Overview of My Submission

STACKER

Is a software that helps businesses to easily track communications between customer service agents and clients.It uses REDIS to store data(issues submitted by clients). It is integrated with a chat developed using socketIO. This Project comes with apython(Flask) API and a Vue,Vite Application.The user interface was built using tailwindCss.

Basic Functionality:

1. As a client, you create an account or register.
2. Access the dashboard
3. Create an Issue(the issue will be added to a queue)
4. On the customer service agent side.
5. Login to the system.
6. You will see a dashboard with a list of Issues to be attended.
7. Those that are already being attended by other agents, will be indicated in red.
8. Attend an issue with a green background.
9. To attend an issue, click go to chat. It will redirect you to a chat where you can communicate with a client.
10. The client will be notified when the issue is being attended.
11. If an issue has been completed, it is CLOSED.
12. If it is under investigation, it is ARCHIVED.
13. Otherwise, it is left OPEN / in PROGRESS.
14. On the dashboard, the client and the customer service agent will be able to see their issues -open,closed and archived.

Why this?:

We want to provide a simple way for customer representative agents to handle multiple clients at the same time seemlessly, using a chat and a queuing system.

Where we used redis.

((as a primary database using RedisJson Module through Redis OM Python))

• Storage of chat information - messages
• Storage of Issues
• Storage of user data

Submission Category:

Wacky Wildcards

Overview video (Optional)

Link to Code

Languages Used:

Javascript(Vue,js) html Tailwindcss Python

Screen screenshots

Landing Page

Dashboard Page

Chat Page

How it works

How the data is stored:

Data is stored using RedisJSON module in DB and RedisOM Python as a client library

• Store (Add): model_instance = ModelName(key1=value1, key2=value2, ..., keyN=valueN) model_instance.save()

Code Example:Database Schema

Issues

class Issue(EmbeddedJsonModel, JsonModel): subject: Optional[Optional[str]] = Field(index=True) description: Optional[str] = Field(index=True) issue_status: Optional[str] = Field(index=True) sender: Optional[str] = Field(index=True) created_at: Optional[str] = Field(index=True) record_status: Optional[str] = Field(index=True) 

Messages

class Message(JsonModel): issue: Optional[Optional[str]] = Field(index=True) sender: Optional[str] = Field(index=True) sender_data: User issue_data: Issue message_body: Optional[str] = Field(index=True) 

User

class User(EmbeddedJsonModel, JsonModel): first_name: Optional[str] = Field(index=True) last_name: Optional[str] = Field(index=True) role: Optional[str] = Field(index=True) created_at: Optional[str] = Field(index=True) record_status: Optional[str] = Field(index=True) 

How the data is accessed:

• Get:
  model_instance = ModelName.find((ModelName.field1=="value1")&(ModelName.field2=="value2")) - to filterby field1's and field2's values.

• Update:
  model_instance = ModelName().get(model_instance_id)
model_instance.field1 = new_value1
model_instance.field2 = new_value2
model_instance.fieldN = new_valueN
model_instance.save()

Code Example: How to access/get user data

def get_users(): try: users = User.find(User.record_status=="ALIVE").all() users_list = [] for user in users: user_dict = {} for x in user: user_dict[x[0]] = x[1] users_list.append(user_dict) return jsonify({ "status_code": "200", "status": "success", "message": "users_retrieved_ok", "data": users_list }) except: traceback.print_exc() return jsonify({ "status_code": "500", "status": "error", "message": "failed_to_retrieve_users", "data": [], }) 

How to run it locally?

Backend

• Prerequisites: Python 3.8.2
• Local Installation Steps:

- clone repo - access folder titled "CRM BACKEND" - add ".env" file in the root directory of the project and add the line: -> "REDIS_OM_URL=[URL_TO_REDIS_CLOUD]" - create and activate virtual environment in the root directory using the command (on Windows 10 cmd): -> "python -m venv [ENVIRONMENT_NAME]" -> "[ENVIRONMENT_NAME]\scripts\activate" -install project packages in the active environment using the command (on Windows 10 cmd): -> "pip install -r requirements.txt" -run flask API using the command (on Windows 10 cmd): -> "flask run" -it should give an output like: * Debug mode: on * Running on localhost:[PORT_NUMBER] * Restarting with stat * Debugger is active! * Debugger PIN: [DEBUGGER_PIN] 

Frontend

• Prerequisites: Node.js >= 14
• Local Installation Steps:

- clone repo - access folder titled "CRM FRONTEND" - run "YARN INSTALL" - In the project folder, there is a file "config.js".change url to your backends server url. - run "YARN DEV" to run the project - To expose host on a network run with --host flag eg:"YARN DEV --host" 

Prerequisites

Node.js >= 14 Python 3.8.2 Redis Cloud Account

Additional Resources / Info

Architecture

Model

Collaborators

Role: Python Developer
On this Project, he developed a python Api using flask

Valentine Sean ChanengetaFollow

Software Developer (Python, Flask, Java, Spring Boot, MySQL, MongoDB, Git, Docker, Redis)

Me
Role: Front End Developer
On this project, i developed a vue.js application

Deployment

We recommend running this project Locally following the steps above

License

APACHE