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Welcome to the Saga Python Bridge Vectorization application for Aspire page.  A central location for all information on crawling and processing content using the Aspire Python Bridge Vectorization application and associated components.Deploy on-premise python models BERT, MiniLM, T5, GTR-T5 for vector embedding generation of the content extracted from the documents. It can handle one text per document or an array of text segments to get the embeddings for them.

Prerequisites

About the Saga Python Bridge Vectorization Embeddings application for Aspire, how it works, and features.

How to Configure

This is a step-by-step tutorial to configure the Saga Python Bridge Vectorization Embeddings application.

Troubleshooting

These are common questions and answers, as well as troubleshooting techniques for the Saga Python Bridge Vectorization Embeddings application.