You are very welcome!
Here are the detail steps.
1. Direct Integration with Document Intelligence API:
- This approach involves calling the Document Intelligence API directly within your indexing pipeline. Here's the step-by-step breakdown:
- Preprocess documents: Format your documents for analysis by the Document Intelligence API. This might involve converting them to a supported format (e.g., PDF, PNG, JPG).
- Call the Document Intelligence API: Use the Azure SDK or REST API to call the appropriate endpoint (e.g., "analyzeLayout" for layout extraction). Pass the preprocessed document as input.
- Parse the response: Extract the relevant information from the API response. This might include key-value pairs for identified fields, bounding boxes, or other layout elements.
- Enrich index: Add the extracted information as new fields to your Azure AI Search index using the Search SDK or REST API.
This method involves creating a custom skill that acts as a wrapper for the Document Intelligence API call.- Develop a custom skill:
- This can be implemented as an Azure Function.
- The skill receives the document as input from the Azure AI Search pipeline.
- Call the Document Intelligence API: Inside the custom skill, call the Document Intelligence API using the same process as described in option 1 (steps 2 and 3).
- Process and return output: Parse the API response within the skill.
- Enrich index: The skill should format the extracted information according to the Azure AI Search expected format and then return it. Azure AI Search subsequently adds this information to the index.
Document Extraction with Azure AI Document Intelligence:
Hope this resources will be helpful to you.
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