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Project description
Regia AI SDK
A lightweight Python SDK to interact with the Regia Vision Extractor API.
Send PDF documents and automatically extract structured data using Pydantic schemas.
📦 Installation
Using pip:
pip install regia-ai-sdk
or uv use the command line:
uv add regia-ai-sdk
🚀 Quickstart
from vision import VisionClient
from pydantic import BaseModel, Field
import os
class InvoiceModel(BaseModel):
due_date: str = Field(..., description="The due date of the invoice")
total_amount: float = Field(..., description="The total amount of the invoice")
base_url = os.getenv("BASE_URL")
token = os.getenv("API_TOKEN")
client = VisionClient(token=token, base_url=base_url)
result = client.extract("./data/sample.pdf", InvoiceModel)
print(result)
📂 Other Input Methods
From bytes
with open("./data/sample.pdf", "rb") as f:
content_bytes = f.read()
result = client.extract(content_bytes, InvoiceModel, filename="sample_bytes.pdf")
print(result)
From base64
import base64
with open("./data/sample.pdf", "rb") as f:
base64_string = base64.b64encode(f.read()).decode("utf-8")
result = client.extract(base64_string, InvoiceModel, filename="sample_base64.pdf")
print(result)
🧠 Features
- ✅ Simple interface for sending documents to the Regia Vision API
- ✅ Supports file path, bytes, and base64 inputs
- ✅ Use Pydantic models to define the expected data
- ✅ Automatically converts Pydantic to schema JSON
🔐 Authentication
You must provide an API token and base URL:
export BASE_URL=https://your-api-url.com
export API_TOKEN=your_api_token_here
Made with 💡 by Regia.ai
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