VectorCinema

Semantic movie recommendations — describe a mood, get films. Sentence-BERT embeddings in Astra DB, 94% precision@10.

TYPE
Semantic search
ROLE
AI developer intern
BUILT
Jul 2025
STATUS
Live demo · Rabbitt AI
VISIT
vectorcinema.vercel.app
SOURCE
GitHub
TECH STACK
Next.jsTypeScriptTailwind CSSPythonSentence-BERTAstra DB
VectorCinema screenshot
01

Search by mood, not title

Instead of keyword matching, VectorCinema embeds every film's plot and themes with Sentence-BERT and stores them in Astra DB, so you can type 'sci-fi films in space' and get meaningfully related results.

02

Recommendations you can see

Every film shows its nearest neighbours with similarity scores, calculated live from the vector index.

03

Results

94% precision@10Natural-language searchLive similarity scores
FAQ

Questions people ask

Why vectors?

Embeddings capture meaning, so two films with no shared keywords can still be found as similar.

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