<u32>,
pub pages_with_columns: Vec<u32>,
pub has_encoding_issues: bool,
}
/// Lightweight PDF classification result.
#[napi(object)]
pub struct PdfClassification {
pub pdf_type: PdfType,
pub page_count: u32,
/// 0-indexed page numbers that need OCR.
pub pages_needing_ocr: Vec<u32>,
pub confidence: f64,
}
/// A positioned text item extracted from a PDF.
#[napi(object)]
pub struct TextItem {
pub text: String,
pub x: f64,
pub y: f64,
pub width: f64,
pub height: f64,
pub font: String,
pub font_size: f64,
pub page: u32,
pub is_bold: bool,
pub is_italic: bool,
pub item_type: ItemType,
/// URL for link items, `None` for other types.
pub link_url: Option<String>,
}
/// A page's regions for text extraction: (page_index_0based, bboxes).
#[napi(object)]
pub struct PageRegions {
pub page: u32,
/// Each bbox is [x1, y1, x2, y2] in PDF points, top-left origin.
pub regions: Vec<Vec<f64>>,
}
/// Extracted text for a single region.
#[napi(object)]
pub struct RegionText {
pub text: String,
/// `true` when the text should not be trusted (empty, GID fonts, garbage, encoding issues).
pub needs_ocr: bool,
}
/// Extracted text for one page's regions.
#[napi(object)]
pub struct PageRegionTexts {
pub page: u32,
pub regions: Vec<RegionText>,
}
// ---------------------------------------------------------------------------
// Helpers
// ---------------------------------------------------------------------------
fn convert_pdf_type(t: pdf_inspector::PdfType) -> PdfType {
match t {
pdf_inspector::PdfType::TextBased => PdfType::TextBased,
pdf_inspector::PdfType::Scanned => PdfType::Scanned,
pdf_inspector::PdfType::ImageBased => PdfType::ImageBased,
pdf_inspector::PdfType::Mixed => PdfType::Mixed,
}
}
fn to_napi_result(r: pdf_inspector::PdfProcessResult) -> PdfResult {
PdfResult {
pdf_type: convert_pdf_type(r.pdf_type),
markdown: r.markdown,
page_count: r.page_count,
processing_time_ms: r.processing_time_ms as u32,
pages_needing_ocr: r.pages_needing_ocr,
title: r.title,
confidence: r.confidence as f64,
is_complex_layout: r.layout.is_complex,
pages_with_tables: r.layout.pages_with_tables,
pages_with_columns: r.layout.pages_with_columns,
has_encoding_issues: r.has_encoding_issues,
}
}
fn convert_item_type(t: &pdf_inspector::types::ItemType) -> (ItemType, Option<String>) {
match t {
pdf_inspector::types::ItemType::Text => (ItemType::Text, None),
pdf_inspector::types::ItemType::Image => (ItemType::Image, None),
pdf_inspector::types::ItemType::Link(url) => (ItemType::Link, Some(url.clone())),
pdf_inspector::types::ItemType::FormField => (ItemType::FormField, None),
}
}
fn to_napi_err(e: impl std::fmt::Display, ctx: &str) -> Error {
Error::new(Status::GenericFailure, format!("{ctx}: {e}"))
}
/// Run a closure, catching any Rust panic and converting it to a NAPI error.
/// Prevents process abort from unwind panics in the native module.
fn catch_panic<F, T>(ctx: &str, f: F) -> Result<T>
where
F: FnOnce() -> Result<T> + panic::UnwindSafe,
{
match panic::catch_unwind(f) {
Ok(result) => result,
Err(payload) => {
let msg = if let Some(s) = payload.downcast_ref::<&str>() {
s.to_string()
} else if let Some(s) = payload.downcast_ref::<String>() {
s.clone()
} else {
"unknown panic".to_string()
};
Err(Error::new(
Status::GenericFailure,
format!("{ctx}: Rust panic: {msg}"),
))
}
}
}
// ---------------------------------------------------------------------------
// Public NAPI API
// ---------------------------------------------------------------------------
/// Process a PDF from a Buffer: detect type, extract text, and convert to Markdown.
