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- Quickstart: Use SDK to create and manage knowledge base - QnA Maker . . .
The runtime QnA Maker client is a QnAMakerRuntimeClient object After you publish your knowledge base using the authoring client, use the runtime client's generateAnswer method to get an answer from the knowledge base
- AI-900: How to test your knowledge base with QnA Maker portal
Learn how to use the built-in test interface in QnA Maker portal to test your knowledge base efficiently and easily Find out why this option is better than making REST API calls or publishing the service and testing it from a custom-built application You are building a user support bot solution with QnA Maker
- front-end search engine for ms marco qna query set, going to evolve . . .
Start your app by running npm start, and start debugging in VS Code by pressing F5 or by clicking the green debug icon You can now write code, set breakpoints, make changes to the code, and debug your newly modified code—all from your editor
- Understanding Automation Testing through QnA - LinkedIn
Data-driven testing is a methodology in which test data is stored separately from test scripts, allowing tests to be run multiple times with different sets of data
- The QnA tool | BigFix Developer
Use of the QnA program is straightforward Simply type Q: followed by a relevance clause, and click the Q A button for evaluation The QnA program can evaluate many queries at the same time It ignores any text not preceded by Q:
- Troubleshooting - QnA Maker - Foundry Tools | Microsoft Learn
The curated list of the most frequently asked questions regarding the QnA Maker service helps you adopt the service faster and with better results
- How to test a knowledge base - QnA Maker - Foundry Tools
You can test the published version of knowledge base in the test pane Once you have published the KB, select the Published KB box and send a query to get results from the published KB
- QnA Maker Runtime Error - Microsoft Q A
QnA Maker is a cloud-based NLP service that easily creates a natural conversational layer over your data It can be used to find the most appropriate answer for any given natural language input, from your custom knowledge base (KB) of information
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