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movie-browser's Introduction

The Movie Browser

Link to the website: themoviebrowser.com

Created by: Chaitanya Vootla visit my site for more projects info and contact details.

image

TMB is a movie and TV show discovery platform that helps you find the right content to watch. With features like ratings, watch links, watchlist, discovery and AI recommendations TMB is the only platform you need to find your next watch.

  • Feel like you've watched everything? TMB begs to differ with its powerful discovery feature.
  • Not sure if a movie is worth watching? TMB has ratings from multiple sources.
  • Not sure when the next episodes of all your favorite TV shows air? TMB has you covered.
  • Want to quickly jump to your favorite streaming service to continue watching? TMB has watch links for that.
  • Want to watch every last zombie movie? TMB has a filter for that.
  • Want to find movies that are war comedies that are available on amazon prime? OK, - TMB doesnt have a filter for that, but you can create your own check this out, seems like you're looking for Tropic Thunder

Tech stack:

  • TMDB API - All the api backend for movies, series and custom filters
  • Nuxt
  • AWS Lambda for ratings and watch links using puppeteer
  • MongoDB on docker
  • ChromaDB for AI recommendations using OpenAI's embeddings

Setup steps:

Add a .env file to the project root from the template shown in template.env file

npm i
npm run dev

For vector database setup

Go to VectorDB folder, copy .env from root you created before to this place and add an additional entry OPENAI_API_KEY with your openai api key for creating embeddings, dont worry the new OpenAI embeddings cost is super low and will barely cost a couple of cents for 20k movies.

Create a python venv and install the requirements.txt file, then run this to create the embeddings in the chromaDB

python3 openai/create.py

Then run this for starting the server

python3 openai/server.py

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