Auto reply suggestions to chat messages/emails built using rasa_nlu framework.

1. Make sure you have git, python, virtualenv and npm installed
2. Clone the repository git clone https://github.com/varunon9/chat-reply-suggestions.git
3. Go to project directory cd chat-reply-suggestions/
4. Create a virtual environment virtualenv venv
5. Activate virtual environment source venv/bin/activate
6. Install Rasa NLU as well as spacy pip install rasa_nlu[spacy] --default-timeout=100
7. Install language model for the english language python -m spacy download en_core_web_md
8. Link to model data python -m spacy link en_core_web_md en
9. Install some additional dependencies pip install -r requirements.txt
10. Place your nlu_data.json file inside data directory (a sample file is provided).
11. Train the intent models using below command
12. python -m rasa_nlu.train --config config_spacy.yml --data data/nlu_data.json --path projects
13. Install node dependencies npm install
14. Start nlu server in current terminal python -m rasa_nlu.server --path projects
15. Open another terminal in same project directory (no need to activate virtual environment)
16. Start the app node index.js

• The above app uses sample data (collected by me) for demo. Bot can be made more efficient by training with more real world data.
• Currently suggestions are bunch of hardcoded arrays based on intent. Entity recognition can be done and suggestions can be generated on the fly.

• https://youtu.be/MCBmbJyoamY