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kreuzberg

kreuzberg

Extract text, tables, metadata, and images from 91+ document formats (PDF, Office, images, HTML, email, archives, academic) using Kreuzberg. Use when writing code that calls Kreuzberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async), configuration (OCR, chunking, output format), batch processing, error handling,…

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GitHub

name: kreuzberg description: >- Extract text, tables, metadata, and images from 91+ document formats (PDF, Office, images, HTML, email, archives, academic) using Kreuzberg. Use when writing code that calls Kreuzberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async), configuration (OCR, chunking, output format), batch processing, error handling, and plugins. license: Elastic-2.0 metadata: author: kreuzberg-dev version: "0.1.0" repository: https://github.com/kreuzberg-dev/kreuzberg

Kreuzberg Document Extraction

Kreuzberg is a high-performance document intelligence library with a Rust core and native bindings for Python, Node.js/TypeScript, Ruby, Go, Java, C#, PHP, and Elixir. It extracts text, tables, metadata, and images from 91+ file formats including PDF, Office documents, images (with OCR), HTML, email, archives, and academic formats.

Use this skill when writing code that:

  • Extracts text or metadata from documents
  • Performs OCR on scanned documents or images
  • Batch-processes multiple files
  • Configures extraction options (output format, chunking, OCR, language detection)
  • Implements custom plugins (post-processors, validators, OCR backends)

If the kreuzberg MCP server is registered in this session, prefer its tools over shelling out to the CLI — they expose the same extraction surface with structured arguments and results.

Installation

Python

pip install kreuzberg
# Optional OCR backends:
pip install kreuzberg[easyocr]    # EasyOCR

Node.js

npm install @kreuzberg/node

Rust

# Cargo.toml
[dependencies]
kreuzberg = { version = "4", features = ["tokio-runtime"] }
# features: tokio-runtime (required for sync + batch), pdf, ocr, chunking,
#           embeddings, language-detection, keywords-yake, keywords-rake

CLI

brew install kreuzberg-dev/tap/kreuzberg
# or run without a persistent install (the CLI proxy package self-installs the binary):
npx @kreuzberg/kreuzberg-cli --help
uvx --from kreuzberg-cli kreuzberg --help
# or download a prebuilt binary from the latest GitHub release:
#   https://github.com/kreuzberg-dev/kreuzberg/releases/latest
# or build from source:
cargo install --git https://github.com/kreuzberg-dev/kreuzberg kreuzberg-cli

Quick Start

Python (Async)

from kreuzberg import extract_file

result = await extract_file("document.pdf")
print(result.content)       # extracted text
print(result.metadata)      # document metadata
print(result.tables)        # extracted tables

Python (Sync)

from kreuzberg import extract_file_sync

result = extract_file_sync("document.pdf")
print(result.content)

Node.js

import { extractFile } from "@kreuzberg/node";

const result = await extractFile("document.pdf");
console.log(result.content);
console.log(result.metadata);
console.log(result.tables);

Node.js (Sync)

import { extractFileSync } from "@kreuzberg/node";

const result = extractFileSync("document.pdf");

Rust (Async)

use kreuzberg::{extract_file, ExtractionConfig};

#[tokio::main]
async fn main() -> kreuzberg::Result<()> {
    let config = ExtractionConfig::default();
    let result = extract_file("document.pdf", None, &config).await?;
    println!("{}", result.content);
    Ok(())
}

Rust (Sync) — requires tokio-runtime feature

use kreuzberg::{extract_file_sync, ExtractionConfig};

fn main() -> kreuzberg::Result<()> {
    let config = ExtractionConfig::default();
    let result = extract_file_sync("document.pdf", None, &config)?;
    println!("{}", result.content);
    Ok(())
}

CLI

kreuzberg extract document.pdf
kreuzberg extract document.pdf --format json
kreuzberg extract document.pdf --content-format markdown

Configuration

All languages use the same configuration structure with language-appropriate naming conventions.

