xberg 1.0.0-rc.26

High-performance document intelligence library

Dart / Flutter

Extract text, tables, images, metadata, and code intelligence from 97 file formats and 306 programming languages including PDF, Office documents, images, and audio/video transcripts where native transcription is available. Dart bindings via flutter_rust_bridge for both Flutter apps and pure-Dart server contexts, with isolate-safe Future/Stream APIs.

What This Package Provides

• Document intelligence core — extract text, tables, images, metadata, entities, keywords, code intelligence, and transcripts in builds that enable transcription.
• Format coverage — PDF, Office, images, HTML/XML, email, archives, notebooks, citations, scientific formats, plain text, and audio/video formats in builds that enable transcription.
• OCR choices — Tesseract, PaddleOCR, Candle where supported, VLM OCR through liter-llm, and plugin hooks for custom backends.
• Same engine as every binding — Rust, Python, Node.js, Go, Java, PHP, Ruby, .NET, Elixir, WASM, Kotlin Android, Swift, Dart, Zig, and C FFI share the same Rust implementation.
• Dart package — Future/Stream API through flutter_rust_bridge.

Installation

Package Installation

Install via pub:

dart pub add xberg

For Flutter projects:

flutter pub add xberg

System Requirements

• Dart SDK 3.0+ for pure-Dart consumers
• Flutter projects supported on macOS, iOS, Android, Linux, and Windows; Flutter Web is not supported
• Native runtime delivered via flutter_rust_bridge with bundled binaries for the supported platforms
• Optional: Tesseract OCR for OCR functionality

Quick Start

Basic Extraction

Extract text, metadata, and structure from any supported document format:

import 'package:xberg/xberg.dart';

final output = await Xberg.extract(
  const ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'document.pdf',
  ),
);

print(output.results.first.content);

Common Use Cases

Extract with Custom Configuration

Most use cases benefit from configuration to control extraction behavior:

With OCR (for scanned documents):

import 'package:xberg/xberg.dart';

Future<void> main() async {
  const config = ExtractionConfig(
    useCache: true,
    enableQualityProcessing: true,
    forceOcr: true,
    disableOcr: false,
    ocr: OcrConfig(
      enabled: true,
      backend: 'tesseract',
      language: ['eng'],
      autoRotate: false,
      vlmFallback: VlmFallbackPolicy.disabled(),
    ),
    resultFormat: ResultFormat.unified,
    outputFormat: OutputFormat.plain(),
    includeDocumentStructure: false,
    maxArchiveDepth: 3,
    useLayoutForMarkdown: false,
    url: UrlExtractionConfig(
      mode: UrlExtractionMode.auto,
      allowLocalFileInputs: true,
      allowFileUris: true,
    ),
  );

  const input = ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'scanned.pdf',
  );
  final output = await XbergBridge.extract(input, config: config);
  final document = output.results.first;

  print(document.content);
}

Table Extraction

See Configuration Guide for table extraction options.

Processing Multiple Files

import 'dart:convert';
import 'package:xberg/xberg.dart';

final output = await Xberg.extractBatch([
  const ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'document.pdf',
  ),
  ExtractInput(
    kind: ExtractInputKind.bytes,
    bytes: utf8.encode('Hello from memory'),
    mimeType: 'text/plain',
    filename: 'note.txt',
  ),
]);

for (final result in output.results) {
  print(result.content);
}

Async Processing

For non-blocking document processing:

import 'package:xberg/xberg.dart';

final output = await Xberg.extract(
  const ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'document.pdf',
  ),
);

print(output.results.first.content);

Next Steps

• Installation Guide - Platform-specific setup
• API Documentation - Complete API reference
• Examples & Guides - Full code examples and usage guides
• Configuration Guide - Advanced configuration options

Features

Supported File Formats (96)

97 file formats across 8 major categories with intelligent format detection and comprehensive metadata extraction.

Office Documents

Category	Formats	Capabilities
Word Processing	.docx, .docm, .doc, .dotx, .dotm, .dot, .odt, .pages	Full text, tables, images, metadata, styles
Spreadsheets	.xlsx, .xlsm, .xlsb, .xls, .xla, .xlam, .xltm, .xltx, .xlt, .ods, .numbers	Sheet data, formulas, cell metadata, charts
Presentations	.pptx, .pptm, .ppt, .ppsx, .potx, .potm, .pot, .odp, .key	Slides, speaker notes, images, metadata
PDF	.pdf	Text, tables, images, metadata, OCR support
eBooks	.epub, .fb2	Chapters, metadata, embedded resources
Database	.dbf	Table data extraction, field type support
Hangul	.hwp, .hwpx	Korean document format, text extraction

Images (OCR-Enabled)

Category	Formats	Features
Raster	.png, .jpg, .jpeg, .gif, .webp, .bmp, .tiff, .tif	OCR, table detection, EXIF metadata, dimensions, color space
Advanced	.jp2, .jpx, .jpm, .mj2, .jbig2, .jb2, .pnm, .pbm, .pgm, .ppm	OCR via hayro-jpeg2000 (pure Rust decoder), JBIG2 support, table detection, format-specific metadata
HEIC family	.heic, .heics, .heif, .avif, .avcs	EXIF metadata, optional libheif pixel decoding
Vector	.svg	DOM parsing, embedded text, graphics metadata

Audio & Video

Category	Formats	Features
Audio	.mp3, .mpga, .m4a, .wav, .webm	Whisper transcription when native transcription is available
Video audio track	.mp4, .mpeg, .webm	Audio-track transcription only

Web & Data

Category	Formats	Features
Markup	.html, .htm, .xhtml, .xml, .svg	DOM parsing, metadata (Open Graph, Twitter Card), link extraction
Structured Data	.json, .yaml, .yml, .toml, .csv, .tsv	Schema detection, nested structures, validation
Text & Markdown	.txt, .md, .markdown, .djot, .mdx, .rst, .org, .rtf	CommonMark, GFM, Djot, MDX, reStructuredText, Org Mode

