Product Recommendation Engine

This web application and soon-to-be browser extension empower users to make informed decisions about purchasing products. By simply providing a product link from Amazon or Flipkart, users gain insights and recommendations tailored to their needs.

LINK : https://product-recommendation-engine.vercel.app/

Features

• Product Analysis: Input a product link to receive detailed analysis and recommendations.
• Informative Insights: Gain access to insightful information aiding purchase decisions.
• Local Deployment: Easily run the project locally to explore and contribute.
• Contribution Opportunities: Open to contributions; top contributors will receive bounty rewards.

Local Setup

Frontend

1. Installation: Navigate to the frontend directory and install dependencies.

   npm install

2. Run Development Server: Execute the following command to start the frontend server.

   npm run dev

Backend (FastAPI)

1. Installation: Move to the server directory and install the required dependencies.

   cd server
   pip install -r requirements.txt

2. Run Backend Server: Launch the backend FastAPI server using Uvicorn.

   uvicorn main:app --host 0.0.0.0 --port 8000

Running Backend via Docker

1. Navigate: Move to the server directory.

   cd server

2. Docker Compose: Use the following command to set up and run the backend server using Docker.

   docker-compose up

Contributions

Contributions to enhance this project are encouraged and appreciated! The project welcomes contributors, and the top contributors will be rewarded with bounty rewards.

How to Contribute

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Commit your changes and push the branch to your fork.
4. Open a pull request detailing your changes.

Contributor Rewards

• Top contributors will receive bounty rewards.
• Contributions improving functionality, adding new features, or enhancing user experience are highly valued.

License

This project is licensed under TAGDA FOUNDATIONS.