Skip to content

Latest commit

 

History

History
 
 

11.qnamaker

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
bots
bots
 
 
cognitiveModels
cognitiveModels
 
 
deploymentTemplates
deploymentTemplates
 
 
README.md
README.md
 
 
app.py
app.py
 
 
config.py
config.py
 
 
requirements.txt
requirements.txt
 
 

README.md

QnA Maker

Bot Framework v4 QnA Maker bot sample

This bot has been created using Bot Framework, it shows how to create a bot that uses the QnA Maker Cognitive AI service.

The QnA Maker Service enables you to build, train and publish a simple question and answer bot based on FAQ URLs, structured documents or editorial content in minutes. In this sample, we demonstrate how to use the QnA Maker service to answer questions based on a FAQ text file used as input.

Prerequisites

This samples requires prerequisites in order to run.

Overview

This bot uses QnA Maker Service, an AI based cognitive service, to implement simple Question and Answer conversational patterns.

Create a QnAMaker Application to enable QnA Knowledge Bases

QnA knowledge base setup and application configuration steps can be found here.

Running the sample

  • Clone the repository
git clone https://github.com/Microsoft/botbuilder-samples.git
  • Bring up a terminal, navigate to botbuilder-samples\samples\python\11.qnamaker folder
  • Activate your desired virtual environment
  • In the terminal, type pip install -r requirements.txt
  • Update QNA_KNOWLEDGEBASE_ID, QNA_ENDPOINT_KEY, and QNA_ENDPOINT_HOST in config.py
  • Run your bot with python app.py

Testing the bot using Bot Framework Emulator

Microsoft Bot Framework Emulator is a desktop application that allows bot developers to test and debug their bots on localhost or running remotely through a tunnel.

  • Install the Bot Framework emulator from here

Connect to bot using Bot Framework Emulator

QnA Maker service

QnA Maker enables you to power a question and answer service from your semi-structured content.

One of the basic requirements in writing your own bot is to seed it with questions and answers. In many cases, the questions and answers already exist in content like FAQ URLs/documents, product manuals, etc. With QnA Maker, users can query your application in a natural, conversational manner. QnA Maker uses machine learning to extract relevant question-answer pairs from your content. It also uses powerful matching and ranking algorithms to provide the best possible match between the user query and the questions.

Deploy the bot to Azure

To learn more about deploying a bot to Azure, see Deploy your bot to Azure for a complete list of deployment instructions.

Further reading