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Chatbot with RASA | Valuebound

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Presentation on chatbot created using RASA NLU and RASA CORE with slack as its communication platform. This is Artificial Intelligence usage in Drupal. We have covered this topic in an online event "Drupal and Artificial Intelligence for Personalization" on May 18th

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Chatbot with RASA | Valuebound

  1. 1. Chatbot with RASA BY VALUEBOUND
  2. 2. INTRODUCTION ● This is a chatbot created using RASA NLU and RASA CORE with slack as its communication platform. ● Rasa NLU will understand the natural language. ● Rasa core will maintain the dialogue flow.
  3. 3. REQUIREMENTS To run this application below are the requirements: a. Anaconda3 or Virtualenv a. npm and node
  4. 4. INSTALLATION Install anaconda3 or virtualenv a. Follow the below link to setup anaconda https://www.digitalocean.com/community/tutorials/how-to-install-the-anaconda- python-distribution-on-ubuntu-16-04 Install node and npm a. Follow the below link to setup node and npm https://www.digitalocean.com/community/tutorials/how-to-install-node-js-on-ubuntu- 16-04
  5. 5. INSTALLATION Create Environment source activate venv Setting up Get the project repo and do the following operation for setup ➔ git clone https://path/to/repository/rasa-bot.git ➔ cd rasa_app ➔ pip install -r requirements.txt ➔ python -m spacy download en ➔ npm i -g rasa-nlu-trainer
  6. 6. CONNECTION/CLIEN T Here we are using slack as a communication channel. So to work with slack we have to do the following. Create your own slack workspace or use existing one if you have the permission to integrate third party app. Get the legacy token which you will be using on your app to communicate. Workspace: [yourworkspace].slack.com ● Username: yourusername ● Password: yourpassword Tokens: https://api.slack.com/custom-integrations/legacy-tokens
  7. 7. CONNECTION/CLIEN T To setup slack app : ➔ Goto https://api.slack.com ➔ Click on Your Apps
  8. 8. INSTANCES There is three part of this app. ➔ NLU training model ➔ NLU trainer UI ➔ RASA core
  9. 9. INSTANCES NLU Training MODEL Every model we have to train manually with some dummy data. The more the sample data the more will be the accuracy label. Below is the step to train a model. ➔ Open nlu_model.py ➔ Uncomment train_nlu('./data/data.json…….. In last if statement ➔ Comment run_nlu() ➔ Run python nlu_model.py
  10. 10. INSTANCES NLU trainer UI This application contains a rasa nlu trainer which will give you to add/edit the sample data using a UI. Where you can add statement or select entity or intent. ➔ Run rasa-nlu-trainer
  11. 11. INSTANCES Rasa Core This is used to control the dialogue flow and manage the session data. Find which RASA NLU Version you are running python -c "import rasa_nlu; print(rasa_nlu.__version__);" Output: 0.11.3 Ref: https://nlu.rasa.ai/ Language Understanding with rasa NLU
  12. 12. INSTANCES Find Which Node Package Manager you are using npm -v Output: 5.6.0 Find Which Node you are using node -v Output: v9.8.0
  13. 13. REFERENCES ➔ http://rasa-nlu.readthedocs.io/en/latest/tutorial.html ➔ https://core.rasa.ai/tutorial_basics.html