IRMrec

A web application to make movie recommendations, gather user feedback, and create a test collection

Getting Started

To set up IRMrec locally, follow these steps:

Clone this repository:

$ git clone https://github.com/maancham/IRMrec.git

Create a Python virtual environment and activate it:
```
$ python -m venv env
$ source env/bin/activate
```
Install dependencies from requirements file:
```
$ pip install -r requirements.txt
```
Then simply apply the migrations:
```
$ python manage.py migrate
```

You will need two files to populate the database, I have excluded them from the repository due to privacy reasons. The first file is called movies.csv which is as follows:

Column	Description
movieId	Unique identifier for each movie
imdbId	IMDb identifier for each movie
tmdbId	TMDB identifier for each movie
title	Title of the movie
genres	Genres associated with the movie (comma-separated string)
year	Year of release of the movie
overview	Brief overview or synopsis of the movie
img_path	TMDB link to the movie's image
runtime	Duration of the movie in minutes
cast	Actors and actresses in the movie (comma-separated string)
directors	Directors of the movie (comma-separated string)
languages	Languages spoken in the movie (comma-separated string)
map	MAP rating of the movie (e.g., PG-13, R, etc.)

and the second one is users.json, which is a list of json objects. Each object has the following structure:

first_name: First name of the user associated with the dataset.
last_name: Last name of the user associated with the dataset.
dataset_id: Unique identifier from the training dataset.
pass: Password or access key to log into the webapp.
recs: An array of recommended movie IDs for the user.

Populate the database with movies and users:

$ python manage.py load_movies --path movies.csv
$ python manage.py load_users --path users.json

You can now start the development server:
```
$ python manage.py runserver
```