Python Bot Framework Wrapper

Description: Python wrapper and package for Bot Framework REST API and State REST API (not production ready, yet).

A snippet of a basic bot:

from pybotframework.botframework import BotFramework
from pybotframework.sklearn_connector import SklearnConnector

# Labels for ML model
target_names = ['neg', 'pos']

# Instatiate the connector to custom ML model
sklearn_lang_conn = SklearnConnector(model_file='sentiment.pkl',
                                     target_names=target_names)

# Instatiate the bot
my_app = BotFramework(connectors=[sklearn_lang_conn])

if __name__ == '__main__':
    """Run the Flask app"""
    my_app.run_server(host='0.0.0.0', port=3978, debug=True)

See the README in the examples folder for running a test bot.

Installation

Install the pybotframework package from this repository with

pip install .

or

python setup.py

Requirements for Examples

• Bot Framework Emulator https://github.com/Microsoft/BotFramework-Emulator
• Python installed (Anaconda 3.5 recommended) https://anaconda.org/
• Python experience https://docs.python.org/3/tutorial
• Pybotframework library installed from repo (python setup.py or pip install .)
• Docker (if macOS get https://docs.docker.com/docker-for-mac/install/ and if Windows get https://docs.docker.com/docker-for-windows/install/)
• Ngrok https://ngrok.com/download
• TensorFlow (tensorflow==1.3.0) and Scikit-learn (scikit-learn==0.18.2) installed
• Some knowledge of ML and neural nets (helpful)

You will also need the following models and data:

• Scikit-learn sentiment model (click to download)

• TensorFlow word2vec model (click to download)

Docker Instructions

To build and run the Docker image ensure you have Docker running. https://docs.docker.com/engine/installation/

Then set up the botframework emulator.

https://docs.microsoft.com/en-us/bot-framework/debug-bots-emulator

Make sure to go through the "Install and configure ngrok" settings (ensure you have ngrok installed - see Requirements above). Uncheck the "Bypass ngrok for local addresses" to enable the bot to talk with Docker.

Now build the Docker image on the command line.

cd <pybotframework base directory>

docker build .

docker images

Search for your Docker "Image ID" in the list

docker run -p 3978:3978 -id <image ID> python

docker ps

You should see your container ID running.

Now try to connect to the bot by entering the address in the Emulator: http://localhost:3978/api/messages

You should see the messages "User added!" and "Bot added!" This means that you are set up!

Links

• Flask project

• Microsoft Bot Framework