Quick start

Get Typless up and running in 5 minutes!

Typless is an AI-powered document extraction platform for automating manual data entry from any document. With an easy-to-use API, you can extract data with a single call in a matter of seconds.

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 Simple invoice template and click Create document type. This will create a new document type with the name simple-invoice and the following fields:

supplier_name
invoice_number
pay_due_date
issue_date
total_amount

2. Get your API key

To use the Typless API, you need to authorize your requests with an API key. The Authorization header for your API key is: Token YOUR-API-KEY (Login if you do not see one) To obtain the API key, visit the Settings page.

3. Adding a new supplier

Typless is a tool for automation. That's why you need to fill the dataset and train it first. To automate a new supplier, you need first to add its invoices to the data setto first add its invoices to the data set. Download an invoice from Amazing Company:

Amazing company - download.

To add a document to the dataset, use the add-document endpoint or use the training room, where you can easily upload a file and fill out the necessary information.

The dataset is created by uploading an original file with the correct value for each field defined inside the document type:

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

Open the file and encode it as a base64 String. Make sure you are pointing to the directory with the file.

2 Specify your payload with the needed fields (Lines 11-38)

file - base64 encoded file

file_name - Name of the file

document_type_name - the name of the document type we want to add the supplier to

learning_fields - fields with the correct values used for training

3 Specify headers (Lines 34-38)

Add all the needed request headers.

4 Send the request (Lines 46-48)

Send the request and make sure that everything went smoothly.

import requests
import base64

file_name = 'amazing_company_1.pdf'
# Make sure that you are pointing to the directory with file
with open(file_name, 'rb') as file:
    base64_data = base64.b64encode(file.read()).decode('utf-8')

url = "https://developers.typless.com/api/add-document"

payload = {
    "learning_fields": [
        {
            "name": "supplier_name",
            "value": "Amazing Company"
        },
        {
            "name": "invoice_number",
            "value": "333"
        },
        {
            "name": "issue_date",
            "value": "2021-02-01"
        },
        {
            "name": "pay_due_date",
            "value": "2021-03-31"
        },
        {
            "name": "total_amount",
            "value": "15.0000"
        }
    ],
    "line_items": [],
    "file": base64_data,
    "file_name": file_name,
    "document_type_name": "simple-invoice"
}

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

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

print(response.json())

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

const fileName = 'amazing_company_1.pdf';
const base64File = fs.readFileSync(fileName, {encoding: 'base64'});

let url = 'https://developers.typless.com/api/add-document';

const payload = {
  file: base64File,
  file_name: fileName,
  document_type_name: "simple-invoice",
  learning_fields: [
    {
        name: "supplier_name",
       value: "Amazing Company"
    },
    {
        name: "invoice_number",
        value: "333"
    },
    {
        name: "pay_due_date",
        value: "2021-03-31"
    },
    {
        name: "issue_date",
        value: "2021-02-01"
    },
    {
        name: "total_amount",
        value: "15.00"
    }
  ]
};


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 => console.log(json))
  .catch(err => console.error('error:' + err));

import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.Base64;
import com.squareup.okhttp.*;


public class AddSupplier {
    public static void main(String[] args) {
        String apiUrl = "https://developers.typless.com/api/add-document";
        String apiKey = "<<apiKey>>";

        String fileName = "amazing_company_1.pdf";
        String resourcesDirectory = "src/main/resources";
        File file = new File(resourcesDirectory, fileName);
        String base64File = encodeFileToBase64(file);

