Invoice with line items

Extracting metadata and line items from invoices with examples in Python and Node.

Overview

This guide covers how to extract metadata and line items from multiple supplier invoices with examples in Python and Node. For this example, we will use the Pretrained model.

You will extract the following metadata fields:

Name of the supplier
Name of the receiver
Invoice number
Purchase order number
Issue date
Pay due date
Total amount

You will extract the following line item fields:

Product number
Product description
Quantity
Price

This guide shows you how to

Getting your API Key

The Authorization header for your API key is: Token YOUR-API-KEY (Login if you do not see one). You can also obtain the API key by visiting the Settings page.

1. Create a new document type

Before you start extracting data, you need to define a document type. Navigate to the Dashboard page and click on the New document type button in the top right corner of the table. Next, select the Pretrained model, followed by Use a Predefined Template. Next, click on Line item invoice card. The wizard will already pre-fill all the needed extraction fields along with the document type configuration. Click on the Create document type.

This will create a new document type with name line-item-invoice with the following fields:

supplier_name
supplier_vat_id
buyer_name
buyer_vat_id
invoice_number
payment_reference
invoice_date
payment_due_date
service_date
total_amount
net_amount
vat_amount
IBAN
payment_purpose_code
purchasing_order
currency

and line items fields:

item_code
item_description
unit
net_amount
vat_amount
gross_amount
discount_percentage
discount
unit_price
quantity
vat_rate

2. Extract data from documents

👍 For the Pretrained model, we do not need to train the suppliers - we can start extracting data right away.

Here are two examples of invoices that you can use for data extraction:

Download them and extract the data using the code:

1 Open file as base64 string (Lines 6-7)

Make sure that you are pointing to the correct path.

2 Specify payload (Lines 8-12)

3 Specify headers (Lines 16-20)

4 Make POST request (Lines 22-24)

import requests
import base64

file_name = 'amazing_company_2.pdf'
with open(file_name, 'rb') as file:
    base64_data = base64.b64encode(file.read()).decode('utf-8')

payload = {
    "file": base64_data,
    "file_name": file_name,
    "document_type_name": "line-item-invoice"
}

url = "https://developers.typless.com/api/extract-data"

headers = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": "<<apikey>>"
}

response = requests.request("POST", url, json=payload, headers=headers)

for field in response.json()['extracted_fields']:
    print(f'{field["name"]}: {field["values"][0]["value"]}')

const fetch = require('node-fetch');
const fs = require('fs');

const fileName = 'amazing_company_2.pdf';
const base64File = fs.readFileSync(fileName, {encoding: 'base64'});

const url = 'https://developers.typless.com/api/extract-data';

const payload = {
  file: base64File,
  file_name: fileName,
  document_type_name: "line-item-invoice"
}

const headers = {
  'Accept': 'application/json',
  'Content-Type': 'application/json',
  'Authorization': '<<apikey>>'
}

let options = {
  method: 'POST',
  headers: headers,
  body: JSON.stringify(payload)
};

fetch(url, options)
  .then(res => res.json())
  .then(json => {
      json.extracted_fields.forEach(field => console.log(`${field.name}: ${field.values[0].value}`))
      json.line_items.forEach(
        line_item => {
          console.log('Line item')
          line_item.forEach(field => console.log(`${field.name}: ${field.values[0].value}`))
        }
      )
    }
  )
  .catch(err => console.error('error:' + err));

Response:

// Example extraction response - the provided recipe will not produce equal results
{
    "file_name": "invoice_2.pdf",
    "object_id": "1cb25cc8-c9fa-4149-9a83-b4ed6a2173b9",
    "extracted_fields": [
        {
            "name": "supplier",
            "values": [
                {
                    "x": -1,
                    "y": -1,
                    "width": -1,
                    "height": -1,
                    "value": "ScaleGrid",
                    "confidence_score": "0.968",
                    "page_number": -1
                }
            ],
            "data_type": "AUTHOR"
        },
        {
            "name": "invoice_number",
            "values": [
                {
                    "x": 1989,
                    "y": 545,
                    "width": 323,
                    "height": 54,
                    "value": "20190500005890",
                    "confidence_score": "0.250",
                    "page_number": 0
                },
                {
                    "x": 167,
                    "y": 574,
                    "width": 391,
                    "height": 54,
                    "value": "GB123456789",
                    "confidence_score": "0.250",
                    "page_number": 0
                }
            ],
            "data_type": "STRING"
        },
        {
            "name": "issue_date",
            "values": [
                {
                    "x": 2072,
                    "y": 628,
                    "width": 240,
                    "height": 54,
                    "value": "2019-06-05",
                    "confidence_score": "0.358",
                    "page_number": 0
                }
            ],
            "data_type": "DATE"
        },
        {
            "name": "total_amount",
            "values": [
                {
                    "x": 2146,
                    "y": 1196,
                    "width": 126,
                    "height": 54,
                    "value": "47.5300",
                    "confidence_score": "0.990",
                    "page_number": 0
                }
            ],
            "data_type": "NUMBER"
        }
    ],
    "line_items": [
        [
            {
                "name": "Description",
                "values": [
                    {
                        "x": 208,
                        "y": 1196,
                        "width": 1022,
                        "height": 50,
                        "value": "5/2019-MongoBackend-MgmtStandalone-Small-744 hours",
                        "confidence_score": "0.661",
                        "page_number": 0
                    }
                ],
                "data_type": "STRING"
            },
            {
                "name": "Price",
                "values": [
                    {
                        "x": 2146,
                        "y": 1196,
                        "width": 126,
                        "height": 54,
                        "value": "47.5300",
                        "confidence_score": "0.582",
                        "page_number": 0
                    }
                ],
                "data_type": "NUMBER"
            },
            {
                "name": "Quantity",
                "values": [
                    {
                        "x": 1979,
                        "y": 1196,
                        "width": 23,
                        "height": 54,
                        "value": "1",
                        "confidence_score": "0.647",
                        "page_number": 0
                    }
                ],
                "data_type": "NUMBER"
            }
        ]
    ],
    "customer": null
}

Need a more in-depth explanation of the response? You can read about it here.

Running Typless live

The only thing that you need to do to automate your manual data entry is to integrate those simple API calls into your system.

Have any questions or need some help? Contact us via chat or email support@typless.com

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