Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import pandas as pd | |
| import requests | |
| import pickle | |
| # Load the processed data and similarity matrix | |
| with open('movie_data.pkl', 'rb') as file: | |
| movies, cosine_sim = pickle.load(file) | |
| # Function to get movie recommendations | |
| def get_recommendations(title, cosine_sim=cosine_sim): | |
| idx = movies[movies['title'] == title].index[0] | |
| sim_scores = list(enumerate(cosine_sim[idx])) | |
| sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True) | |
| sim_scores = sim_scores[1:11] # Get top 10 similar movies | |
| movie_indices = [i[0] for i in sim_scores] | |
| return movies[['title', 'movie_id']].iloc[movie_indices] | |
| # Fetch movie poster and additional details using append_to_response | |
| def fetch_movie_data(movie_id): | |
| api_key = "5c1c27e14a6a61a873db79d82528056f" | |
| url = f'https://api.themoviedb.org/3/movie/{movie_id}?api_key={api_key}&append_to_response=videos,images' | |
| try: | |
| response = requests.get(url) | |
| response.raise_for_status() | |
| data = response.json() | |
| # Handle poster path | |
| poster_path = data.get('poster_path') | |
| poster_url = f"https://image.tmdb.org/t/p/w500{poster_path}" if poster_path else \ | |
| "https://via.placeholder.com/500x750?text=No+Image+Available" | |
| # Handle trailer safely | |
| videos = data.get('videos', {}).get('results', []) | |
| trailer = next((v for v in videos if v.get('type') == 'Trailer'), None) | |
| # Handle backdrop safely | |
| backdrops = data.get('images', {}).get('backdrops', []) | |
| backdrop_path = backdrops[0].get('file_path') if backdrops else '' | |
| # Handle overview | |
| overview = data.get('overview', 'No description available')[:100] + "..." | |
| return { | |
| 'poster': poster_url, | |
| 'trailer_key': trailer.get('key') if trailer else None, | |
| 'backdrop': backdrop_path, | |
| 'overview': overview | |
| } | |
| except requests.exceptions.RequestException as e: | |
| st.error(f"API Error: {str(e)}") | |
| return { | |
| 'poster': "https://via.placeholder.com/500x750?text=No+Image+Available", | |
| 'trailer_key': None, | |
| 'backdrop': '', | |
| 'overview': 'No description available' | |
| } | |
| # Streamlit UI | |
| st.title("Movie Recommendation System") | |
| selected_movie = st.selectbox("Select a movie:", movies['title'].values) | |
| if st.button('Recommend'): | |
| recommendations = get_recommendations(selected_movie) | |
| st.write("Top 10 recommended movies:") | |
| # Create a 2x5 grid layout | |
| for i in range(0, 10, 5): # Loop over rows (2 rows, 5 movies each) | |
| cols = st.columns(5) # Create 5 columns for each row | |
| for col, j in zip(cols, range(i, i+5)): | |
| if j < len(recommendations): | |
| movie_title = recommendations.iloc[j]['title'] | |
| movie_id = recommendations.iloc[j]['movie_id'] | |
| movie_data = fetch_movie_data(movie_id) | |
| with col: | |
| st.image(movie_data['poster'], width=130, caption=movie_title) | |
| if movie_data['trailer_key']: | |
| st.markdown(f"[Watch Trailer](https://www.youtube.com/watch?v={movie_data['trailer_key']})") | |
| st.write(movie_data['overview'][:100] + "...") |