Document Text extraction model

Vusirikala, Aishwarya 0 Reputation points
2025-02-06T12:46:12.8766667+00:00

I have created a model for "Document Text extraction" under Azure AI foundry. I would like to use the model that i have created in my python code. How do i use the model to extract the fields from the files?

Azure AI Document Intelligence
Azure AI Document Intelligence
An Azure service that turns documents into usable data. Previously known as Azure Form Recognizer.
1,971 questions
0 comments No comments
{count} votes

1 answer

Sort by: Most helpful
  1. Vikram Singh 2,390 Reputation points Microsoft Employee
    2025-02-06T14:22:05.45+00:00

    Hi Vusirikala, Aishwarya

    Welcome to the Microsoft Q&A Forum! Thank you for posting your query here.

    To utilize your custom "Document Text Extraction" model from Azure AI Foundry in your Python application. Here's how you can use the model to extract fields in your code:

    1. Deploy the Model: First, ensure that your model is deployed in Azure AI Foundry. You can do this by navigating to your Azure AI Foundry project, selecting "Management center" from the left pane, and then selecting "Models + endpoints" under the Project section.
    2. Get the REST Endpoint: Once your model is deployed, you will need the REST endpoint prediction URL. You can get this by selecting the model you want to deploy and noting the REST endpoint provided.
    3. Use the Python SDK: You can use the Azure AI Document Intelligence SDK or the REST API to apply your custom model for inferencing.
    4. Extract Fields: The response will contain the extracted fields from your document. You can parse this JSON response to get the specific fields you need.

    For more detailed guidance, you can refer to the official Microsoft documentation: How to use Azure AI services in Azure AI Foundry portal

    Additionally, the Azure AI Document Intelligence client library for Python provides detailed information on processing documents and extracting text using the SDK.

    I hope this is helpful!

    Thanks

    Please do not forget to "Accept the answer” and “up-vote” wherever the information provided helps you, this can be beneficial to other community members.


Your answer

Answers can be marked as Accepted Answers by the question author, which helps users to know the answer solved the author's problem.