import streamlit as st
import numpy as np
import pandas as pd

final_movie_df = pd.read_csv('movie_data.csv') 

similarity = np.load("similarity.npy")

def recomendMovie(movie_title) :
    matching_indices = final_movie_df[final_movie_df['title'].str.contains(movie_title, case=False, na=False)].index
    if not matching_indices.empty:
        distance = similarity[matching_indices[0]]
        
        movie_list = sorted(list(enumerate(distance)), reverse=True, key = lambda x: x[1])[1:6]
        output_list = []
        for movie in movie_list:
            output_list.append(final_movie_df.iloc[movie[0]].title)
        return pd.DataFrame({
            'movie_name' : output_list
        })
    else:
        return "This movie isn't present in the dataset."
           
st.title('Get recommendation related to your favourite movies 🍿 🎬')
name = st.text_input("Enter Movie name: ")
if name != "":
    output = recomendMovie(name)
    st.dataframe(output, use_container_width=True)