Azure - Building Multimodal Generative Experiences. Part 2
Manjunatha Sai Uppu
Posted on May 31, 2024
Previous Post Link
Create a composed Document Intelligence Model
- Composed models in Azure AI document intelligence enable users to submit a form when they don't know which is the best model to use.
- Composed Models
- when you have forms with unusual or unique formats, you can create and train your own custom models in Azure AI Document Intelligence.
- You can create custom model of 2 types (custom template model and custom neural models) refer to previous post to know more about them.
- Once you have created a set of custom models, you must assemble them into a composed model. you can do this on the Azure AI Studio.
- Custom model Compatibility
- Custom template models are responsible with other custom template models across 3.0 and 2.1 API versions
- Custom neural models are composable with other custom neural models.
- Custom neural models can't be composed with custom template models.
- Custom models
Build a document intelligence custom skill for azure search.
- If you integrate AI Search with an Azure AI Document intelligence solution, you can enrich your index with fields that your Azure AI Document Intelligence models are trained to extract.
- Azure AI Search is a search service hosted in Azure that can index content on your permises or in a cloud location.
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There are 5 stages in Indexing process
- Document Cracking. In document cracking, the indexer opens the content files and extracts their content.
- Field Mappings. Fields such as titles, names, dates, and more are extracted from the content. You can use field mappings to control how they're stored in the index.
- Skillset Execution. In the optional skillset execution stage, custom AI processing is done on the content to enrich the final index.
- Output field mappings. If you're using a custom skillset, its output is mapped to index fields in this stage.
- Push to index. The results of the indexing process are stored in the index in Azure AI Search.
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AI Search Skillset
- Key Phrase extraction
- Language Detection
- Merge
- Sentiment
- Translation
- Image Analysis
- Optical character recognition
we can use custom skills too and they can be used for 2 reasons
The list of built-in skills doesn't include the type of AI Enrichment you need.
you want to train your own model to analyze the data
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2 types of custom skills that you can create
- Azure Machine Learning Custom Skills
- Custom Web API Skills Refer to this link for building an Azure AI Document Intelligence Custom Skill
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Manjunatha Sai Uppu
Posted on May 31, 2024
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