German-OCR

High-performance German document OCR - Local & Cloud

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🚀 Supported Backends

         

Hugging Face  •  Ollama  •  llama.cpp

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✨ Features

Feature	Local	Cloud
German Documents	Invoices, contracts, forms	All document types
Output Formats	Markdown, JSON, text	JSON, Markdown, text, n8n
PDF Support	Images only	Up to 50 pages
Privacy	100% local	DSGVO-konform (Frankfurt)
Speed	~5s/page	~2-3s/page
Backends	Ollama, llama.cpp, HuggingFace	Cloud API
Hardware	CPU, GPU, NPU (CUDA/Metal/Vulkan/OpenVINO)	Managed

📦 Installation

Python

pip install german-ocr

Node.js

npm install german-ocr

PHP

composer require keyvan/german-ocr

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⚡ Quick Start

Option 1: ☁️ Cloud API (Recommended)

No GPU required. Get your API credentials at app.german-ocr.de

from german_ocr import CloudClient

# API Key + Secret (Secret is only shown once at creation!)
client = CloudClient(
    api_key="gocr_xxxxxxxx",
    api_secret="your_64_char_secret_here"
)

# Simple extraction
result = client.analyze("invoice.pdf")
print(result.text)

# Structured JSON output
result = client.analyze(
    "invoice.pdf",
    prompt="Extrahiere Rechnungsnummer und Gesamtbetrag",
    output_format="json"
)
print(result.text)

Node.js

const { GermanOCR } = require('german-ocr');

const client = new GermanOCR(
    process.env.GERMAN_OCR_API_KEY,
    process.env.GERMAN_OCR_API_SECRET
);

const result = await client.analyze('invoice.pdf', {
    model: 'german-ocr-ultra'
});
console.log(result.text);

PHP

<?php
use GermanOCR\GermanOCR;

$client = new GermanOCR(
    getenv('GERMAN_OCR_API_KEY'),
    getenv('GERMAN_OCR_API_SECRET')
);

$result = $client->analyze('invoice.pdf', [
    'model' => GermanOCR::MODEL_ULTRA
]);
echo $result['text'];

Option 2: 🦙 Local (Ollama)

Requires Ollama installed.

# Install model
ollama pull Keyvan/german-ocr-turbo

from german_ocr import GermanOCR

ocr = GermanOCR()
text = ocr.extract("invoice.png")
print(text)

Option 3: 🔧 Local (llama.cpp)

For maximum control and edge deployment with GGUF models.

# Install with GPU support (CUDA)
CMAKE_ARGS="-DGGML_CUDA=on" pip install german-ocr[llamacpp]

# Or CPU only
pip install german-ocr[llamacpp]

from german_ocr import GermanOCR

# Auto-detect best device (GPU/CPU)
ocr = GermanOCR(backend="llamacpp")
text = ocr.extract("invoice.png")

# Force CPU only
ocr = GermanOCR(backend="llamacpp", n_gpu_layers=0)

# Full GPU acceleration
ocr = GermanOCR(backend="llamacpp", n_gpu_layers=-1)

☁️ Cloud Models

Model	Parameter	Best For
German-OCR Ultra	german-ocr-ultra	Maximale Präzision, Strukturerkennung
German-OCR Pro	german-ocr-pro	Balance aus Speed & Qualität
German-OCR Turbo	german-ocr	DSGVO-konform, lokale Verarbeitung in DE

Model Selection

from german_ocr import CloudClient

client = CloudClient(
    api_key="gocr_xxxxxxxx",
    api_secret="your_64_char_secret_here"
)

# German-OCR Ultra - Maximale Präzision
result = client.analyze("dokument.pdf", model="german-ocr-ultra")

# German-OCR Pro - Schnelle Cloud (Standard)
result = client.analyze("dokument.pdf", model="german-ocr-pro")

# German-OCR Turbo - Lokal, DSGVO-konform
result = client.analyze("dokument.pdf", model="german-ocr")

💻 CLI Usage

Cloud

# Set API credentials (Secret shown only once at creation!)
export GERMAN_OCR_API_KEY="gocr_xxxxxxxx"
export GERMAN_OCR_API_SECRET="your_64_char_secret_here"

# Extract text (uses German-OCR Pro by default)
german-ocr --cloud invoice.pdf

# Use German-OCR Turbo (DSGVO-konform, lokal)
german-ocr --cloud --model german-ocr invoice.pdf

# JSON output with German-OCR Ultra
german-ocr --cloud --model german-ocr-ultra --output-format json invoice.pdf

# With custom prompt
german-ocr --cloud --prompt "Extrahiere alle Betraege" invoice.pdf

Local

# Single image
german-ocr invoice.png

# Batch processing
german-ocr --batch ./invoices/

# JSON output
german-ocr --format json invoice.png

🔌 Cloud API

Output Formats

Format	Description
text	Plain text (default)
json	Structured JSON
markdown	Formatted Markdown
n8n	n8n-compatible format

Progress Tracking

from german_ocr import CloudClient

client = CloudClient(
    api_key="gocr_xxxxxxxx",
    api_secret="your_64_char_secret"
)

def on_progress(status):
    print(f"Page {status.current_page}/{status.total_pages}")

result = client.analyze(
    "large_document.pdf",
    on_progress=on_progress
)

Async Processing

# Submit job with German-OCR Pro
job = client.submit("document.pdf", model="german-ocr-pro", output_format="json")
print(f"Job ID: {job.job_id}")

# Check status
status = client.get_job(job.job_id)
print(f"Status: {status.status}")

# Wait for result
result = client.wait_for_result(job.job_id)

# Cancel job
client.cancel_job(job.job_id)

Account Info

# Check balance
balance = client.get_balance()
print(f"Balance: {balance}")

# Usage statistics
usage = client.get_usage()
print(f"Usage: {usage}")

🏠 Local Models

🦙 Ollama Models

Model	Size	Speed	Best For
german-ocr-turbo	1.9 GB	~5s	Recommended
german-ocr	3.2 GB	~7s	Standard

🤗 GGUF Models (llama.cpp / Hugging Face)

Model	Size	Speed	Best For
german-ocr-2b	1.5 GB	~5s (GPU) / ~25s (CPU)	Edge/Embedded
german-ocr-turbo	1.9 GB	~5s (GPU) / ~20s (CPU)	Best accuracy

Hardware Support:

• CUDA (NVIDIA GPUs)
• Metal (Apple Silicon)
• Vulkan (AMD/Intel/NVIDIA)
• OpenVINO (Intel NPU)
• CPU (all platforms)

💰 Pricing

See current pricing at app.german-ocr.de

📄 License

Apache 2.0 - See LICENSE for details.

👤 Author

Keyvan Hardani - keyvan.ai

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Made with ❤️ in Germany 🇩🇪

⭐ Star us on GitHub!