You build a QnA Maker bot by using a frequently asked questions (FAQ) page. You need to add professional greetings and other responses to make the bot more user friendly. What should you do?

The chit-chat feature in QnA Maker (now part of Azure AI Language's Custom question answering) is specifically designed to make a bot more conversational and engaging. It allows you to add a pre-populated set of conversational responses for common small talk, such as greetings, goodbyes, and other pleasantries. You can select a specific personality for the bot, including "Professional," which directly addresses the user's need to add professional greetings and make the bot more user-friendly without having to manually create these question-and-answer pairs.

A. Increase the confidence threshold of responses: This adjusts how certain the service must be to return an answer. It filters out less relevant answers but does not add new conversational content like greetings.

B. Enable active learning: This feature suggests new question variations to add to your knowledge base based on user queries, improving the accuracy of existing answers, not adding general small talk.

C. Create multi-turn questions: This feature helps guide users to a specific answer through follow-up prompts. It is used for disambiguation within a topic, not for general, out-of-context greetings.

1. Microsoft Learn

"Add chit-chat to a project": "Adding chit-chat to your bot makes it more conversational and engaging. The chit-chat feature in custom question answering allows you to easily add a pre-populated set of the top chit-chat

to your project... When you create your project

you can add a chit-chat data source. You choose the personality you want for your chit-chat. The personalities available are: Professional

Friendly

Witty

Caring

and Enthusiastic."

2. Microsoft Learn

"Confidence score": "The confidence score indicates the confidence that the answer is the correct match for a given user query... By default the threshold is set to 0

so all possible answers are returned." This confirms its role as a filter

not a content source.

3. Microsoft Learn

"Active learning suggestions": "Active learning gives you suggestions for new question and answer pairs to add to your project based on user queries that are hitting your published project." This clarifies its purpose is to improve the existing knowledge base.

4. Microsoft Learn

"Use follow-up prompts to create multiple turns of a conversation": "Custom question answering lets you add follow-up prompts to question and answer pairs. This feature lets your client application provide a determined conversation flow with the user to reveal the correct answer." This shows its function is for guided conversations

not general greetings.