Email & Archives

Category	Formats	Features
Email	.eml, .msg, .pst	Headers, body (HTML/plain), attachments, threading
Archives	.zip, .tar, .tgz, .gz, .7z	File listing, nested archives, metadata

Academic & Scientific

Category	Formats	Features
Citations	.bib, .ris, .nbib, .enw	Structured parsing: RIS, PubMed/MEDLINE, EndNote XML, BibTeX/BibLaTeX, CSL JSON by MIME type
Scientific	.tex, .latex, .typ, .typst, .jats, .ipynb	LaTeX, Typst, Jupyter notebooks, PubMed JATS
Publishing	.fb2, .docbook, .dbk, .docbook4, .docbook5, .opml	FictionBook, DocBook XML, OPML outlines
Documentation	MIME-only POD, mdoc, troff	Technical documentation formats

Code Intelligence (306 Languages)

Feature	Description
Structure Extraction	Functions, classes, methods, structs, interfaces, enums
Import/Export Analysis	Module dependencies, re-exports, wildcard imports
Symbol Extraction	Variables, constants, type aliases, properties
Docstring Parsing	Google, NumPy, Sphinx, JSDoc, RustDoc, and 10+ formats
Diagnostics	Parse errors with line/column positions
Syntax-Aware Chunking	Split code by semantic boundaries, not arbitrary byte offsets

Powered by tree-sitter-language-pack — documentation.

Complete Format Reference

Key Capabilities

• Text Extraction - Extract all text content with position and formatting information
• Metadata Extraction - Retrieve document properties, creation date, author, etc.
• Table Extraction - Parse tables with structure and cell content preservation
• Image Extraction - Extract embedded images and render page previews
• Audio/Video Transcription - Extract speech transcripts from MP3, M4A, WAV, WebM, and MP4 inputs when the native transcription feature is available
• OCR Support - Integrate multiple OCR backends for scanned documents
• Async/Await - Non-blocking document processing with concurrent operations
• Plugin System - Extensible post-processing for custom text transformation
• Embeddings - Generate vector embeddings using ONNX Runtime models or provider-hosted services
• Batch Processing - Efficiently process multiple documents in parallel
• Memory Efficient - Stream large files without loading entirely into memory
• Language Detection - Detect and support multiple languages in documents
• Code Intelligence - Extract structure, imports, exports, symbols, and docstrings from 306 programming languages via tree-sitter
• Configuration - Fine-grained control over extraction behavior
• Six Output Formats - Plain text, Markdown, Djot, HTML, JSON tree structure, or Structured JSON with OCR metadata

OCR Support

Xberg supports multiple OCR backends for extracting text from scanned documents and images:

• Tesseract

• Paddleocr

OCR Configuration Example

import 'package:xberg/xberg.dart';

Future<void> main() async {
  const config = ExtractionConfig(
    useCache: true,
    enableQualityProcessing: true,
    forceOcr: true,
    disableOcr: false,
    ocr: OcrConfig(
      enabled: true,
      backend: 'tesseract',
      language: ['eng'],
      autoRotate: false,
      vlmFallback: VlmFallbackPolicy.disabled(),
    ),
    resultFormat: ResultFormat.unified,
    outputFormat: OutputFormat.plain(),
    includeDocumentStructure: false,
    maxArchiveDepth: 3,
    useLayoutForMarkdown: false,
    url: UrlExtractionConfig(
      mode: UrlExtractionMode.auto,
      allowLocalFileInputs: true,
      allowFileUris: true,
    ),
  );

  const input = ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'scanned.pdf',
  );
  final output = await XbergBridge.extract(input, config: config);
  final document = output.results.first;

  print(document.content);
}

Async Support

This binding provides full async/await support for non-blocking document processing:

import 'package:xberg/xberg.dart';

final output = await Xberg.extract(
  const ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'document.pdf',
  ),
);

print(output.results.first.content);

Plugin System

Xberg supports extensible post-processing plugins for custom text transformation and filtering.

For detailed plugin documentation, visit Plugin System Guide.

Embeddings Support

Generate vector embeddings for extracted text using the built-in ONNX Runtime support. Requires ONNX Runtime installation.

Embeddings Guide

Batch Processing

Process multiple documents efficiently:

import 'dart:convert';
import 'package:xberg/xberg.dart';

final output = await Xberg.extractBatch([
  const ExtractInput(
    kind: ExtractInputKind.uri,
    uri: 'document.pdf',
  ),
  ExtractInput(
    kind: ExtractInputKind.bytes,
    bytes: utf8.encode('Hello from memory'),
    mimeType: 'text/plain',
    filename: 'note.txt',
  ),
]);

for (final result in output.results) {
  print(result.content);
}

Configuration

For advanced configuration options including language detection, table extraction, OCR settings, and more:

Configuration Guide

Documentation

• Official Documentation
• API Reference
• Examples & Guides

Contributing

Contributions are welcome! See Contributing Guide.

Part of Xberg.dev

• crawlberg — web crawling and scraping with HTML→Markdown and headless-Chrome fallback.
• html-to-markdown — fast, lossless HTML→Markdown engine.
• liter-llm — universal LLM API client with native bindings for 14 languages and 143 providers.
• tree-sitter-language-pack — tree-sitter grammars and code-intelligence primitives.
• alef — the polyglot binding generator that produces this README and all per-language bindings.
• Discord — community, roadmap, announcements.

License

MIT License — see LICENSE for details.

Support

• Discord Community: Join our Discord
• GitHub Issues: Report bugs
• Discussions: Ask questions