SalesSage

SalesSage is a powerful platform for predicting sales data on a daily, weekly, or yearly basis. It provides insightful analytics to help companies make data-driven decisions. The platform offers three subscription plans: one free and two paid options, tailored to different business needs.

Table of Contents

• Features
• Screenshots
• Installation
• Usage
• API Documentation
• Contributing
• Roadmap
• Support
• Authors
• License

Features

• Predictive Analytics: Forecast sales data with high accuracy.
• Customizable Plans: Choose from free and paid subscription plans.
• User-Friendly Interface: Easy to navigate and use.
• Real-Time Insights: Get up-to-date sales predictions.
• Scalable Architecture: Easily scale the platform as your data grows.
• Secure Data Handling: Ensure your data is safe with our secure backend.

Screenshots

Here are some screenshots of the SalesSage platform: SalesSage landing page

Installation

Follow these steps to set up the project locally.

Prerequisites

• Docker
• Docker Compose

Clone the Repository

git clone https://github.com/pallav46/SalesSage.git
cd SalesSage

Setup and Run

Environment Variables

The project uses environment variables for configuration. Create a .env file in the backend directory with the following variables:

MONGODB_HOST=<your_mongodb_host>
MONGODB_PORT=<your_mongodb_port>
MONGODB_NAME=<your_database_name>
MONGODB_USER=<your_mongodb_username>
MONGODB_PASSWORD=<your_mongodb_password>

SECRET_KEY=<your_django_secret_key>
JWT_ALGORITHM=<your_jwt_algorithm>

EMAIL_PORT=<your_email_port>
EMAIL_HOST_USER=<your_email_host_user>
EMAIL_HOST_PASSWORD=<your_email_host_password>

RAZORPAY_KEY_ID=<your_razorpay_key_id>
RAZORPAY_KEY_SECRET=<your_razorpay_key_secret>
RAZORPAY_WEBHOOK_SECRET=<your_razorpay_webhook_secret>

Backend

1. Navigate to the backend directory:

   cd backend

2. Create and activate the virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Run the Django server:

   daphne SalesSage.asgi:application

Frontend

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

Docker

Alternatively, you can use Docker to run both the backend and frontend.

1. Build and start the containers:

   docker-compose up --build

2. Access the application at http://localhost:5173.

Usage

• Accessing the Application: Open your browser and go to http://localhost:5173.
• User Registration: Sign up for a free or paid plan.
• Sales Predictions: Add Sales report to view sales predictions.

API Documentation

Our API allows developers to integrate SalesSage's predictive analytics into their own applications. Below is a brief overview of the available endpoints.

Endpoints

• GET /api/predictions: Retrieve sales predictions.
• POST /api/sales-data: Submit sales data for analysis.

For detailed API documentation, please refer to the API Docs.

Contributing

We welcome contributions from the community. To get started:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.

Please make sure to update tests as appropriate.

Development Environment Setup

1. Clone the repository:

   git clone https://github.com/pallav46/SalesSage.git
   cd SalesSage

2. Backend:

   • Create and activate a virtual environment:

     python -m venv venv
     source venv/bin/activate  # On Windows use `venv\Scripts\activate`

   • Install the required packages:

     pip install -r requirements.txt

3. Frontend:

   • Navigate to the frontend directory and install dependencies:

     cd frontend
     npm install

Code Style

• Ensure your code adheres to the existing style conventions.
• Run linters before committing your code.

Roadmap

• Add more detailed sales analytics
• Implement user authentication and authorization
• Integrate more data sources for comprehensive predictions
• Enhance the UI/UX for better user experience
• Mobile app version for on-the-go access

Support

For support, please open an issue in the repository or contact us at support@SalesSage.com.

Authors

• Ishaan - Backend - ishaan19d
• Ubaid - AI & ML - ubaid2751
• Pallav - Frontend - pallav46

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License. See the LICENSE file for details.