I'm excited to share a project I've been passionately working on in my spare time: AI Movie Finder (https://www.aimoviefinder.com).

The idea was born out of a simple, yet frequent, frustration: having a movie on the tip of my tongue but being unable to recall the title. All I could remember were fragments – a specific scene, a snippet of dialogue, the general plot, or even just the mood it evoked. Traditional search engines often fell short with these kinds of abstract queries.

So, I decided to build a solution. AI Movie Finder uses a natural language processing model to understand these descriptive and sometimes vague queries. You can type in things like:

"that movie where a guy keeps reliving the same day"

"a sci-fi film with a blue alien opera singer"

"a feel-good movie about a band in the 80s"

The goal is to make movie discovery more intuitive and human-like. Instead of just searching by actors or exact titles, you can search by memory and feeling.

The backend is built with Python and utilizes a fine-tuned sentence transformer model to create vector embeddings for a large movie database. The frontend is a clean and simple interface built with vanilla JavaScript to keep it fast and accessible.

This is still very much a work in progress, and the database is continuously growing. I'm actively working on improving the model's accuracy and expanding the search capabilities.

I would love to get your feedback. Please give it a try and let me know what you think. I'm particularly interested in:

How well does it work for your queries?

Are there any features you think would be a great addition?

Any suggestions on how to improve the model or the user experience?

Thanks for checking it out! I'll be here to answer any questions.