Reddit JSON => mysqlite db => training files => train chatbot => interact with chatbot

1. Git clone https://github.com/davetlewis-van/APy.git into a new directory.
2. wget http://downloads.activestate.com/ActivePython/releases/3.6.0.3600/ActivePython-3.6.0.3600-linux-x86_64-glibc-2.3.6-401834.tar.gz
3. docker build -t "python36:dockerfile" .
4. docker run -it python36:dockerfile
5. There are sample training files, but you can copy the training files you want to use to the new_data folder. If so, you need to adjust the files listed at the top of prepare_data.py and dev_prefix and test_prefix in settings.py
6. Navigate to the /code/nmt-chatbot/setup folder and run prepare_data.py
7. Navigate to the /code/nmt-chatbot/ folder and run train.py
8. To interact with the chatbot run inference.py

• Public IP: https://35.230.32.103
• Jupyter notebook access: sudo jupyter notebook -ip 0.0.0.0 --port 8888 --allow-root
• TensorBoard config:
  1. Create firewall rule for port 6006
  2. cd nmt-chatbot/model
  3. tensorboard --logdir=train_log/ --host 0.0.0.0 --port 6006
  4. Browse to: http://35.230.32.103:6006/#projector&run=.

• PythonProgramming.net chatbot tutorials
• AI and Chatbots in Technical Communication
• Google Dialogflow

• JSON
• Google BigQuery

• Kaggle

  • Questions.csv
  • Answers.csv
  • Tags.csv

• Google BigQuery

• Get access to a GPU
• Figure out how to access my programming-specific BigQuery tables from the Google Cloud VM instance.
• Figure out how to read in Stack Overflow Q&A
• Run docker container on Google Cloud VM

Copyright (c) 2018 ActiveState Software Inc. Released under the BSD-3 license. See LICENSE file for details.