xberg 1.2.1
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High-performance document intelligence library
Dart / Flutter #
Extract text, tables, images, metadata, and code intelligence from 107 file formats and 371 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_bridgewith 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';
Future<void> main() async {
final output = await XbergBridge.extract(
const ExtractInput(
kind: ExtractInputKind.uri,
uri: 'document.pdf',
),
config: await createExtractionConfigFromJson(json: '{}'),
);
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 {
// `ExtractionConfig` is a generated data class with no defaults, so build it
// from JSON: every field you omit keeps its Rust-side default value.
final config = await createExtractionConfigFromJson(json: '''
{
"force_ocr": true,
"ocr": {
"backend": "tesseract",
"language": ["eng"]
}
}
''');
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 'package:xberg/xberg.dart';
Future<void> main() async {
final inputs = [
const ExtractInput(kind: ExtractInputKind.uri, uri: 'report.pdf'),
const ExtractInput(kind: ExtractInputKind.uri, uri: 'notes.txt'),
];
final output = await XbergBridge.extractBatch(inputs);
for (final result in output.results) {
print(result.content);
}
}
Async Processing
For non-blocking document processing:
import 'package:xberg/xberg.dart';
Future<void> main() async {
final output = await XbergBridge.extract(
const ExtractInput(
kind: ExtractInputKind.uri,
uri: 'document.pdf',
),
config: await createExtractionConfigFromJson(json: '{}'),
);
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 (107 formats · 141 file extensions · 56 MIME aliases) #
107 formats across 140 unique file extensions, with 56 compatibility MIME aliases, intelligent format detection, and comprehensive metadata extraction.
Office Documents
| Category | Formats | Capabilities |
|---|---|---|
| Word Processing | .docx, .docm, .doc, .dotx, .dotm, .dot, .odt, .pages, .wpd, .wp, .wp5, .wp6 |
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, .pps, .ppsx, .potx, .potm, .pot, .odp, .key |
Slides, speaker notes, images, metadata |
.pdf |
Text, tables, images, metadata, OCR support | |
| eBooks | .epub, .fb2 |
Chapters, metadata, embedded resources |
| Database | .dbf, .sqlite, .sqlite3, .db, .gpkg, .gpkx |
Bounded table extraction, schema metadata, GeoPackage detection |
| 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, .jpg2, .j2c, .j2k, .jpc, .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, .heifs, .hif, .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 |
| MP4 audio track | .mp4, .mpg4, .mp4v, .m4v |
Audio-track transcription only |
| MPEG audio track | .mpeg, .mpg, .mpe, .m1v, .m2v |
Audio-track transcription only |
| WebM audio track | .webm |
Audio-track transcription only |
Web & Data
| Category | Formats | Features |
|---|---|---|
| Markup | .html, .htm, .xhtml, .xht, .xml, .kml, .svg |
DOM parsing, metadata (Open Graph, Twitter Card), link extraction |
| Structured Data | .json, .geojson, .jsonl, .ndjson, .yaml, .yml, .toml, .csv, .tsv |
Schema detection, nested structures, validation |
| Text & Markdown | .txt, .adoc, .asciidoc, .vtt, .md, .markdown, .commonmark, .qmd, .rmd, .djot, .dj, .mdx, .doctags, .rst, .org, .rtf |
AsciiDoc, CommonMark, MyST Markdown, Quarto, R Markdown, Djot, MDX, DocTags, reStructuredText, Org Mode |
Email & Archives
| Category | Formats | Features |
|---|---|---|
.eml, .msg, .pst |
Headers, body (HTML/plain), attachments, threading | |
| Archives | .zip, .tar, .tgz, .gz, .7z |
Recursive extraction of nested archives, file listing, metadata, zip-bomb protection |
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, .nxml |
LaTeX, Typst, PubMed JATS |
| Text notebooks | .ipynb, .md, .py, .R, .jl |
Jupyter, MyST-NB, Jupytext percent/light, saved outputs, cell visibility tags |
| Publishing | .fb2, .docbook, .dbk, .docbook4, .docbook5, .opml |
FictionBook, DocBook XML, OPML outlines |
Code Intelligence (371 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.
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 371 programming languages via tree-sitter
- Configuration - Fine-grained control over extraction behavior
- Six Output Formats - Plain text, Markdown, Djot, HTML, JSON tree structure, or Docling DocTags
OCR Support #
Xberg supports multiple OCR backends for extracting text from scanned documents and images:
-
Tesseract
-
Paddleocr
-
Sceptre
OCR Configuration Example #
import 'package:xberg/xberg.dart';
Future<void> main() async {
// `ExtractionConfig` is a generated data class with no defaults, so build it
// from JSON: every field you omit keeps its Rust-side default value.
final config = await createExtractionConfigFromJson(json: '''
{
"force_ocr": true,
"ocr": {
"backend": "tesseract",
"language": ["eng"]
}
}
''');
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';
Future<void> main() async {
final output = await XbergBridge.extract(
const ExtractInput(
kind: ExtractInputKind.uri,
uri: 'document.pdf',
),
config: await createExtractionConfigFromJson(json: '{}'),
);
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.
Batch Processing #
Process multiple documents efficiently:
import 'package:xberg/xberg.dart';
Future<void> main() async {
final inputs = [
const ExtractInput(kind: ExtractInputKind.uri, uri: 'report.pdf'),
const ExtractInput(kind: ExtractInputKind.uri, uri: 'notes.txt'),
];
final output = await XbergBridge.extractBatch(inputs);
for (final result in output.results) {
print(result.content);
}
}
Configuration #
For advanced configuration options including language detection, table extraction, OCR settings, and more:
Documentation #
Contributing #
Contributions are welcome! See Contributing Guide.
Part of Xberg.io #
- Xberg — the open-source content-intelligence engine: text, tables, and metadata from 107 formats (141 file extensions), with OCR, transcription, and code intelligence. MIT.
- Xberg Pro — a complete self-hosted content-intelligence backend in a single container. Commercial.
- Xberg Enterprise — the distributed, governed content-intelligence platform, scaled on Kubernetes with team governance and support. Commercial.
- 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 165 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