Python (snake_case)

from kreuzberg import (
    ExtractionConfig, OcrConfig, TesseractConfig,
    PdfConfig, ChunkingConfig,
)

config = ExtractionConfig(
    ocr=OcrConfig(
        backend="tesseract",
        language="eng",
        tesseract_config=TesseractConfig(psm=6, enable_table_detection=True),
    ),
    pdf_options=PdfConfig(passwords=["secret123"]),
    chunking=ChunkingConfig(max_chars=1000, max_overlap=200),
    output_format="markdown",
)

result = await extract_file("document.pdf", config=config)

Node.js (camelCase)

import { extractFile, type ExtractionConfig } from "@kreuzberg/node";

const config: ExtractionConfig = {
  ocr: { backend: "tesseract", language: "eng" },
  pdfOptions: { passwords: ["secret123"] },
  chunking: { maxChars: 1000, maxOverlap: 200 },
  outputFormat: "markdown",
};

const result = await extractFile("document.pdf", null, config);

Rust (snake_case)

use kreuzberg::{ExtractionConfig, OcrConfig, ChunkingConfig, OutputFormat};

let config = ExtractionConfig {
    ocr: Some(OcrConfig {
        backend: "tesseract".into(),
        language: "eng".into(),
        ..Default::default()
    }),
    chunking: Some(ChunkingConfig {
        max_characters: 1000,
        overlap: 200,
        ..Default::default()
    }),
    output_format: OutputFormat::Markdown,
    ..Default::default()
};

let result = extract_file("document.pdf", None, &config).await?;

Config File (TOML)

output_format = "markdown"

[ocr]
backend = "tesseract"
language = "eng"

[chunking]
max_characters = 1000
overlap = 200

[pdf_options]
passwords = ["secret123"]
# CLI: auto-discovers kreuzberg.toml in current/parent directories
kreuzberg extract doc.pdf
# or explicit:
kreuzberg extract doc.pdf --config kreuzberg.toml
kreuzberg extract doc.pdf --config-json '{"ocr":{"backend":"tesseract","language":"deu"}}'

Batch Processing

Python

from kreuzberg import batch_extract_files, batch_extract_files_sync

# Async
results = await batch_extract_files(["doc1.pdf", "doc2.docx", "doc3.xlsx"])

# Sync
results = batch_extract_files_sync(["doc1.pdf", "doc2.docx"])

for result in results:
    print(f"{len(result.content)} chars extracted")

Node.js

import { batchExtractFiles } from "@kreuzberg/node";

const results = await batchExtractFiles(["doc1.pdf", "doc2.docx"]);

Rust — requires tokio-runtime feature

use kreuzberg::{batch_extract_file, ExtractionConfig};

let config = ExtractionConfig::default();
let paths = vec!["doc1.pdf", "doc2.docx"];
let results = batch_extract_file(paths, &config).await?;

CLI

kreuzberg batch *.pdf --format json
kreuzberg batch docs/*.docx --content-format markdown

OCR

OCR runs automatically for images and scanned PDFs. Tesseract is the default backend (native binding, no external install required).

Backends

  • Tesseract (default): Built-in native binding. All Tesseract languages supported.
  • EasyOCR (Python only): pip install kreuzberg[easyocr]. Pass easyocr_kwargs={"gpu": True}.
  • PaddleOCR (Python only): Bundled since 4.8.5, no extra install needed. Pass paddleocr_kwargs={"use_angle_cls": True}.
  • Guten (Node.js only): Built-in OCR backend via GutenOcrBackend.

Language Codes

config = ExtractionConfig(ocr=OcrConfig(language="eng"))       # English
config = ExtractionConfig(ocr=OcrConfig(language="eng+deu"))   # Multiple
config = ExtractionConfig(ocr=OcrConfig(language="all"))       # All installed

Force OCR

config = ExtractionConfig(force_ocr=True)  # OCR even if text is extractable

ExtractionResult Fields

FieldPythonNode.jsRustDescription
Text contentresult.contentresult.contentresult.contentExtracted text (str/String)
MIME typeresult.mime_typeresult.mimeTyperesult.mime_typeInput document MIME type
Metadataresult.metadataresult.metadataresult.metadataDocument metadata (dict/object/HashMap)
Tablesresult.tablesresult.tablesresult.tablesExtracted tables with cells + markdown
Languagesresult.detected_languagesresult.detectedLanguagesresult.detected_languagesDetected languages (if enabled)
Chunksresult.chunksresult.chunksresult.chunksText chunks (if chunking enabled)
Imagesresult.imagesresult.imagesresult.imagesExtracted images (if enabled)
Elementsresult.elementsresult.elementsresult.elementsSemantic elements (if element_based format)
Pagesresult.pagesresult.pagesresult.pagesPer-page content (if page extraction enabled)
Keywordsresult.keywordsresult.keywordsresult.keywordsExtracted keywords (if enabled)

