profile

Vivek Chaurasiya 👋

Software Engineer at Paytm with 1 year of industry experience building scalable full-stack web applications. Strong in React.js, Redux Toolkit, TailwindCSS, JavaScript, HTML, CSS, with hands-on backend experience in Node.js, Express.js, MongoDB, and JWT authentication. Skilled in REST API development, performance optimization and delivering production-ready features in Agile environments.

Resume
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Client For:

Netflix-Gpt

Services:

Full Stack Development

Website

Overview

Netflix-GPT is a feature-rich, AI-powered web application that blends Netflix's browsing experience with the intelligence of Gemini AI. Users can search for movies using natural language queries, receiving personalized movie recommendations in real-time. The app is built using React, TailwindCSS, Firebase Authentication, TMDB API, and Gemini AI API.

Features: Secure user authentication, AI-powered movie recommendations, dynamic movie browsing, multi-language support, responsive design, optimized API handling, and real-time UX enhancements.

Technology: Developed using ReactJS, TailwindCSS, Firebase Authentication, TMDB API, Gemini AI API, Redux Toolkit, and deployed on Vercel for fast, reliable performance.

Challenges

Building Netflix-GPT required addressing several design, performance, and integration challenges to ensure a seamless, real-time user experience. Here are some key challenges and solutions:

AI Integration:
  • Challenge: Seamlessly integrating Gemini AI API for real-time, context-aware movie recommendations.
  • Solution: Crafted dynamic prompt structures and optimized API calls using memoization, ensuring accurate recommendations while minimizing API overuse.
State Management:
  • Challenge: Managing complex application state for user data, movie details, and AI-generated results.
  • Solution: Utilized Redux Toolkit to handle global state efficiently, ensuring scalability and smoother data flow.
Responsive Design & UX:
  • Challenge: Delivering a clean, fully responsive interface accessible on all devices.
  • Solution: Implemented TailwindCSS for responsive layouts, added toast notifications, loaders, and multi-language support to enhance usability.
Performance Optimization:
  • Challenge: Reducing redundant API calls and preventing unnecessary re-renders to optimize app speed.
  • Solution: Applied memoization and lazy-loading strategies, improving load time by 30% and ensuring a smooth browsing experience.

Results/Conclusion:

Netflix-GPT successfully delivers an engaging, AI-enhanced movie recommendation platform with a smooth user experience. It has been well-received for its real-time recommendations, intuitive interface, and responsive performance. Future improvements include expanding genre filters and adding watchlist functionality.

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