🎯 Smart Task Planner

An intelligent task planning system that leverages Google's Gemini AI to break down high-level goals into a structured, actionable plan with dependencies and timelines.

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📋 Table of Contents

• About The Project
• ✨ Key Features
• 🤖 How It Works
• 🛠️ Tech Stack
• 🚀 Deployment
• ▶️ Getting Started
• 🔌 API Endpoints
• 📂 Project Structure

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📖 About The Project

The Smart Task Planner was built to bridge the gap between ambitious goals and concrete actions. Often, the hardest part of achieving a goal is knowing where to start. This application solves that problem by taking a simple goal description—like "Launch a new product in 2 weeks"—and using AI-powered reasoning to generate a complete project plan.

The core of the project is a FastAPI backend that communicates with the Google Gemini API to perform logical decomposition of the user's goal. The generated plan, including tasks, timelines, and their inter-dependencies, is then stored in a MongoDB database and beautifully rendered by a React frontend.

This project fulfills the following objectives:

• Generation of actionable task breakdowns from a simple text input.
• Logical estimation of timelines and identification of task dependencies.
• A clean, user-friendly interface to submit goals and visualize plans.
• A well-designed RESTful API to handle all logic.

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✨ Key Features

• AI-Powered Task Decomposition: Leverages Google Gemini for sophisticated reasoning to create comprehensive task lists.
• Logical Timeline Generation: The AI suggests realistic deadlines and durations for each task.
• Dependency Mapping: Automatically identifies which tasks need to be completed before others can begin.
• Interactive Web Interface: A modern frontend built with React and Vite to submit goals and view plans in a clean, organized manner.
• Persistent Storage: Securely stores all generated plans in a MongoDB Atlas database for future reference.
• RESTful API: A robust backend built with FastAPI provides clear and efficient endpoints for managing plans.
• Data Export: Functionality to export a complete task plan to a CSV file.

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🤖 How It Works

The application follows a simple yet powerful workflow:

1. Goal Submission: The user enters a high-level goal into the React frontend.
2. API Request: The frontend sends the goal to the FastAPI backend.
3. AI Reasoning: The backend constructs a detailed prompt for the Google Gemini API, instructing it to break down the goal. A sample prompt looks like this:

   "Break down this goal: '{user_goal}' into actionable tasks with suggested deadlines and dependencies. Provide the output as a structured list."

4. Plan Generation: Gemini processes the request and returns a structured breakdown of tasks.
5. Database Storage: The backend parses the AI's response, validates the data, and stores the complete plan in the MongoDB database.
6. Frontend Display: The structured plan is sent back to the React client, where it is displayed to the user in an intuitive format.

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🛠️ Tech Stack

This project is built using a modern and scalable technology stack.

Category	Technology
Backend	Python, FastAPI
Frontend	React, Vite, Axios
Database	MongoDB Atlas
AI Model	Google Gemini

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🚀 Deployment

This project is fully deployed, with the frontend and backend hosted on separate, scalable platforms.

Service	Platform	Status
Frontend	Vercel The React application is deployed on Vercel, leveraging its global CDN for optimal performance.
Backend	Render The FastAPI server is hosted on Render, running as a web service connected to MongoDB Atlas.

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▶️ Getting Started

To get a local copy up and running, follow these simple steps.

Prerequisites

Make sure you have the following installed:

• Python 3.11+
• Node.js v18+ and npm
• A free MongoDB Atlas account and your connection string.
• A free Google Gemini API Key.

Installation & Setup

1. Clone the repository:

   git clone [https://github.com/kandarpchandra/smart-task-planner.git](https://github.com/kandarpchandra/smart-task-planner.git)
   cd smart-task-planner

2. Backend Setup:

   # Navigate to the backend directory
   cd backend
   
   # Create and activate a virtual environment
   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate
   
   # Install dependencies
   pip install -r requirements.txt
   
   # Create a .env file and add your credentials
   # (You can copy .env.example to .env)
   echo "GEMINI_API_KEY='YOUR_GEMINI_API_KEY'" > .env
   echo "MONGODB_URL='YOUR_MONGODB_CONNECTION_STRING'" >> .env
   
   # Run the server
   uvicorn main:app --reload

   Your backend API will be available at http://localhost:8000.

3. Frontend Setup:

   # Navigate to the frontend directory from the root
   cd frontend
   
   # Install dependencies
   npm install
   
   # Run the development server
   npm run dev

   Your frontend will be available at http://localhost:5173.

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🔌 API Endpoints

The backend provides the following RESTful API endpoints:

Method	Endpoint	Description
POST	/api/plan	Create a new task plan from a goal.
GET	/api/plans	Retrieve all existing plans.
GET	/api/plan/{id}	Get a specific plan by its ID.
PATCH	/api/task/{plan_id}/{task_number}/status	Update the status of a single task.
GET	/api/plan/{id}/progress	Get the completion progress of a plan.
GET	/api/plan/{id}/export/csv	Export a plan as a CSV file.
DELETE	/api/plan/{id}	Delete a plan by its ID.

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📂 Project Structure

The repository is organized with a clear separation between the frontend and backend applications.

smart-task-planner/
├── backend/
│   ├── main.py           # FastAPI application logic and API endpoints
│   ├── models.py         # Pydantic data models for validation
│   └── requirements.txt  # Python package dependencies
├── frontend/
│   ├── src/              # React application source code
│   └── package.json      # Node.js package dependencies
├── demo/
│   └── demo.gif          # Animated demo for the README
├── .gitignore            # Specifies files for Git to ignore
├── LICENSE               # Project's MIT license
└── README.md             # You are here!