Customer Query Resolution application by Mohit Pathak

Demo video can be viewed Here

Login details:

User mode: 208@user.com, 218@user.com, 444@user.com, 676@user.com, 779@user.com, 1092@user.com, 1155@user.com, 1241@user.com, 1245@user.com, 1354@user.com, 1481@user.com, 2035@user.com, 2126@user.com, 2517@user.com, 2780@user.com, 2788@user.com, 2884@user.com, 2926@user.com, 2983@user.com, 3056@user.com, 3091@user.com, 3112@user.com, 3170@user.com, 3643@user.com, 3701@user.com, 3725@user.com, 3775@user.com, 3897@user.com, 3900@user.com, 4178@user.com, 4373@user.com, 4442@user.com, 4481@user.com, 4522@user.com, 4708@user.com, 5000@user.com, 5297@user.com, 5480@user.com, 5696@user.com, 5724@user.com, 6054@user.com, 6326@user.com, 6515@user.com, 6884@user.com, 7140@user.com, 7457@user.com, 7725@user.com, 7812@user.com, 7837@user.com, 7944@user.com, 8014@user.com, 8101@user.com, 8125@user.com, 8392@user.com, 8647@user.com

Agent mode: 1@agent.com, 2@agent.com, 3@agent.com, 4@agent.com, 5@agent.com, 6@agent.com, 7@agent.com, 8@agent.com, 9@agent.com, 10@agent.com, 11@agent.com, 12@agent.com, 13@agent.com, 14@agent.com, 15@agent.com, 16@agent.com, 17@agent.com, 18@agent.com, 19@agent.com, 20@agent.com, 21@agent.com, 22@agent.com, 23@agent.com, 24@agent.com, 25@agent.com, 26@agent.com, 27@agent.com, 28@agent.com, 29@agent.com, 30@agent.com

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Features implemented

• Agent Interface and Customer Interface
• Intuitive UI for user and customer agent
• Feature for user to add new queries and a way to prioritise these new queries; User can select a total of 16 different cases (4 issues x 4 subissues) comprising different issues having different prioritties
• Way for customer agents to keep any eye on the incoming messages and prioritising urgent issues
  • The chats having highest priority and are most recent displayed on the top
  • Implemented pagination so that only a handful of selected chats are fetched at a time from the server
  • The customer agent can select a chat request to resolve, After selection the chat is removed from the "new chats request" table thereby avoiding multiple agents to work on same chat simultaneously
• Realtime chat between user and customer agent. Even when either side is offline the messages are not lost and stored in DB which are then fetched when a user clicks to open the chat
• Also implemented the online status of users
• The agent or user can mark the chat as resolved. Once resolved, The chat will be read-only. The user and agent both can view the resolved chats by going to the resolved section
• Implemented New chat request notification for agents and new messages notifications
• Populated the DB with the chats provided in the CSV files (Gives some extra attributes to rows to fit the data model)
• Dockerized the application (consisting of 5 containers viz Frontend(ReactJS), Backend: Stateless Application server(NodeJS), Backend: Stateful websocket server, Database: MySQL(For relational data), MongoDB(For storing the chats)). Running the application requires just one command docker compose up --build.
• Added notification and loader to improve the UX

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Architecture

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Setting up the application on local machine

Requirements

• Git and docker

Steps

1. Clone the GitHub repo on your local machine

git clone https://github.com/aystic/CustomerQueryResolution.git

2. Navigate inside the cloned repo

cd CustomerQueryResolution

3. Run the docker compose command

docker compose -f ./docker-compose.dev.yaml up --build

4. Run the following command for mongoDB chat migration

docker container exec -it customerqueryresolution-db_mongodb-1 mongoimport --type=csv -d BranchBackend -c chats  --columnsHaveTypes --fields 'chatID.int64(),userID.int64(),agentID.int64(),type.string(),sender.string(),timestamp.string(),message.string()' --file=ChatsMongo.csv

If step 4 fails then check the name of the docker container for the mongoDB database using

docker container ls -a

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