DeepPavlov is a comprehensive open source framework for building chatbots and other conversational agents for a variety of purposes and tasks. While this bot is designed for more goal-oriented bots, it will suit us well, as it is full-featured and includes several sequence-to-sequence model variations. Let's take a look at how to build a simple pattern (sequence-to-sequence) recognition model in the following steps:
- Up until now, we have kept our Python environment loose, but that has to change. We now want to isolate our development environment so that we can easily replicate it to other systems later. The best way to do this is working with Python virtual environments. Create a new environment and then activate it with the following commands at an Anaconda window:
#Anaconda virtual environment
conda create --name dlgames
#when prompted choose yes
activate dlgames...
