app.py

from flask import Flask, request, jsonify, render_template
import pickle
import pandas as pd
import requests

app = Flask(__name__)

# Load pre-trained movie recommendation models  
# `movies_list.pkl` contains movie data (titles and IDs)  
# `similarity.pkl` is a precomputed similarity matrix for recommendations  
movies = pickle.load(open("movies_list.pkl", 'rb'))
similarity = pickle.load(open("similarity.pkl", 'rb'))

# TMDB API Key (for fetching movie posters and ratings)  
API_KEY = "c7ec19ffdd3279641fb606d19ceb9bb1"


def fetch_movie_details(movie_id):
    """
    Fetch movie details (poster URL and rating) from TMDB using the given movie ID.

    :param movie_id: TMDB movie ID
    :return: Dictionary containing poster URL and rating
    """
    url = f"https://api.themoviedb.org/3/movie/{movie_id}?api_key={API_KEY}&language=en-US"
    data = requests.get(url).json()

    poster_path = data.get('poster_path', '')  # Extract poster path (if available)
    rating = data.get('vote_average', 'N/A')  # Extract rating, default to 'N/A' if missing

    return {
        'poster': f"https://image.tmdb.org/t/p/w500/{poster_path}" if poster_path else "",  # Full poster URL
        'rating': rating
    }


@app.route('/')
def home():
    """
    Render the homepage (index.html).

    :return: Rendered HTML template
    """
    return render_template('index.html')


@app.route('/suggest', methods=['GET'])
def suggest():
    """
    Suggest movie names based on user input.

    :return: JSON response containing up to 10 suggested movie titles
    """
    query = request.args.get('query', '').strip().lower()  # Get user query, strip whitespace, and convert to lowercase

    if not query:
        return jsonify({'suggestions': []})  # Return an empty list if query is empty

    # Filter movies whose titles start with the query string (case-insensitive search)
    suggestions = movies[movies['title'].str.lower().str.startswith(query)]['title'].tolist()

    return jsonify({'suggestions': suggestions[:10]})  # Return up to 10 suggestions


@app.route('/recommend', methods=['POST'])
def recommend():
    """
    Recommend similar movies based on a given movie title.

    :return: JSON response containing recommended movie titles, posters, and ratings
    """
    data = request.json  # Get JSON data from request
    movie_name = data.get('movie', '').strip()  # Extract movie name and strip whitespace

    if not movie_name:
        return jsonify({'message': 'Movie name is required'}), 400  # Return error if no movie name provided

    try:
        # Find index of the movie in the dataset  
        index = movies[movies['title'] == movie_name].index[0]

        # Get similarity scores for the given movie and sort them in descending order  
        distances = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda x: x[1])

        recommend_movies = []  # List to store recommended movie titles  
        recommend_posters = []  # List to store corresponding movie poster URLs  
        recommend_ratings = []  # List to store corresponding movie ratings  

        # Fetch details for the top 6 recommended movies (excluding the input movie)  
        for i in distances[1:7]:  
            movie_id = movies.iloc[i[0]].id  # Get movie ID  
            movie_details = fetch_movie_details(movie_id)  # Fetch poster and rating  

            recommend_movies.append(movies.iloc[i[0]].title)  # Append movie title  
            recommend_posters.append(movie_details['poster'])  # Append poster URL  
            recommend_ratings.append(movie_details['rating'])  # Append rating  

        return jsonify({
            'movies': recommend_movies,
            'posters': recommend_posters,
            'ratings': recommend_ratings
        })

    except IndexError:
        return jsonify({'message': 'Movie not found'}), 404  # Return error if movie is not found in dataset


if __name__ == '__main__':
    print(app.url_map)  # Print all registered routes for debugging purposes  
    app.run(debug=True)  # Run the Flask app with debugging enabled