Form Recognizer 2023-02-28-preview

Form Recognizer extracts information from forms and images into structured data. It includes the following options:

  • Read - Extract text from documents.
  • Layout - Extract text and layout information from documents.
  • Document - Extract text, layout, entities, and general key-value pairs from documents.
  • Business Card - Extract key information from business cards.
  • ID Document - Extract key information from passports and ID cards.
  • Invoice - Extract key information from invoices.
  • Receipt - Extract key information from receipts.
  • US W2 Tax - Extract key information from IRS US W2 tax forms (year 2018-current).
  • Vaccination Card - Extract key information from US Covid-19 CDC vaccination cards.
  • Health Insurance Card - Extract key information from US health insurance cards.
  • US 1098 Tax - Extract key information from United States Internal Revenue Service Form 1098 (2021-current).
  • US 1098-E Tax - Extract key information from United States Internal Revenue Service Form 1098-E (2021-current).
  • US 1098-T Tax - Extract key information from United States Internal Revenue Service Form 1098-T (2021-current).
  • Contract - Extract key information from legal contracts.
  • Custom - Extracts information from forms (PDFs and images) into structured data based on a model created from a set of representative training forms. Form Recognizer learns the structure of your forms to intelligently extract text and data. It ingests text from forms, applies machine learning technology to identify keys, tables, and fields, and then outputs structured data that includes the relationships within the original file.

Create - Build classifier

Build a custom document classifier.

Select the testing console in the region where you created your resource:

Open API testing console

Request URL

Request headers

string
Media type of the body sent to the API.
string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.

Request body

{
  "classifierId": "string",
  "description": "string",
  "buildMode": "template",
  "docTypes": {
    "azureBlobSource": {
      "containerUrl": "string",
      "prefix": "string"
    },
    "azureBlobFileListSource":{
      "containerUrl": "string",
      "fileList": "string"
    }
  }
}
{
  "description": "Request body to build a new custom document model.",
  "type": "object",
  "required": [
    "modelId",
    "buildMode"
  ],
  "properties": {
    "modelId": {
      "description": "Unique document model name.",
      "type": "string",
      "pattern": "^[a-zA-Z0-9][a-zA-Z0-9._~-]{1,63}$"
    },
    "description": {
      "description": "Document model description.",
      "type": "string",
      "maxLength": 4096
    },
    "buildMode": {
      "description": "Custom document model build mode.",
      "type": "string",
      "enum": [
        "template",
        "neural"
      ],
      "x-ms-enum": {
        "name": "DocumentBuildMode",
        "modelAsString": true,
        "values": [
          {
            "value": "template",
            "description": "Target documents with similar visual templates."
          },
          {
            "value": "neural",
            "description": "Support documents with diverse visual templates."
          }
        ]
      }
    },
    "azureBlobSource": {
      "description": "Azure Blob Storage content.",
      "type": "object",
      "required": [
        "containerUrl"
      ],
      "properties": {
        "containerUrl": {
          "description": "Azure Blob Storage container URL.",
          "type": "string",
          "format": "url"
        },
        "prefix": {
          "description": "Blob name prefix.",
          "type": "string"
        }
      }
    },
    "azureBlobFileListSource": {
      "description": "File list in Azure Blob Storage.",
      "type": "object",
      "required": [
        "containerUrl",
        "fileList"
      ],
      "properties": {
        "containerUrl": {
          "description": "Azure Blob Storage container URL.",
          "type": "string",
          "format": "url"
        },
        "fileList": {
          "description": "Path to a JSONL file within the container specifying a subset of documents for training.",
          "type": "string"
        }
      }
    },
    "tags": {
      "description": "List of key-value tag attributes associated with the document model.",
      "type": "object",
      "additionalProperties": {
        "type": "string"
      }
    }
  }
}

Response 202

Request is queued successfully.

