WeTube, A movie recommendation platform powered by vector search and user comment analysis

This is a submission for the KendoReact Free Components Challenge. What I Built WeTube is a modern movie discovery platform that blends vector search technology with AI-powered recommendations. Built with Next.js and React, it offers personalized movie suggestions through an intuitive and accessible interface. Fully mobile-responsive, WeTube also analyzes and summarizes user comments on each movie — providing a sentiment score, key themes, highlights (likes), areas of improvement (dislikes), and actionable suggestions, all powered by AI. Demo links Demo link on vercel Github repo Screenshots KendoReact Experience I used free kendoUI components to achieve the following Skeleton component to show page placeholders Card for video cards UI Notification for showing toast while making comments Button to submit comments and make a search Input for performing search AppBar for the page header Textarea for writing comments Icon for meaningful UI Dialog to display comment analysis from AI Avatar for displaying user images AIm to Impress I utilized Google Gemini and MongoDB vector embeddings to implement vector search, delivering intelligent, AI-powered movie recommendations based on semantic similarity. Summarized user comments on each movie by providing an overall sentiment score, key themes, highlights (likes), areas for improvement (dislikes), and actionable suggestions based on user feedback.

Mar 24, 2025 - 08:03

WeTube, A movie recommendation platform powered by vector search and user comment analysis

This is a submission for the KendoReact Free Components Challenge.

What I Built

WeTube is a modern movie discovery platform that blends vector search technology with AI-powered recommendations. Built with Next.js and React, it offers personalized movie suggestions through an intuitive and accessible interface. Fully mobile-responsive, WeTube also analyzes and summarizes user comments on each movie — providing a sentiment score, key themes, highlights (likes), areas of improvement (dislikes), and actionable suggestions, all powered by AI.

Demo links

Demo link on vercel
Github repo

Screenshots

KendoReact Experience

I used free kendoUI components to achieve the following

Skeleton component to show page placeholders

Card for video cards UI

Notification for showing toast while making comments

Button to submit comments and make a search

Input for performing search

AppBar for the page header

Textarea for writing comments

Icon for meaningful UI

Dialog to display comment analysis from AI

Avatar for displaying user images

AIm to Impress

I utilized Google Gemini and MongoDB vector embeddings to implement vector search, delivering intelligent, AI-powered movie recommendations based on semantic similarity.
Summarized user comments on each movie by providing an overall sentiment score, key themes, highlights (likes), areas for improvement (dislikes), and actionable suggestions based on user feedback.