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.
This samples requires prerequisites in order to run.
This bot uses QnA Maker Service, an AI based cognitive service, to implement simple Question and Answer conversational patterns.
QnA knowledge base setup and application configuration steps can be found here.
- Clone the repository
git clone https://github.com/Microsoft/botbuilder-samples.git- Bring up a terminal, navigate to
botbuilder-samples\samples\python\11.qnamakerfolder - Activate your desired virtual environment
- In the terminal, type
pip install -r requirements.txt - Update
QNA_KNOWLEDGEBASE_ID,QNA_ENDPOINT_KEY, andQNA_ENDPOINT_HOSTinconfig.py - Run your bot with
python app.py
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
- Launch Bot Framework Emulator
- File -> Open Bot
- Paste this URL in the emulator window - http://localhost:3978/api/messages
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.
To learn more about deploying a bot to Azure, see Deploy your bot to Azure for a complete list of deployment instructions.