Azure AI Document Intelligence is a cloud service that uses machine learning to analyze text and structured data from documents. The Document Intelligence software development kit (SDK) is a set of libraries and tools that enable you to easily integrate Document Intelligence models and capabilities into your applications. Document Intelligence SDK is available across platforms in C#/.NET, Java, JavaScript, and Python programming languages.
Supported programming languages
Document Intelligence SDK supports the following languages and platforms:
Use Document Intelligence SDK in your applications
The Document Intelligence SDK enables the use and management of the Document Intelligence service in your application. The SDK builds on the underlying Document Intelligence REST API allowing you to easily use those APIs within your programming language paradigm. Here's how you use the Document Intelligence SDK for your preferred language:
Here's where to find your Document Intelligence API key in the Azure portal:
Important
We recommend Microsoft Entra ID authentication with managed identities for Azure resources to avoid storing credentials with your applications that run in the cloud.
If you use an API key, store it securely somewhere else, such as in Azure Key Vault. Don't include the API key directly in your code, and never post it publicly.
//set `<your-endpoint>` and `<your-key>` variables with the values from the Azure portal to create your `AzureKeyCredential` and `DocumentIntelligenceClient` instance
string key = "<your-key>";
string endpoint = "<your-endpoint>";
AzureKeyCredential credential = new AzureKeyCredential(key);
DocumentIntelligenceClient client = new DocumentIntelligenceClient(new Uri(endpoint), new AzureKeyCredential(key));
// create your `DocumentIntelligenceClient` instance and `AzureKeyCredential` variable
DocumentIntelligenceClient documentIntelligenceClient = new DocumentIntelligenceClientBuilder()
.credential(new AzureKeyCredential("<your-key>"))
.endpoint("<your-endpoint>")
.buildClient();
// create your `DocumentIntelligenceClient` instance and `AzureKeyCredential` variable
async function main() {
const client = DocumentIntelligence(process.env["your-endpoint>"], {
key: process.env["<your-key>"],
});
# create your `DocumentIntelligenceClient` instance and `AzureKeyCredential` variable
endpoint = "<your-endpoint>"
credential = AzureKeyCredential("<your-key>")
document_analysis_client = DocumentIntelligenceClient(endpoint, credential)
Use a Microsoft Entra token credential
Note
Regional endpoints don't support Microsoft Entra authentication. Create a custom subdomain for your resource in order to use this type of authentication.
Authorization is easiest using the DefaultAzureCredential. It provides a default token credential, based upon the running environment, capable of handling most Azure authentication scenarios.
Grant access to Document Intelligence by assigning the Cognitive Services User role to your service principal.
Set the values of the client ID, tenant ID, and client secret in the Microsoft Entra application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, and AZURE_CLIENT_SECRET, respectively.
Create your DocumentIntelligenceClient instance including the DefaultAzureCredential:
string endpoint = "<your-endpoint>";
var client = new DocumentIntelligenceClient(new Uri(endpoint), new DefaultAzureCredential());
Grant access to Document Intelligence by assigning the Cognitive Services User role to your service principal.
Set the values of the client ID, tenant ID, and client secret of the Microsoft Entra application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, and AZURE_CLIENT_SECRET, respectively.
Create your DocumentIntelligenceClient instance and TokenCredential variable:
TokenCredential credential = new DefaultAzureCredentialBuilder().build();
DocumentIntelligenceClient documentIntelligenceClient = new DocumentIntelligenceClientBuilder()
.endpoint("{your-endpoint}")
.credential(credential)
.buildClient();
Grant access to Document Intelligence by assigning the Cognitive Services User role to your service principal.
Set the values of the client ID, tenant ID, and client secret of the Microsoft Entra application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, and AZURE_CLIENT_SECRET, respectively.
Create your DocumentIntelligenceClient instance including the DefaultAzureCredential:
const { DocumentIntelligenceClient } = require("@azure-rest/ai-document-intelligence@1.0.0");
const { DefaultAzureCredential } = require("@azure/identity");
const client = new DocumentIntelligenceClient("<your-endpoint>", new DefaultAzureCredential());
Grant access to Document Intelligence by assigning the Cognitive Services User role to your service principal.
Set the values of the client ID, tenant ID, and client secret of the Microsoft Entra application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, and AZURE_CLIENT_SECRET, respectively.
Create your DocumentIntelligenceClient instance including the DefaultAzureCredential:
from azure.identity import DefaultAzureCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
credential = DefaultAzureCredential()
client = DocumentIntelligenceClient(
endpoint="<your-endpoint>",
credential=credential
)
Create a client object to interact with the Document Intelligence SDK, and then call methods on that client object to interact with the service. The SDKs provide both synchronous and asynchronous methods. For more insight, try a quickstart in a language of your choice.
Help options
The Microsoft Q&A and Stack Overflow forums are available for the developer community to ask and answer questions about Azure AI Document Intelligence and other services. Microsoft monitors the forums and replies to questions that the community has yet to answer. To make sure, use the following tags so that we see your question.
REST API version 2024-11-30 GA