Kotlin (Android)
Extract text, tables, images, and metadata from 90+ file formats and 300+ programming languages including PDF, Office documents, and images. Android library (AAR) with bundled jniLibs/arm64-v8a and jniLibs/x86_64 — Gradle automatically picks up the native cdylib for emulator and device builds. Server-side Kotlin/JVM consumers can use the Java binding directly via standard Kotlin/Java interop.
What This Package Provides
- Document intelligence core — extract text, tables, images, metadata, entities, keywords, and code intelligence from one API.
- Format coverage — PDF, Office, images, HTML/XML, email, archives, notebooks, citations, scientific formats, and plain text.
- OCR choices — Tesseract, PaddleOCR, EasyOCR 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, R, WASM, Kotlin Android, Swift, Dart, Zig, and C FFI share the same Rust implementation.
- Android AAR — JNI-backed package for mobile extraction workloads.
Installation
Package Installation
Kotlin DSL (build.gradle.kts):
implementation("dev.kreuzberg:kreuzberg-android:5.0.0-rc.3")
Groovy DSL (build.gradle):
implementation 'dev.kreuzberg:kreuzberg-android:5.0.0-rc.3'
Add to your pom.xml:
<dependency>
<groupId>dev.kreuzberg</groupId>
<artifactId>kreuzberg-android</artifactId>
<version>5.0.0-rc.3</version>
</dependency>
System Requirements
- See Installation Guide for requirements
Quick Start
Basic Extraction
Extract text, metadata, and structure from any supported document format:
Common Use Cases
Extract with Custom Configuration
Most use cases benefit from configuration to control extraction behavior:
With OCR (for scanned documents):
Table Extraction
See Configuration Guide for table extraction options.
Processing Multiple Files
Async Processing
For non-blocking document processing:
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 (90+)
90+ file formats across 8 major categories with intelligent format detection and comprehensive metadata extraction.
Office Documents
| Category | Formats | Capabilities |
|---|---|---|
| Word Processing | .docx, .docm, .dotx, .dotm, .dot, .odt |
Full text, tables, images, metadata, styles |
| Spreadsheets | .xlsx, .xlsm, .xlsb, .xls, .xla, .xlam, .xltm, .xltx, .xlt, .ods |
Sheet data, formulas, cell metadata, charts |
| Presentations | .pptx, .pptm, .ppsx, .potx, .potm, .pot, .ppt |
Slides, speaker notes, images, metadata |
.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 |
| Vector | .svg |
DOM parsing, embedded text, graphics metadata |
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, .rst, .org, .rtf |
CommonMark, GFM, Djot, reStructuredText, Org Mode |
Email & Archives
| Category | Formats | Features |
|---|---|---|
.eml, .msg |
Headers, body (HTML/plain), attachments, threading | |
| Archives | .zip, .tar, .tgz, .gz, .7z |
File listing, nested archives, metadata |
Academic & Scientific
| Category | Formats | Features |
|---|---|---|
| Citations | .bib, .biblatex, .ris, .nbib, .enw, .csl |
Structured parsing: RIS (structured), PubMed/MEDLINE, EndNote XML (structured), BibTeX, CSL JSON |
| Scientific | .tex, .latex, .typst, .jats, .ipynb, .docbook |
LaTeX, Jupyter notebooks, PubMed JATS |
| Documentation | .opml, .pod, .mdoc, .troff |
Technical documentation formats |
Code Intelligence (300+ 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
- 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
- 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 300+ programming languages via tree-sitter
- Configuration - Fine-grained control over extraction behavior
Performance Characteristics
| Format | Speed | Memory | Notes |
|---|---|---|---|
| PDF (text) | 10-100 MB/s | ~50MB per doc | Fastest extraction |
| Office docs | 20-200 MB/s | ~100MB per doc | DOCX, XLSX, PPTX |
| Images (OCR) | 1-5 MB/s | Variable | Depends on OCR backend |
| Archives | 5-50 MB/s | ~200MB per doc | ZIP, TAR, etc. |
| Web formats | 50-200 MB/s | Streaming | HTML, XML, JSON |
OCR Support
Kreuzberg supports multiple OCR backends for extracting text from scanned documents and images:
-
Tesseract
-
Paddleocr
OCR Configuration Example
Async Support
This binding provides full async/await support for non-blocking document processing:
Plugin System
Kreuzberg 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:
Configuration
For advanced configuration options including language detection, table extraction, OCR settings, and more:
Documentation
Contributing
Contributions are welcome! See Contributing Guide.
Part of Kreuzberg.dev
- Kreuzberg Cloud — managed extraction API with SDKs, dashboards, and observability.
- kreuzcrawl — 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
Elastic-2.0 License — see LICENSE for details.
Support
- Discord Community: Join our Discord
- GitHub Issues: Report bugs
- Discussions: Ask questions