        String jsonString = "{\"file\":\"" + base64File + "\",\"file_name\":\"" + fileName + "\",\"document_type_name\":\"simple-invoice\",\"learning_fields\":[{\"name\":\"supplier_name\",\"value\":\"Amazing Company\"},{\"name\":\"invoice_number\",\"value\":\"333\"},{\"name\":\"issue_date\",\"value\":\"2021-02-01\"},{\"name\":\"pay_due_date\",\"value\":\"2021-03-31\"},{\"name\":\"total_amount\",\"value\":\"15.0000\"}]}";

        try {
            String response = addDocumentFeedback(apiUrl, apiKey, jsonString);
            System.out.println(response);
        } catch (IOException e) {
            System.out.println(e);
        }
    }

    private static String addDocumentFeedback(String apiUrl, String token, String json) throws IOException {
        MediaType JSON = MediaType.parse("application/json");
        OkHttpClient client = new OkHttpClient();
        RequestBody body = RequestBody.create(JSON, json);
        Request request = new Request.Builder()
                .url(apiUrl)
                .post(body)
                .addHeader("Accept", "application/json")
                .addHeader("Content-Type", "application/json")
                .addHeader("Authorization", token)
                .build();
        Response response = client.newCall(request).execute();
        return response.body().string();
    }

    private static String encodeFileToBase64(File file) {
        try {
            byte[] fileContent = Files.readAllBytes(file.toPath());
            return Base64.getEncoder().encodeToString(fileContent);
        } catch (IOException e) {
            throw new IllegalStateException("could not read file " + file, e);
        }
    }
}

using System;
using System.IO;
using RestSharp;

class AddDocument
{

  static void Main(string[] args)
  {

    String apiUrl = "https://developers.typless.com/api/add-document";
    String apiKey = "<<apiKey>>";

    String fileName = "amazing_company_1.pdf";
    String path = Path.Combine("path/to/file", fileName);
    String base64File = encodeFileToBase64(path);

    String jsonString = "{\"file\":\"" + base64File + "\",\"file_name\":\"" + fileName + "\",\"document_type_name\":\"simple-invoice\",\"learning_fields\":[{\"name\":\"supplier_name\",\"value\":\"Amazing Company\"},{\"name\":\"invoice_number\",\"value\":\"333\"},{\"name\":\"issue_date\",\"value\":\"2021-02-01\"},{\"name\":\"pay_due_date\",\"value\":\"2021-03-31\"},{\"name\":\"total_amount\",\"value\":\"15.0000\"}]}";

    String response = addDocumentToDataset(apiUrl, apiKey, jsonString);
    Console.WriteLine(response);
  }


  private static String addDocumentToDataset(String apiUrl, String apiKey, String payload)
  {
    var client = new RestClient(apiUrl);
    var request = new RestRequest(Method.POST);
    request.AddHeader("Accept", "application/json");
    request.AddHeader("Content-Type", "application/json");
    request.AddHeader("Authorization", apiKey);
    request.AddJsonBody(payload);
    return client.Execute(request).Content;
  }

  private static String encodeFileToBase64(String filePath)
  {
    Byte[] bytes = File.ReadAllBytes(filePath);
    return Convert.ToBase64String(bytes);
  }
}

Response:

{
    'details': ['0cbabe33bc9f0f093d2bd06ae3f86240368b6937'], 
    'message': 'Document added successfully.'
}

You have just added your first document to your data set!

4. Execute training

To build the model for extraction, you need to trigger the training. Go to the Dashboard page, look for the simple-invoice document type in the list, and click on the ⚙️ settings icon.

Wait a few moments for the training to finish. You can refresh the status by clicking on the refresh button in the top left part of the table. After the training status says Models trained, the model is ready for data extraction.

5. Extract data from documents

After the training is finished, you can start precisely extracting data from documents from trained suppliers. Download another invoice from Amazing Company:

Amazing company - download.

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

Extract the data:

1 Open file as base 64 string (Lines 4-7)

Open the file in a binary mode and correctly decode it into a base64 string. Make sure that your file is in the same directory as the script.

