Form Recognizer API (v2.0)

On 31 August 2026 Azure AI Document Intelligence (formerly known as Azure Form Recognizer) v2.0 API will be retired. Please transition to Azure AI Document Intelligence v3.1 API by that date following the detailed steps.

Form Recognizer extracts information from forms and images into structured data. It includes the following options: * Form - 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. * Receipt - Detects and extracts data from receipts using optical character recognition (OCR) and our receipt model, enabling you to easily extract structured data from receipts such as merchant name, merchant phone number, transaction date, transaction total, and more. * Layout - Extracts text and table structure from documents using optical character recognition (OCR).

Analyze Layout - Get Analyze Layout Result

Track the progress and obtain the result of the analyze layout operation

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

Open API testing console

Request URL

Request parameters

string

Format - uuid. Analyze operation result identifier.

Request headers

string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.

Request body

Response 200

JSON fields in the response body:

Field Type Description
status String Analyze Layout operation status. Possible values:
  • notStarted: The analysis operation has not started.
  • running: The analysis operation is in progress.
  • failed: The analysis operation has failed.
  • succeeded: The analysis operation has succeeded.
If the status is succeeded, the response JSON will include the layout and text recognition results. The layout result is organized as a list of tables for each page. When includeTextDetails is true, the detailed text recognition result is organized as a hierarchy of lines and words, with text, bounding box and confidence information.
createdDateTime String Date and time (UTC) when the operation was created.
lastUpdatedDateTime String Date and time (UTC) when the status is last updated.
analyzeResult Object Results of the analyze operation.
version String The version of schema used for this result.
readResults [Object] List of of extracted text result for each page in the input document.
page Integer The 1-based page number in the input document.
width Number The width of the image/PDF in pixels/inches, respectively.
height Number The height of the image/PDF in pixels/inches, respectively.
unit String The unit used by the width, height and boundingBox properties. For images, the unit is "pixel". For PDF, the unit is "inch".
angle Number The general orientation of the text in clockwise direction, measured in degrees between (-180, 180].
language String The detected language on the page overall or of a specific line if different from the page.
lines [Object] List of text lines. The lines are sorted top to bottom, left to right, although in certain cases proximity is treated with higher priority. As the sorting order depends on the detected text, it may change across images and OCR version updates. Thus, business logic should be built upon the actual line location instead of order. This field only appears when includeTextDetails is set to true.
words [Object] List of words in the text line.
boundingBox [Number] Quadrangle bounding box of a line or word, depending on the parent object, specified as a list of 8 numbers. The coordinates are specified relative to the top-left of the original image. The eight numbers represent the four points, clockwise from the top-left corner relative to the text orientation. For image, the (x, y) coordinates are measured in pixels. For PDF, the (x, y) coordinates are measured in inches.
text String Extracted field text in documentResults, or the text content of a word/line in readResults.
confidence Number Confidence value.
pageResults [Object] Page-level information extracted from the input.
page Integer Page number.
tables [Object] List of data tables extracted from the page.
rows Integer Number of rows.
columns Integer Number of columns.
cells [Object] List of cells contained in the table.
rowIndex Integer Row index of the cell.
columnIndex Integer Column index of the cell.
rowSpan Integer Number of rows spanned by this cell.
columnSpan Integer Number of columns spanned by this cell.
elements [String] When includeTextDetails is set to true, a list of JSON references to the text elements constituting this field.

Response 404

Invalid or expired result identifier.

{
  "error": {
    "code": "BadArgument",
    "message": "Operation ID is invalid or expired."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Response 500

Internal server error.

{
  "error": {
    "code": "Unspecified",
    "message": "Internal server error."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Response 503

Transient fault while querying Microsoft Azure storage services.

{
  "error": {
    "code": "StorageException",
    "message": "Transient fault occurred while querying Microsoft Azure storage services. Please try again later."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Code samples

@ECHO OFF

curl -v -X GET "https://*.cognitiveservices.azure.com/formrecognizer/v2.0/layout/analyzeResults/{resultId}"
-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/v2.0/layout/analyzeResults/{resultId}?" + queryString;

            var response = await client.GetAsync(uri);
        }
    }
}	
// // 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/v2.0/layout/analyzeResults/{resultId}");


            URI uri = builder.build();
            HttpGet request = new HttpGet(uri);
            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/v2.0/layout/analyzeResults/{resultId}?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
            },
            type: "GET",
            // 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/v2.0/layout/analyzeResults/{resultId}";
    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:@"GET"];
    // Request headers
    [_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/v2.0/layout/analyzeResults/{resultId}');
$url = $request->getUrl();

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

$request->setHeader($headers);

$parameters = array(
    // Request parameters
);

$url->setQueryVariables($parameters);

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

// 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
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.urlencode({
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("GET", "/formrecognizer/v2.0/layout/analyzeResults/{resultId}?%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
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.parse.urlencode({
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("GET", "/formrecognizer/v2.0/layout/analyzeResults/{resultId}?%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/v2.0/layout/analyzeResults/{resultId}')
uri.query = URI.encode_www_form({
})

request = Net::HTTP::Get.new(uri.request_uri)
# 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