Installation¶
Native bindings for 17 languages plus a standalone CLI. Every package ships prebuilt binaries for Linux (x86_64/aarch64), macOS (Apple Silicon), and Windows — no compile step needed.
x86_64 CPU — AVX/AVX2 instruction set required
The bundled ONNX Runtime binaries require AVX/AVX2 CPU instructions. CPUs without AVX support (e.g. Intel Atom, Celeron N5105/Jasper Lake, older pre-2011 processors) will crash with an invalid opcode trap when using ONNX-dependent features. The affected features are PaddleOCR, layout detection, and embeddings. All other Kreuzberg functionality (text extraction, Tesseract OCR, chunking, metadata, etc.) works normally on any x86_64 CPU. ARM platforms (aarch64) are unaffected.
Windows — ONNX Runtime required for Go, Elixir, and C/C++
Go, Elixir, and C/C++ bindings on Windows link against ONNX Runtime dynamically. You must have onnxruntime.dll on your PATH at runtime. Download it from the ONNX Runtime releases (for example onnxruntime-win-x64-1.24.1.zip). Python, TypeScript, Java, C#, Ruby, PHP, and Wasm are unaffected.
Choose your language¶
- Python
- TypeScript (Node.js / Bun)
- TypeScript (Browser / Edge)
- Rust
- Go
- Java
- :fontawesome-brands-kotlin:{ .lg .middle } Kotlin
- Ruby
- Swift
- C# / .NET
- PHP
- Elixir
- R
- C / C++
- :material-language-dart:{ .lg .middle } Dart / Flutter
- :material-language-zig:{ .lg .middle } Zig
System requirements¶
Only relevant if building from source or enabling OCR:
| Dependency | When you need it |
|---|---|
| AVX/AVX2 CPU instructions | Required for ONNX Runtime features (PaddleOCR, layout detection, embeddings) on x86_64 |
Rust toolchain (rustup) |
Building any native binding from source |
| C/C++ compiler | Building native bindings (Xcode command-line tools / build-essential / MSVC) |
| Tesseract OCR | Optional — brew install tesseract / apt install tesseract-ocr |
| PDFium | Auto-fetched during builds |
The Wasm package (@kreuzberg/wasm) has zero system dependencies.
GPU Acceleration¶
Kreuzberg bundles a CPU-only ONNX Runtime — ML features (PaddleOCR, layout detection, embeddings) work out of the box on CPU.
For GPU acceleration, install a GPU-enabled ONNX Runtime and set ORT_DYLIB_PATH:
| Platform | Install | Set ORT_DYLIB_PATH |
|---|---|---|
| Linux (CUDA) | Download from ONNX Runtime releases | export ORT_DYLIB_PATH=/path/to/libonnxruntime.so |
| Python (any OS) | pip install onnxruntime-gpu |
Point at the pip package's capi/ directory |
| macOS (CoreML) | Works with bundled ORT — no extra setup needed | — |
See AccelerationConfig and ORT_DYLIB_PATH for details.
Language-specific notes¶
Edge cases and alternative install methods where they come up.
TypeScript¶
Two npm packages target different runtimes:
| Package | Best for | Performance |
|---|---|---|
@kreuzberg/node |
Node.js, Bun — server-side apps | Native (100%) |
@kreuzberg/wasm |
Browsers, Deno, Cloudflare Workers | Wasm (~60-80%) |
Both work with pnpm (pnpm add) and Yarn (yarn add) as well.
pnpm workspaces
In monorepos, add this to your root .npmrc so platform-specific optional deps resolve correctly:
Wasm — Browser usage
<script type="module">
import { initWasm, extractFromFile } from "@kreuzberg/wasm";
await initWasm();
const input = document.getElementById("file");
input.addEventListener("change", async (e) => {
const result = await extractFromFile(e.target.files[0]);
console.log(result.content);
});
</script>
<input type="file" id="file" />
Wasm — Deno
Wasm — Cloudflare Workers
import { initWasm, extractBytes } from "@kreuzberg/wasm";
export default {
async fetch(request: Request): Promise<Response> {
await initWasm();
const bytes = new Uint8Array(await request.arrayBuffer());
const result = await extractBytes(bytes, "application/pdf");
return Response.json({ content: result.content });
},
};
Supported runtimes: Chrome 74+, Firefox 79+, Safari 14+, Edge 79+, Node.js 22+, Deno 1.35+, Cloudflare Workers.