Error Handling

Python

from kreuzberg import (
    extract_file_sync, KreuzbergError, ParsingError,
    OCRError, ValidationError, MissingDependencyError,
)

try:
    result = extract_file_sync("file.pdf")
except ParsingError as e:
    print(f"Failed to parse: {e}")
except OCRError as e:
    print(f"OCR failed: {e}")
except ValidationError as e:
    print(f"Invalid input: {e}")
except MissingDependencyError as e:
    print(f"Missing dependency: {e}")
except KreuzbergError as e:
    print(f"Extraction failed: {e}")

Node.js

import {
  extractFile,
  KreuzbergError,
  ParsingError,
  OcrError,
  ValidationError,
  MissingDependencyError,
} from "@kreuzberg/node";

try {
  const result = await extractFile("file.pdf");
} catch (e) {
  if (e instanceof ParsingError) {
    /* ... */
  } else if (e instanceof OcrError) {
    /* ... */
  } else if (e instanceof ValidationError) {
    /* ... */
  } else if (e instanceof KreuzbergError) {
    /* ... */
  }
}

Rust

use kreuzberg::{extract_file, ExtractionConfig, KreuzbergError};

let config = ExtractionConfig::default();
match extract_file("file.pdf", None, &config).await {
    Ok(result) => println!("{}", result.content),
    Err(KreuzbergError::Parsing(msg)) => eprintln!("Parse error: {msg}"),
    Err(KreuzbergError::Ocr(msg)) => eprintln!("OCR error: {msg}"),
    Err(e) => eprintln!("Error: {e}"),
}

Common Pitfalls

  1. Python ChunkingConfig fields: Use max_chars and max_overlap, NOT max_characters or overlap.
  2. Rust extract_file signature: Third argument is &ExtractionConfig (a reference), not Option. Use &ExtractionConfig::default() for defaults.
  3. Rust feature gates: extract_file_sync, batch_extract_file, and batch_extract_file_sync all require features = ["tokio-runtime"] in Cargo.toml.
  4. Rust async context: extract_file is async. Use #[tokio::main] or call from an async context.
  5. CLI --format vs --content-format: --format controls CLI output (text/json). --content-format controls content format (plain/markdown/djot/html). The older --output-format is a deprecated alias that still works but prints a warning — prefer --content-format.
  6. Node.js extractFile signature: extractFile(path, mimeType?, config?) — mimeType is the second arg (pass null to skip).
  7. Python detect_mime_type: The function for detecting from bytes is detect_mime_type(data). For paths use detect_mime_type_from_path(path).
  8. Config file field names: Use snake_case in TOML/YAML/JSON config files. The Rust [chunking] fields are max_characters and overlap (with max_chars / max_overlap accepted as aliases). Other fields use names like output_format, pdf_options.

Supported Formats (Summary)

CategoryExtensions
PDF.pdf
Word.docx, .odt
Spreadsheets.xlsx, .xlsm, .xlsb, .xls, .xla, .xlam, .xltm, .ods
Presentations.pptx, .ppt, .ppsx
eBooks.epub, .fb2
Images.png, .jpg, .jpeg, .gif, .webp, .bmp, .tiff, .tif, .jp2, .jpx, .jpm, .mj2, .jbig2, .jb2, .pnm, .pbm, .pgm, .ppm, .svg
Markup.html, .htm, .xhtml, .xml
Data.json, .yaml, .yml, .toml, .csv, .tsv
Text.txt, .md, .markdown, .djot, .rst, .org, .rtf
Email.eml, .msg
Archives.zip, .tar, .tgz, .gz, .7z
Academic.bib, .biblatex, .ris, .nbib, .enw, .csl, .tex, .latex, .typ, .jats, .ipynb, .docbook, .opml, .pod, .mdoc, .troff

See references/supported-formats.md for the complete format reference with MIME types.

Additional Resources

Detailed reference files for specific topics:

Related skills

Task-focused sibling skills go deeper than this overview:

  • extracting-with-ocr — OCR backends, language packs, force-OCR, tuning.
  • extracting-tables — layout-aware table detection and table models.
  • chunking — chunk size/overlap, markdown/yaml/semantic chunkers, the chunk command.
  • extracting-keywords — YAKE/RAKE keywords, language detection, the embed command.
  • batch-extraction — the batch command, --file-configs, parallelism, error recovery.
  • picking-a-format — choosing --format / --content-format per consumer.

Full documentation: https://docs.kreuzberg.dev GitHub: https://github.com/kreuzberg-dev/kreuzberg

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