#[napi]
pub fn process_pdf(buffer: Buffer, pages: Option<Vec<u32>>) -> Result<PdfResult> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("process_pdf", move || {
let mut opts = pdf_inspector::PdfOptions::new();
if let Some(p) = pages {
opts = opts.pages(p);
}
let result = pdf_inspector::process_pdf_mem_with_options(&bytes, opts)
.map_err(|e| to_napi_err(e, "process_pdf"))?;
Ok(to_napi_result(result))
})
}
/// Fast detection only — no text extraction or markdown.
#[napi]
pub fn detect_pdf(buffer: Buffer) -> Result<PdfResult> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("detect_pdf", move || {
let result =
pdf_inspector::detect_pdf_mem(&bytes).map_err(|e| to_napi_err(e, "detect_pdf"))?;
Ok(to_napi_result(result))
})
}
/// Lightweight PDF classification — returns type, page count, and OCR pages.
/// Faster than detectPdf as it skips building the full PdfResult.
/// Pages in pagesNeedingOcr are 0-indexed.
#[napi]
pub fn classify_pdf(buffer: Buffer) -> Result<PdfClassification> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("classify_pdf", move || {
let result =
pdf_inspector::classify_pdf_mem(&bytes).map_err(|e| to_napi_err(e, "classify_pdf"))?;
Ok(PdfClassification {
pdf_type: convert_pdf_type(result.pdf_type),
page_count: result.page_count,
pages_needing_ocr: result.pages_needing_ocr,
confidence: result.confidence as f64,
})
})
}
/// Extract plain text from a PDF Buffer.
#[napi]
pub fn extract_text(buffer: Buffer) -> Result<String> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("extract_text", move || {
pdf_inspector::extractor::extract_text_mem(&bytes)
.map_err(|e| to_napi_err(e, "extract_text"))
})
}
/// Extract text with position information from a PDF Buffer.
#[napi]
pub fn extract_text_with_positions(
buffer: Buffer,
pages: Option<Vec<u32>>,
) -> Result<Vec<TextItem>> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("extract_text_with_positions", move || {
let items = match pages {
Some(p) => {
let page_set: HashSet<u32> = p.into_iter().collect();
pdf_inspector::extractor::extract_text_with_positions_mem_pages(
&bytes,
Some(&page_set),
)
.map_err(|e| to_napi_err(e, "extract_text_with_positions"))?
}
None => pdf_inspector::extractor::extract_text_with_positions_mem(&bytes)
.map_err(|e| to_napi_err(e, "extract_text_with_positions"))?,
};
Ok(items
.into_iter()
.map(|item| {
let (item_type, link_url) = convert_item_type(&item.item_type);
TextItem {
text: item.text,
x: item.x as f64,
y: item.y as f64,
width: item.width as f64,
height: item.height as f64,
font: item.font,
font_size: item.font_size as f64,
page: item.page,
is_bold: item.is_bold,
is_italic: item.is_italic,
item_type,
link_url,
}
})
.collect())
})
}
/// Extract text within bounding-box regions from a PDF.
///
/// For hybrid OCR: layout model detects regions in rendered images,
/// this extracts PDF text within those regions — skipping GPU OCR
/// for text-based pages.
///
/// Each region result includes `needsOcr` — set when the extracted text
/// is unreliable (empty, GID-encoded fonts, garbage, encoding issues).
///
/// Coordinates are PDF points with top-left origin.
#[napi]
pub fn extract_text_in_regions(
buffer: Buffer,
page_regions: Vec<PageRegions>,
) -> Result<Vec<PageRegionTexts>> {
let bytes: Vec<u8> = buffer.to_vec();
let regions = parse_page_regions(&page_regions);
catch_panic("extract_text_in_regions", move || {
let results = pdf_inspector::extract_text_in_regions_mem(&bytes, &regions)
.map_err(|e| to_napi_err(e, "extract_text_in_regions"))?;
Ok(to_page_region_texts(results))
})
}
/// Extract markdown tables within bounding-box regions from a PDF.
