AI-Driven Task Manager

A fully AI-driven task management application where users give instructions in natural language, and AI automatically detects the most eligible person for tasks and assigns relevant tags.

Features

• Natural language task creation
• AI-powered task analysis using OpenAI GPT-4
• Automatic assignment to team members based on skills and availability
• Auto-tagging of tasks
• Priority detection
• Real-time chat interface
• Task dashboard

Tech Stack

Backend

• Node.js + Express
• MongoDB (Mongoose)
• OpenAI API (GPT-4)

Frontend

• Next.js 14
• React

Project Structure

Task manager/
├── backend/
│   ├── config/
│   │   └── database.js
│   ├── models/
│   │   ├── Task.js
│   │   └── TeamMember.js
│   ├── routes/
│   │   ├── tasks.js
│   │   ├── team.js
│   │   └── chat.js
│   ├── services/
│   │   └── aiService.js
│   ├── server.js
│   ├── package.json
│   └── .env.example
│
└── frontend/
    ├── app/
    │   ├── page.js
    │   ├── layout.js
    │   └── globals.css
    ├── components/
    │   ├── ChatInterface.js
    │   └── TaskList.js
    ├── package.json
    └── .env.local.example

Setup Instructions

Prerequisites

• Node.js (v18 or higher)
• MongoDB (local or Atlas)
• OpenAI API key

Backend Setup

1. Navigate to the backend folder:

cd backend

2. Install dependencies:

npm install

3. Create a .env file from the example:

cp .env.example .env

4. Edit .env and add your credentials:

MONGODB_URI=mongodb://localhost:27017/task-manager
OPENAI_API_KEY=your_openai_api_key_here
PORT=5000

5. Start the backend server:

npm run dev

The backend will run on http://localhost:5000

Frontend Setup

1. Navigate to the frontend folder:

cd frontend

2. Install dependencies:

npm install

3. Create a .env.local file from the example:

cp .env.local.example .env.local

4. Edit .env.local:

NEXT_PUBLIC_API_URL=http://localhost:5000/api

5. Start the frontend:

npm run dev

The frontend will run on http://localhost:3000

Adding Team Members

Before creating tasks, you need to add team members. Use an API client like Postman or curl:

curl -X POST http://localhost:5000/api/team \
  -H "Content-Type: application/json" \
  -d '{
    "name": "John Doe",
    "skills": ["frontend", "react", "javascript"],
    "availability": "available"
  }'

Add multiple team members:

curl -X POST http://localhost:5000/api/team \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Jane Smith",
    "skills": ["backend", "nodejs", "database"],
    "availability": "available"
  }'

curl -X POST http://localhost:5000/api/team \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Mike Johnson",
    "skills": ["devops", "docker", "kubernetes"],
    "availability": "available"
  }'

Usage

1. Open the frontend at http://localhost:3000
2. Use the chat interface to create tasks in natural language

Example Commands

• "Create a new task to fix the login bug with high priority"
• "Add a task to implement user authentication, assign it to someone with backend skills"
• "Create a task for updating the homepage design, priority medium"
• "Add a high priority task to deploy the application to production"

The AI will automatically:

• Extract the task title and description
• Detect the priority level
• Assign the most suitable team member based on skills
• Add relevant tags

API Endpoints

Tasks

• POST /api/tasks/create - Create a new task with AI analysis
• GET /api/tasks - Get all tasks
• PUT /api/tasks/:id - Update a task
• DELETE /api/tasks/:id - Delete a task

Team

• POST /api/team - Add a team member
• GET /api/team - Get all team members
• PUT /api/team/:id - Update a team member
• DELETE /api/team/:id - Delete a team member

Chat

• POST /api/chat - General chat with AI assistant

Database Schema

Task

{
  title: String,
  description: String,
  priority: 'low' | 'medium' | 'high',
  assignedTo: String,
  tags: [String],
  status: 'pending' | 'in-progress' | 'completed',
  createdAt: Date,
  dueDate: Date
}

TeamMember

{
  name: String,
  skills: [String],
  currentWorkload: Number,
  availability: 'available' | 'busy' | 'unavailable'
}

Environment Variables

Backend (.env)

• MONGODB_URI - MongoDB connection string
• OPENAI_API_KEY - OpenAI API key
• PORT - Server port (default: 5000)

Frontend (.env.local)

• NEXT_PUBLIC_API_URL - Backend API URL

Future Enhancements

• User authentication
• Task status updates via chat
• Task reassignment
• Due date reminders
• Task analytics and reporting
• Team member performance tracking
• Integration with calendar services
• Email notifications

License

MIT