Documentation Index
Fetch the complete documentation index at: https://runcrate.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
Extract structured text from images, scanned documents, receipts, and invoices using vision-language models purpose-built for OCR. No preprocessing, no bounding boxes — send an image and get text back.
Available OCR models
| Model | Parameters | Strengths |
|---|
deepseek-ai/DeepSeek-OCR | — | High accuracy on complex layouts, tables, handwriting |
allenai/olmOCR-2-7B-1025 | 2.7B | Fast, lightweight, good for bulk processing |
PaddlePaddle/PaddleOCR-VL-0.9B | 0.9B | Ultra-lightweight, edge-deployable |
curl https://api.runcrate.ai/v1/chat/completions \
-H "Authorization: Bearer rc_live_YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-ai/DeepSeek-OCR",
"messages": [
{
"role": "user",
"content": [
{"type": "text", "text": "Extract all text from this document image. Preserve the layout and formatting."},
{"type": "image_url", "image_url": {"url": "https://example.com/invoice.png"}}
]
}
],
"max_tokens": 2048
}'
Receipt parsing with structured output
Extract specific fields from a receipt photo:
from openai import OpenAI
import base64, json
from pathlib import Path
client = OpenAI(
base_url="https://api.runcrate.ai/v1",
api_key="rc_live_YOUR_API_KEY",
)
image_data = base64.b64encode(Path("receipt.jpg").read_bytes()).decode()
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-OCR",
messages=[
{
"role": "system",
"content": "Extract receipt data as JSON with keys: merchant, date, items (array of {name, quantity, price}), subtotal, tax, total. Use null for missing fields.",
},
{
"role": "user",
"content": [
{"type": "text", "text": "Parse this receipt."},
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}},
],
},
],
max_tokens=1024,
)
receipt = json.loads(response.choices[0].message.content)
print(f"Merchant: {receipt['merchant']}")
print(f"Total: ${receipt['total']}")
for item in receipt["items"]:
print(f" - {item['name']}: ${item['price']}")
Next steps
- AI Vision API — analyze images beyond OCR: scene understanding, chart reading, visual Q&A.
- Extract structured data — combine OCR output with schema-based extraction for production pipelines.
- Model catalog — browse all available vision and OCR models.