• Edward Savin
  • Software Engineer


Full Stack Developer:
Edward Savin

Moodvie is an innovative movie recommendation application that provides suggestions based on a user's music taste and mood.

The project stands out because it leverages Spotify's data, harnesses the power of AI through OpenAI's gpt-3.5-turbo API, and utilizes TMDB's vast movie database.

It uses an interesting method for determining movie recommendations: by analyzing the user's recently listened to songs on Spotify, it determines their mood and subsequently suggests relevant movies.

Moodvie's unique approach to movie discovery is powered by a robust tech stack called T3, it includes Next.js, TypeScript, TailwindCSS, tRPC, and Prisma, offering a seamless and personalized user experience.

One of the technical challenges faced during the application's development was implementing the draggable songs image carousel.

The final implementation was able to display an attractive, smoothly dragging image carousel for songs, greatly enhancing the user experience.

Recommendation Showcase
Recommendation Showcase

Given the user's Spotify credentials, Moodvie fetches the user's recently listened to songs, analyzes them using OpenAI, and recommends movies based on the processed mood.

Movie Details
Movie Details

Smoothly fetching and displaying key movie details such as release year, stars, and descriptions by integrating TMDB's extensive movie database.

Wow, what a cool project!

I will definitely be using this to find new movies to watch.

History Showcase
History Showcase

Keeping track of users' recommendations is a great quality of life and provides a better, personalized user experience.

The user's preference data opens a gateway for future development and data analysis.

Mobile View
A sleek mobile experience.

Moodvie's mobile design maintains its unique style elements, animations, and touch-responsive carousel for a consistent, engaging user experience across devices.

Moodvie actively expands the boundary of traditional movie-recommendation applications.

By clever use and integration of various APIs and technologies, it transforms user behaviors into valuable input for generating personalized movie recommendations.

The ability of the Moodvie app to store extensive data for each user qualitatively extends opportunities for personalization and future application growth.

Found this project interesting? Want to chat about it? Let's connect!

Crafting comprehensive digital web solutions with an emphasis on dynamic, responsive, and interactive content.

Committed to delivering high-quality solutions, balancing front-end aesthetics with back-end functionality.

Delivering meticulously crafted front-end user experiences, while maintaining a strong understanding of backend processes, optimization, and performance.

Open to new opportunities —

Remotely or in Cluj-Napoca, Romania.

Software Engineer —

Frontend, Backend, Fullstack.

Languages —
  • TypeScript
  • JavaScript
  • Go
  • C#
  • Python
Frontend —
  • React
  • Next.js
  • CSS
  • Tailwind CSS
Backend —
  • Node.js
  • .NET
  • Prisma
  • SQL
  • tRPC
  • REST
  • AI Integration
OS and Tools —
  • Linux
  • Windows
  • Neovim