Update app.py

app.py

@@ -1,4 +1,5 @@
-from flask import Flask, render_template, request, jsonify
+import os
+from flask import Flask, render_template, request
 import pandas as pd
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
@@ -60,7 +61,7 @@ class BookRecommender:
         except Exception as e:
             return f"An error occurred: {e}"
 
-        similar_books_indices = self.similarity_matrix[book_index].argsort()[::-1][1:6]  # Fixed top_n to 5
+        similar_books_indices = self.similarity_matrix[book_index].argsort()[::-1][1:6]
         recommended_books = self.df['title'].iloc[similar_books_indices].tolist()
         return recommended_books
 
@@ -81,7 +82,7 @@ recommender = BookRecommender()
 @app.route("/", methods=["GET", "POST"])
 def index():
     message = ""
-    recommendations = None # Initialize recommendations
+    recommendations = None
     if request.method == "POST":
         if 'file' in request.files:
             file = request.files['file']
@@ -104,12 +105,13 @@ def index():
                 message = "Please upload and process a file first."
             else:
                 recommendations = recommender.recommend_books(book_title)
-                if isinstance(recommendations, str): # Check if it is an error message.
+                if isinstance(recommendations, str):
                     message = recommendations
                 else:
-                    message = "" # Clear any previous messages.
+                    message = ""
     return render_template("index.html", message=message, recommendations=recommendations)
 
 
 if __name__ == "__main__":
-    app.run(debug=True)
+    port = int(os.environ.get("PORT", 5000))  # Get port from environment or default to 5000
+    app.run(debug=True, host='0.0.0.0', port=port)  # Run on all interfaces, specified port