Update app.py

app.py

@@ -4,15 +4,16 @@ from surprise import Dataset, Reader, SVD
 from surprise.model_selection import train_test_split
 from collections import defaultdict
 
-# Step 1: Load dataset from Hugging Face (ensure raw CSV format)
-dataset_url = "https://huggingface.co/datasets/chrisaldikaraharja/MovieRecommendationEngine/raw/main/imdb_movies.csv"
+# Step 1: Load dataset from Hugging Face (raw file URL)
+dataset_url = "https://huggingface.co/spaces/chrisaldikaraharja/MovieRecommendationEngine/resolve/main/imdb_movies.csv"
 
-# Read CSV with error handling
-df = pd.read_csv(dataset_url)
-
-# Display dataset info
-st.write("Dataset Loaded Successfully ✅")
-st.write(df.head())
+try:
+    df = pd.read_csv(dataset_url)
+    st.write("Dataset Loaded Successfully ✅")
+    st.write(df.head())
+except Exception as e:
+    st.error(f"Failed to load dataset: {e}")
+    st.stop()  # Stop the app if the dataset cannot be loaded
 
 # Convert categorical columns to string (avoids data type issues)
 categorical_columns = ['genre', 'orig_title', 'orig_lang', 'country', 'crew']
@@ -64,4 +65,4 @@ if st.button("Get Recommendations"):
     recommendations = get_recommendations(selected_movies, selected_genre)
     st.write("### Recommended Movies:")
     for movie in recommendations:
-        st.write(f"- {movie}")
+        st.write(f"- {movie}")