@localmode/pdfjs

PDF text extraction using PDF.js for local document processing. Extract text, metadata, and structure from PDFs entirely in the browser.

Features

📄 Full PDF Support — Extract text from any PDF document
🔒 Password Protected — Handle encrypted PDFs
📑 Page-Level Control — Process specific pages or split by page
📊 Metadata Extraction — Get title, author, dates, etc.

Installation

bash pnpm install @localmode/pdfjs @localmode/core

bash npm install @localmode/pdfjs @localmode/core

bash yarn add @localmode/pdfjs @localmode/core

Quick Start

import { extractPDFText } from '@localmode/pdfjs';

// From file input
const file = document.getElementById('fileInput').files[0];

const { text, pageCount, metadata } = await extractPDFText(file);

console.log(`Extracted ${pageCount} pages`);
console.log('Title:', metadata?.title);
console.log('Text:', text);

API Reference

extractPDFText()

Extract text from a PDF file:

import { extractPDFText } from '@localmode/pdfjs';

const result = await extractPDFText(pdfBlob, {
  maxPages: 10, // Limit pages to extract
  includePageNumbers: true, // Add [Page N] headers
  pageSeparator: '\n---\n', // Separator between pages
  password: 'secret', // For encrypted PDFs
});

console.log(result.text); // Full extracted text
console.log(result.pageCount); // Total number of pages
console.log(result.pages); // Array of page texts
console.log(result.metadata); // PDF metadata

Options

Prop

Type

Return Value

Prop

Type

PDFLoader

Document loader for integration with LocalMode core:

import { PDFLoader } from '@localmode/pdfjs';
import { loadDocument } from '@localmode/core';

const loader = new PDFLoader({
  splitByPage: false, // Single doc or one per page
  maxPages: undefined, // All pages
  includePageNumbers: true,
  password: undefined,
});

const { documents } = await loadDocument(loader, pdfBlob);

for (const doc of documents) {
  console.log(doc.text);
  console.log(doc.metadata);
}

Split by Page

Create separate documents for each page:

import { PDFLoader } from '@localmode/pdfjs';

const loader = new PDFLoader({ splitByPage: true });
const { documents } = await loadDocument(loader, pdfBlob);

console.log(`Loaded ${documents.length} pages`);

documents.forEach((doc, i) => {
  console.log(`Page ${i + 1}: ${doc.text.substring(0, 100)}...`);
  console.log(`  Metadata:`, doc.metadata);
});

Utility Functions

import { getPDFPageCount, isPDF } from '@localmode/pdfjs';

// Get page count without full extraction
const pageCount = await getPDFPageCount(pdfBlob);
console.log(`PDF has ${pageCount} pages`);

// Check if file is a PDF
if (await isPDF(file)) {
  // Process as PDF
} else {
  // Handle other file types
}

RAG Pipeline Integration

Build a PDF-powered RAG system:

import { PDFLoader } from '@localmode/pdfjs';
import { createVectorDB, chunk, ingest, semanticSearch, streamText } from '@localmode/core';
import { transformers } from '@localmode/transformers';
import { webllm } from '@localmode/webllm';

// Setup
const embeddingModel = transformers.embedding('Xenova/all-MiniLM-L6-v2');
const llm = webllm.languageModel('Llama-3.2-1B-Instruct-q4f16_1-MLC');
const db = await createVectorDB({ name: 'pdf-docs', dimensions: 384 });

// Load and process PDF
async function ingestPDF(file: File) {
  const loader = new PDFLoader({ splitByPage: true });
  const { documents } = await loadDocument(loader, file);

  // Chunk each page
  const allChunks = documents.flatMap((doc, pageIndex) =>
    chunk(doc.text, {
      strategy: 'recursive',
      size: 512,
      overlap: 50,
    }).map((c) => ({
      text: c.text,
      metadata: {
        filename: file.name,
        page: pageIndex + 1,
        start: c.startIndex,
        end: c.endIndex,
      },
    }))
  );

  // Ingest into vector DB
  await ingest({
    db,
    model: embeddingModel,
    documents: allChunks,
  });

  return allChunks.length;
}

// Query
async function queryPDF(question: string) {
  const results = await semanticSearch({
    db,
    model: embeddingModel,
    query: question,
    k: 3,
  });

  const context = results.map((r) => `[Page ${r.metadata.page}]\n${r.metadata.text}`).join('\n\n');

  const stream = await streamText({
    model: llm,
    prompt: `Answer based on the PDF content:

${context}

Question: ${question}

Answer:`,
  });

  return stream;
}

File Upload Component

React example:

import { useState } from 'react';
import { extractPDFText } from '@localmode/pdfjs';

function PDFUploader() {
  const [text, setText] = useState('');
  const [loading, setLoading] = useState(false);

  async function handleFile(e: React.ChangeEvent<HTMLInputElement>) {
    const file = e.target.files?.[0];
    if (!file) return;

    setLoading(true);
    try {
      const { text, pageCount } = await extractPDFText(file);
      setText(text);
      console.log(`Extracted ${pageCount} pages`);
    } catch (error) {
      console.error('Failed to extract PDF:', error);
    } finally {
      setLoading(false);
    }
  }

  return (
    <div>
      <input type="file" accept=".pdf" onChange={handleFile} />
      {loading && <p>Extracting text...</p>}
      {text && <pre>{text}</pre>}
    </div>
  );
}

Handling Large PDFs

For large PDFs, process in chunks:

import { extractPDFText, getPDFPageCount } from '@localmode/pdfjs';

async function processLargePDF(file: File, batchSize = 10) {
  const totalPages = await getPDFPageCount(file);
  const allText: string[] = [];

  for (let start = 0; start < totalPages; start += batchSize) {
    const { pages } = await extractPDFText(file, {
      startPage: start,
      maxPages: batchSize,
    });

    allText.push(...pages);

    console.log(
      `Processed pages ${start + 1}-${Math.min(start + batchSize, totalPages)} of ${totalPages}`
    );
  }

  return allText.join('\n\n');
}

Password-Protected PDFs

import { extractPDFText } from '@localmode/pdfjs';

try {
  const { text } = await extractPDFText(encryptedPDF, {
    password: userProvidedPassword,
  });
  console.log(text);
} catch (error) {
  if (error.message.includes('password')) {
    // Prompt user for password
  }
}

Metadata Extraction

const { metadata } = await extractPDFText(file);

if (metadata) {
  console.log('Title:', metadata.title);
  console.log('Author:', metadata.author);
  console.log('Subject:', metadata.subject);
  console.log('Creator:', metadata.creator);
  console.log('Creation Date:', metadata.creationDate);
  console.log('Modification Date:', metadata.modDate);
}

Best Practices

PDF Tips

Split by page - Better for RAG; maintains page context
Use page numbers - Include in metadata for citations
Handle errors - Corrupted PDFs, wrong passwords, etc.
Chunk appropriately - 256-512 chars works well for most PDFs
Check file size - Large PDFs may need batched processing

Overview