Response 400

The top-level error.code property can be one of the following:

Error Code Message
InvalidRequest Invalid request.
InvalidArgument Invalid argument.
When possible, additional details are specified in the innererror property:
Top Error Code Inner Error Code Message
InvalidArgument InvalidContentSourceFormat Invalid content source: {details}
InvalidArgument InvalidParameter The parameter {parameterName} is invalid: {details}
InvalidArgument InvalidParameterLength Parameter {parameterName} length must not exceed {maxChars} characters.
InvalidArgument InvalidSasToken The shared access signature (SAS) is invalid: {details}
InvalidArgument ParameterMissing The parameter {parameterName} is required.
InvalidRequest ContentSourceNotAccessible Content is not accessible: {details}
InvalidRequest ContentSourceTimeout Timeout while receiving the file from client.
InvalidRequest DocumentModelLimit Account cannot create more than {maximumModels} models.
InvalidRequest DocumentModelLimitComposed Account cannot create a model with more than {details} component models.
InvalidRequest InvalidContent The file is corrupted or format is unsupported. Refer to documentation for the list of supported formats.
InvalidRequest InvalidContentDimensions The input image dimensions are out of range. Refer to documentation for supported image dimensions.
InvalidRequest InvalidContentLength The input image is too large. Refer to documentation for the maximum file size.
InvalidRequest InvalidFieldsDefinition Invalid fields: {details}
InvalidRequest InvalidTrainingContentLength Training content contains {bytes} bytes. Training is limited to {maxBytes} bytes.
InvalidRequest InvalidTrainingContentPageCount Training content contains {pages} pages. Training is limited to {pages} pages.
InvalidRequest ModelAnalyzeError Could not analyze using a custom model: {details}
InvalidRequest ModelBuildError Could not build the model: {details}
InvalidRequest ModelNotReady Model is not ready for the requested operation. Wait for training to complete or check for operation errors.
InvalidRequest ModelReadOnly The requested model is read-only.
InvalidRequest NotSupportedApiVersion The requested operation requires {minimumApiVersion} or later.
InvalidRequest OperationNotCancellable The operation can no longer be cancelled.
InvalidRequest TrainingContentMissing Training data is missing: {details}
InvalidArgument InvalidParameterLength Parameter description length must not exceed 4096 characters. 

{
  "error": {
    "code": "InvalidRequest",
    "message": "Invalid request.",
    "innererror": {
      "code": "TrainingContentMissing",
      "message": "Training data is missing: Could not find any training data at the given path."
    }
  }
}

Response 403

The top-level error.code property can be one of the following:

Error Code Message
Forbidden Access forbidden due to policy or other configuration.
When possible, additional details are specified in the innererror property:
Top Error Code Inner Error Code Message
Forbidden AuthorizationFailed Authorization failed: {details}
Forbidden InvalidDataProtectionKey Data protection key is invalid: {details}
Forbidden OutboundAccessForbidden The request contains a domain name that is not allowed by the current access control policy. 

{
  "error": {
    "code": "Forbidden",
    "message": "Access forbidden due to policy or other configuration.",
    "innererror": {
      "code": "OutboundAccessForbidden",
      "message": "The request contains a domain name that is not allowed by the current access control policy."
    }
  }
}

Response 409

The top-level error.code property can be one of the following:

Error Code Message
Conflict The request could not be completed due to a conflict.
When possible, additional details are specified in the innererror property:
Top Error Code Inner Error Code Message
Conflict ModelExists A model with the provided name already exists. 

{
  "error": {
    "code": "Conflict",
    "message": "The request could not be completed due to a conflict with the current state of the target resource.",
    "innererror": {
      "code": "ModelExists",
      "message": "A model with the provided name already exists."
    }
  }
}

Response 500

The top-level error.code property can be one of the following:

Error Code Message
InternalServerError An unexpected error occurred.
When possible, additional details are specified in the innererror property:
Top Error Code Inner Error Code Message
InternalServerError Unknow Unknow error. 

{
  "error": {
    "code": "InternalServerError",
    "message": "An unexpected error occurred.",
    "innererror": {
      "code": "Unknown",
      "message": "Unknown error."
    }
  }
}

Response 503

The top-level error.code property can be one of the following:

Error Code Message
ServiceUnavailable A transient error has occurred. Please try again.
When possible, additional details are specified in the innererror property:
Top Error Code Inner Error Code Message
ServiceUnavailable ServiceUnavailable A transient error has occurred. Please try again. 

