Categories:
Build experiences that call Semantic Search
How to build an end-to-end experience that uses the Semantic Search stage (OpenAI embeddings recognizer), within NLP as a service
Introduction
Within [NLP as a Service], the Semantic Search capability enables the use of Azure OpenAI embeddings for the development of generic questions experiences (grounded in FAQs).
Steps in the process
a. Prequisites: Install and enable
GES team / Kernel DevOps Team
Is aura-gateway-api published in Kernel? If not:
Publish the aura-gateway-api API in Kernel as a prerequisite to call this API
GES team
Check if your Kernel token has already expired. If so:
Get a valid Kernel two-legged token
b. Configure
Use case constructor
Configure an application to connect with aura-gateway-api
c. Build & test
Content manager
Prepare the FAQ contents and answers used by the Semantic Search stage
Use case constructor
Generate and deploy the NLP recognition package for your use case
For the Semantic Search capability, the stage OpenAI embeddings is used
Use case constructor
Make a request to Aura NLP resolution API