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AI-in-a-Box leverages the expertise of Microsoft across the globe to develop and provide AI and ML solutions to the technical community. Our intent is to present a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction.
This sample shows how to take text documents as a input via BlobTrigger, does Text Summarization processing using the AI Congnitive Language service, and then outputs to another text document using BlobOutput binding. Uses Azure Functions Python v2 programming model.
The Doc Intelligence in-a-Box project leverages Azure AI Document Intelligence to extract data from PDF forms and store the data in a Azure Cosmos DB. This solution, part of the AI-in-a-Box framework by Microsoft Customer Engineers and Architects, ensures quality, efficiency, and rapid deployment of AI and ML solutions across various industries.
This sample shows how to take text documents as a input via BlobTrigger, does Text Summarization processing using the AI Congnitive Language service, and then outputs to another text document using BlobOutput binding.
Construct a high-performance, low-latency data sharing solution between different Azure Storage Accounts using Azure Functions Flex Consumption and the Copy Blob API.