///
/// Like `extractTextInRegions` but runs table detection on items within each
/// region and returns markdown pipe-tables instead of flat text.
///
/// When table structure is detected, `text` contains a markdown pipe-table and
/// `needsOcr` is `false`. When no table is found, `text` is empty and
/// `needsOcr` is `true` so the caller can fall back to GPU OCR.
///
/// Coordinates are PDF points with top-left origin.
#[napi]
pub fn extract_tables_in_regions(
buffer: Buffer,
page_regions: Vec<PageRegions>,
) -> Result<Vec<PageRegionTexts>> {
let bytes: Vec<u8> = buffer.to_vec();
let regions = parse_page_regions(&page_regions);
catch_panic("extract_tables_in_regions", move || {
let results = pdf_inspector::extract_tables_in_regions_mem(&bytes, &regions)
.map_err(|e| to_napi_err(e, "extract_tables_in_regions"))?;
Ok(to_page_region_texts(results))
})
}
/// Per-page markdown extraction result.
#[napi(object)]
pub struct PageMarkdownResult {
/// 0-indexed page number.
pub page: u32,
/// Formatted markdown for this page.
pub markdown: String,
/// `true` when text on this page is unreliable.
pub needs_ocr: bool,
}
/// Combined per-page markdown extraction and layout classification result.
#[napi(object)]
pub struct PagesExtractionResult {
/// Per-page markdown results.
pub pages: Vec<PageMarkdownResult>,
/// 1-indexed pages where tables were detected.
pub pages_with_tables: Vec<u32>,
/// 1-indexed pages where multi-column layout was detected.
pub pages_with_columns: Vec<u32>,
/// 1-indexed pages that need OCR (scanned/image-based).
pub pages_needing_ocr: Vec<u32>,
/// True if any page has tables or columns.
pub is_complex: bool,
}
/// Extract formatted markdown for specific pages of a PDF, with layout
/// classification metadata.
///
/// Returns per-page markdown and classification data (tables, columns,
/// OCR needs) from a single parse. Font statistics are computed from the
/// full document so header detection is consistent across pages.
#[napi]
pub fn extract_pages_markdown(
buffer: Buffer,
pages: Vec<u32>,
) -> Result<PagesExtractionResult> {
let bytes: Vec<u8> = buffer.to_vec();
catch_panic("extract_pages_markdown", move || {
let result = pdf_inspector::extract_pages_markdown_mem(&bytes, &pages)
.map_err(|e| to_napi_err(e, "extract_pages_markdown"))?;
Ok(PagesExtractionResult {
pages: result
.pages
.into_iter()
.map(|r| PageMarkdownResult {
page: r.page,
markdown: r.markdown,
needs_ocr: r.needs_ocr,
})
.collect(),
pages_with_tables: result.pages_with_tables,
pages_with_columns: result.pages_with_columns,
pages_needing_ocr: result.pages_needing_ocr,
is_complex: result.is_complex,
})
})
}
fn parse_page_regions(page_regions: &[PageRegions]) -> Vec<(u32, Vec<[f32; 4]>)> {
page_regions
.iter()
.map(|pr| {
let bboxes: Vec<[f32; 4]> = pr
.regions
.iter()
.map(|r| {
if r.len() != 4 {
[0.0, 0.0, 0.0, 0.0]
} else {
[r[0] as f32, r[1] as f32, r[2] as f32, r[3] as f32]
}
})
.collect();
(pr.page, bboxes)
})
.collect()
}
fn to_page_region_texts(results: Vec<pdf_inspector::PageRegionResult>) -> Vec<PageRegionTexts> {
results
.into_iter()
.map(|page_result| PageRegionTexts {
page: page_result.page,
regions: page_result
.regions
.into_iter()
.map(|r| RegionText {
text: r.text,
needs_ocr: r.needs_ocr,
})
.collect(),
})
.collect()
}