2 Create Request Payload (Lines 11-15)

Create request payload with all the required parameters:

file
file_name
document_type_name

3 Specify headers (Lines 16-20)

Make sure that the Content-Type is set as application/json

4 Authorize with your API key (Line 19)

If the API key is not filled in, you can get it at https://app.typless.com/settings/profile

5 Execute the request (Lines 24-25)

import requests
import base64

file_name = 'amazing_company_2.pdf'
# Make sure that you are pointing to the directory with file
with open(file_name, 'rb') as file:
    base64_data = base64.b64encode(file.read()).decode('utf-8')

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

payload = {
    "file": base64_data,
    "file_name": file_name,
    "document_type_name": "simple-invoice"
}
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: "simple-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}`))
  })
  .catch(err => console.error('error:' + err));

import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.util.Base64;
import com.squareup.okhttp.*;

public class ExtractData {

    public static void main(String[] args) {
        String apiUrl = "https://developers.typless.com/api/extract-data";
        String apiKey = "<<apiKey>>";

        String fileName = "amazing_company_2.pdf";
        String resourcesDirectory = "src/main/resources";
        File file = new File(resourcesDirectory, fileName);
        String base64File = encodeFileToBase64(file);

        String jsonString = "{\"file\":\""+base64File+"\",\"file_name\":\""+fileName+"\",\"document_type_name\":\"simple-invoice\"}";

        try {
            String response = getExtractedData(apiUrl, apiKey,jsonString);
            System.out.println(response);
        } catch (IOException e) {
            System.out.println(e);
        }
    }

    private static String getExtractedData(String apiUrl, String apiKey, String json) throws IOException {
        MediaType JSON = MediaType.parse("application/json");
        OkHttpClient client = new OkHttpClient();
        RequestBody body = RequestBody.create(JSON, json);
        Request request = new Request.Builder()
                .url(apiUrl)
                .post(body)
                .addHeader("Accept", "application/json")
                .addHeader("Content-Type", "application/json")
                .addHeader("Authorization", apiKey)
                .build();
        Response response = client.newCall(request).execute();
        return response.body().string();
    }

    private static String encodeFileToBase64(File file) {
        try {
            byte[] fileContent = Files.readAllBytes(file.toPath());
            return Base64.getEncoder().encodeToString(fileContent);
        } catch (IOException e) {
            throw new IllegalStateException("could not read file " + file, e);
        }
    }
}

using System;
using System.IO;
using RestSharp;

class ExtractData
{
  static void Main(string[] args)
  {
    String apiUrl = "https://developers.typless.com/api/extract-data";
    String apiKey = "<<apiKey>>";

    String fileName = "amazing_company_2.pdf";
    String examplesPath = "path/to/your/file";
    String path = Path.Combine(examplesPath, fileName);
    String base64File = encodeFileToBase64(path);

    String jsonString = "{\"file\":\"" + base64File + "\",\"file_name\":\"" + fileName + "\",\"document_type_name\":\"simple-invoice\"}";
    String response = getExtractedData(apiUrl, apiKey, jsonString);
    Console.WriteLine(response);
  }

  private static String getExtractedData(String apiUrl, String apiKey, object payload)
  {
    var client = new RestClient(apiUrl);
    var request = new RestRequest(Method.POST);
    request.AddHeader("Accept", "application/json");
    request.AddHeader("Content-Type", "application/json");
    request.AddHeader("Authorization", apiKey);
    request.AddJsonBody(payload);
    return client.Execute(request).Content;
  }
  private static String encodeFileToBase64(String filePath)
  {
    Byte[] bytes = File.ReadAllBytes(filePath);
    return Convert.ToBase64String(bytes);
  }
}

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_name",
            "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": "pay_due_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": []
}
    "customer": null
}

For each of the defined fields, you get an object inside extracted_fields. Every field has up to 5 best-predicted value blocks with coordinates, recognized value, and confidence score. The values are always in a string format.

📘 For simple layouts, one invoice in your data set is enough, but for more complex ones, you may need around 5 from the same supplier.

Congratulations! You just successfully trained and extracted data with Typless. You can now use it to automate manual data entry from any of your invoices.

What’s Next

Now you know the basic concepts of Typless, you can search for some pre-made use cases with examples that can help you satisfy your project requirements and get up and running in a couple of minutes!

Overview →

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Last updated 3 months ago