{
  "error": {
    "code": "ServiceUnavailable",
    "message": "A transient error has occurred. Please try again.",
    "innererror": {
      "code": "ServiceUnavailable",
      "message": "A transient error has occurred. Please try again."
    }
  }
}

Code samples

@ECHO OFF

curl -v -X POST "https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview"
-H "Content-Type: application/json"
-H "Ocp-Apim-Subscription-Key: {subscription key}"

--data-ascii "{body}" 

using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;

namespace CSHttpClientSample
{
    static class Program
    {
        static void Main()
        {
            MakeRequest();
            Console.WriteLine("Hit ENTER to exit...");
            Console.ReadLine();
        }
        
        static async void MakeRequest()
        {
            var client = new HttpClient();
            var queryString = HttpUtility.ParseQueryString(string.Empty);

            // Request headers
            client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");

            var uri = "https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview&" + queryString;

            HttpResponseMessage response;

            // Request body
            byte[] byteData = Encoding.UTF8.GetBytes("{body}");

            using (var content = new ByteArrayContent(byteData))
            {
               content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
               response = await client.PostAsync(uri, content);
            }

        }
    }
}	
// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class JavaSample 
{
    public static void main(String[] args) 
    {
        HttpClient httpclient = HttpClients.createDefault();

        try
        {
            URIBuilder builder = new URIBuilder("https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview");


            URI uri = builder.build();
            HttpPost request = new HttpPost(uri);
            request.setHeader("Content-Type", "application/json");
            request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");


            // Request body
            StringEntity reqEntity = new StringEntity("{body}");
            request.setEntity(reqEntity);

            HttpResponse response = httpclient.execute(request);
            HttpEntity entity = response.getEntity();

            if (entity != null) 
            {
                System.out.println(EntityUtils.toString(entity));
            }
        }
        catch (Exception e)
        {
            System.out.println(e.getMessage());
        }
    }
}


<!DOCTYPE html>
<html>
<head>
    <title>JSSample</title>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>

<script type="text/javascript">
    $(function() {
        var params = {
            // Request parameters
        };
      
        $.ajax({
            url: "https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview&" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Content-Type","application/json");
                xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
            },
            type: "POST",
            // Request body
            data: "{body}",
        })
        .done(function(data) {
            alert("success");
        })
        .fail(function() {
            alert("error");
        });
    });
</script>
</body>
</html>

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[])
{
    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
    
    NSString* path = @"https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                      ];
    
    NSString* string = [array componentsJoinedByString:@"&"];
    path = [path stringByAppendingFormat:@"?%@", string];

    NSLog(@"%@", path);

    NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
    [_request setHTTPMethod:@"POST"];
    // Request headers
    [_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
    [_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
    // Request body
    [_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
    
    NSURLResponse *response = nil;
    NSError *error = nil;
    NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];

    if (nil != error)
    {
        NSLog(@"Error: %@", error);
    }
    else
    {
        NSError* error = nil;
        NSMutableDictionary* json = nil;
        NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
        NSLog(@"%@", dataString);
        
        if (nil != _connectionData)
        {
            json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
        }
        
        if (error || !json)
        {
            NSLog(@"Could not parse loaded json with error:%@", error);
        }
        
        NSLog(@"%@", json);
        _connectionData = nil;
    }
    
    [pool drain];

    return 0;
}

<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';

$request = new Http_Request2('https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Content-Type' => 'application/json',
    'Ocp-Apim-Subscription-Key' => '{subscription key}',
);

$request->setHeader($headers);

$parameters = array(
    // Request parameters
);

$url->setQueryVariables($parameters);

$request->setMethod(HTTP_Request2::METHOD_POST);

// Request body
$request->setBody("{body}");

try
{
    $response = $request->send();
    echo $response->getBody();
}
catch (HttpException $ex)
{
    echo $ex;
}

?>
########### Python 2.7 #############
import httplib, urllib, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.urlencode({
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview&%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.parse.urlencode({
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview&%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################
require 'net/http'

uri = URI('https://*.cognitiveservices.azure.com/formrecognizer/documentClassifiers:build?api-version=2023-02-28-preview')


request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body