UI Component is developed using Angular 7, and would be supported on all browsers compatible with Angular 7. List of supported browsers at this link
Note : As of now IE is not supported although its listed as supported for Angular 7.
API gateway is a python 3.7 backend, which communicates with UI and database to serve the application. it uses socketio for realtime data exchange between backend and UI.
Application does not provide any authentication methods or role based access control.
Application would create a new database called 'eva_platform' and create collections in that database to store training data. This database can be accessed at port 27017 to view the database and its collections.
Note : We do not recommend updating collections directly as this might case data inconsistency
This is a rasa container, as published by rasa in docker hub. We pull rasa with latest tag from docker hub this would ensure the platform gets latest version of rasa. Volumes are also bind-mounted to this container so that training data and model can be persisted on the volume.
this is the rasa actions server. Any connector written for rasa actions server can be deployed in actions server and can be used as documented in rasa. Custom actions needs to be placed in "vol_chatbot_data/rasa/server/actions" folder. If any new code is deployed for that to take effect rasa actions server container would need to be restarted.
Virtual Assistant has been built using docker containerization hence docker and docker-compose would be required to launch the application
- Docker version 18.09 onwards. (not tested on previous versions)
- Docker Compose version 1.24 onwards (not tested on previous versions)
- Linux like distributions (Tested on ubuntu)
Follow steps to install docker CE or enterprise as per your needs following below link and after that complete docker-compose installation by following link
use below commands to clone the github repo to local machine or server.
git clone https://github.com/navigateconsulting/va-grievance-redressal.git
cd va-grievance-redressal
docker-compose build
docker-compose up
Docker containers would be using ports 5055, 5005, 27017, 8080 for VA components. Ensure these ports are free.
The repo contains two docker-compose files. docker-compose.yml and docker-compose.devel.yml.
docker-compose.yml would start all platform components, including rasa server , rasa actions server and connectors this should be used to build the docker containers for server.
docker-compose build
docker-compose up -d
docker-compose.devel.yml would start only the ui application, api gateway and database. Serving infrastructure and connectors would not be started by this compose file. This file can be used to create a development environment for any contributions.
docker-compose -f docker-compose.devel.yml build
docker-compose -f docker-compose.devel.yml up -d
To check logs of any container use below command
docker-compose logs -f <container name>
All the training data generated by the application is stored on the local machine / server itself. For this we use bind-mount volumes which contains default config files, demo samples and database files.
vol_chatbot_data folder in the install base is a bind-mount volume and is mounted to the docker containers the location for this can be changed but ensure to modify docker-compose files to reflect the modified location.
vol_chatbot_data/database/db folder contains the mongodb database files. This folder can be backed up to restore application data in case of any issues.
Note : We do not recommend to change bind-mount volumes attached to docker containers as this might break the functionality. In future releases we would bring in flexibility to define data store locations etc.