Wasm Platform Limitations
The Wasm binding does not support:
- Layout detection (RT-DETR model inference requires ONNX Runtime unavailable in WebAssembly)
- Hardware acceleration config (single-threaded WASM, no GPU access)
- Concurrency config (single-threaded environment,
maxThreadsis ignored) - Email codepage config (EmailConfig not available)
All other features (text extraction, OCR via Tesseract WASM, chunking, embeddings, metadata, tables, language detection, image extraction) work fully in WASM. See the WASM API Reference for details.
Java¶
Requires Java 25+ (FFM/Panama API). Native libraries are bundled in the JAR.
Elixir¶
Add to mix.exs:
Ships prebuilt NIF binaries via RustlerPrecompiled. Falls back to compiling from source if no prebuilt matches your platform (requires Rust).
Windows
The Windows NIF links against ONNX Runtime dynamically. onnxruntime.dll must be on your PATH at runtime — see the note at the top of this page.
Go¶
Windows
The Go binding links against ONNX Runtime dynamically on Windows. onnxruntime.dll must be on your PATH at runtime — see the note at the top of this page.
Windows feature limitations
The Go and C/C++ bindings on Windows (MinGW/GNU target) do not include PaddleOCR, layout detection, or auto-rotate. Tesseract OCR and all other features work normally. These limitations apply only to Windows; Linux and macOS builds include the full feature set.
Rust¶
Enable features selectively in Cargo.toml:
[dependencies]
kreuzberg = { version = "4", features = ["tokio-runtime"] }
# Optional features: pdf, ocr, chunking
C / C++¶
Build the FFI library from source:
This produces libkreuzberg_ffi.a and a header at crates/kreuzberg-ffi/kreuzberg.h. Link into your project:
HEADER_DIR = path/to/crates/kreuzberg-ffi
LIBDIR = path/to/target/release
CFLAGS = -Wall -Wextra -I$(HEADER_DIR)
LDFLAGS = -L$(LIBDIR) -lkreuzberg_ffi -lpthread -ldl -lm
my_app: my_app.c
$(CC) $(CFLAGS) -o $@ $< $(LDFLAGS)
Platform-specific linker flags
macOS: add -framework CoreFoundation -framework Security
Windows: add -lws2_32 -luserenv -lbcrypt
Windows
The Windows FFI library links against ONNX Runtime dynamically. onnxruntime.dll must be on your PATH at runtime — see the note at the top of this page.
Dart / Flutter¶
Pure-Dart and Flutter consumers share the same package. Dart SDK 3.0 or higher is required. Flutter is supported on macOS, iOS, Android, Linux, and Windows; Flutter Web is not supported because the runtime is a native dynamic library delivered via flutter_rust_bridge. For Flutter projects use flutter pub add kreuzberg instead of dart pub add kreuzberg.
Kotlin¶
The Kotlin module sits on top of the Java facade and reuses its Foreign Function & Memory native loader, so the same bundled binaries serve both bindings. Requires JDK 25 or higher. Use the Kotlin DSL block above for build.gradle.kts consumers; Maven and Groovy DSL are also supported — see the README at packages/kotlin/ for both.
Swift¶
Swift Package Manager from swift-tools-version: 6.0 upward. Targets macOS 13+ and iOS 16+; Linux is not currently declared in Package.swift. Once the package ships its binaryTarget, no manual cargo build is needed; in the interim, building the library locally requires cargo build -p kreuzberg-swift against the workspace.
Zig¶
Requires Zig 0.16.0 or higher (declared via minimum_zig_version in build.zig.zon). The Zig binding consumes the C FFI surface from kreuzberg-ffi via linkSystemLibrary; the build expects the consumer to provide a search path to the prebuilt libkreuzberg_ffi and the C header kreuzberg.h. The zig fetch command above pins the source archive in build.zig.zon; wire it into build.zig via b.dependency("kreuzberg", ...).
Development setup¶
For working on the Kreuzberg repository itself:
task setup # installs all language toolchains
task lint # linters across all languages
task dev:test # full test suite
See Contributing for conventions and expectations.