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kreuzberg
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kreuzberg

Active·★ 8.7k·MIT·Updated 2026-07-20
★ Trending★ Essential

Kreuzberg is a high-performance, polyglot library designed to extract text and metadata from over 57 file formats, including comprehensive OCR capabilities. Built with a Rust core, it offers native speed processing, memory efficiency, and the ability to generate embeddings without requiring a GPU, making it highly versatile for various data extraction and processing tasks.

kreuzberg is currently grouped under Vision / Multimodal, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Extensible architecture with a plugin system for custom backends and processors. and Automated extraction of text, metadata, and structured data from diverse document types.. The listed license is MIT, which is useful when adoption constraints matter. It also shows measurable community traction with 8.7k GitHub stars.

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#Document Processing#Data Extraction#OCR#Multi-language#Embeddings#Coding#Data Analysis#Image Generation
↗ Visit site★ GitHub
01

Features

01Extensible architecture with a plugin system for custom backends and processors.
02Polyglot support with native bindings for 10+ programming languages.
03Comprehensive support for 57+ file formats across 8 categories, including Office, PDF, and images.
04Advanced OCR capabilities with multiple backends and intelligent table detection.
05High performance due to a Rust core, SIMD optimizations, and full parallelism.
02

Why choose it

+Extensible architecture with a plugin system for custom backends and processors.
+Automated extraction of text, metadata, and structured data from diverse document types.
+Covers 12 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a MIT license, which makes adoption and review easier.
03

Trade-offs

!This page does not list a concrete install command, so you may need to verify setup steps in the official docs before adopting it.
!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04

Compatibility

Rust
Core Library
Verified via docs
Python
Language Binding
Verified via docs
Elixir
Language Binding
Verified via docs
Node.js
Language Binding
Verified via docs
WASM
WebAssembly Support
Verified via docs
Java
Language Binding
Verified via docs
05

Use cases

↳Automated extraction of text, metadata, and structured data from diverse document types.
↳Building intelligent document processing pipelines for data ingestion and analysis.
↳Enabling efficient search and retrieval systems for unstructured and semi-structured content.
06

How it compares

≈kreuzberg sits in the Vision / Multimodal category, so it makes more sense to evaluate it alongside tools like ragflow instead of in isolation.
≈If your main need is closer to "Automated extraction of text, metadata, and structured data from diverse document types.", that use case is a better lens for comparison than broad feature checklists alone.
≈kreuzberg uses a MIT license, and community traction are both easier to judge in category context.
07

Alternatives

ragflow logo
ragflow★ 85.5k
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
vs →
n8n logo
n8n★ 197.2k
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
vs →
Context7 logo
Context7★ 59.5k

Related searches

kreuzberg AlternativesBest Vision / Multimodal Tools 2026Open Source Vision / Multimodalkreuzberg Tutorialkreuzberg Vs CompetitorsDocument ProcessingData ExtractionOCR

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Stats
GitHub Stars★ 8.7k
Last commit1d ago
StatusActive
LicenseMIT
CategoryVision / Multimodal
Trend (30d)
+0.3k↑ 4.3%
Links
Documentation↗Discussion↗Issues↗Releases↗

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