Update app.py

app.py

@@ -1,22 +1,42 @@
-from flask import Flask, render_template, request
+from transformers import pipeline
 
-app = Flask(__name__)
+# Load a pre-trained model for text classification (e.g., sentiment analysis)
+classifier = pipeline("sentiment-analysis")
 
-# Sample movie database
-movie_database = {
-    "happy": {"title": "The Pursuit of Happyness", "image_url": "https://example.com/happy.jpg"},
-    "sad": {"title": "The Fault in Our Stars", "image_url": "https://example.com/sad.jpg"},
-    "excited": {"title": "Mad Max: Fury Road", "image_url": "https://example.com/excited.jpg"},
-    "relaxed": {"title": "The Secret Life of Walter Mitty", "image_url": "https://example.com/relaxed.jpg"}
+# Simple movie recommendations based on mood
+movie_recommendations = {
+    "happy": {
+        "comedy": {"title": "The Grand Budapest Hotel", "image_url": "comedy_movie_image_url"},
+        "action": {"title": "Guardians of the Galaxy", "image_url": "action_movie_image_url"}
+    },
+    "sad": {
+        "drama": {"title": "The Pursuit of Happyness", "image_url": "drama_movie_image_url"},
+        "romance": {"title": "The Notebook", "image_url": "romance_movie_image_url"}
+    },
+    "angry": {
+        "action": {"title": "Mad Max: Fury Road", "image_url": "action_movie_image_url"},
+        "thriller": {"title": "John Wick", "image_url": "thriller_movie_image_url"}
+    }
 }
 
-@app.route('/', methods=['GET', 'POST'])
-def home():
-    if request.method == 'POST':
-        mood = request.form.get('mood').lower()
-        movie = movie_database.get(mood, None)
-        return render_template('result.html', movie=movie)
-    return render_template('index.html')
+# Ask user for their mood and preferred genre
+mood_input = input("Enter your mood (happy, sad, angry): ").lower()
+genre_input = input("Enter your preferred genre (comedy, action, drama, romance, thriller): ").lower()
 
-if __name__ == '__main__':
-    app.run(debug=True)
+# Use sentiment analysis to confirm or adjust the user's mood input (optional)
+result = classifier(mood_input)[0]
+detected_mood = result['label'].lower()
+
+if detected_mood in movie_recommendations:
+    mood = detected_mood
+else:
+    mood = mood_input
+
+# Fetch the movie recommendation
+movie = movie_recommendations.get(mood, {}).get(genre_input, None)
+
+if movie:
+    print(f"We recommend you watch '{movie['title']}'!")
+    print(f"Movie Image: {movie['image_url']}")
+else:
+    print("Sorry, we couldn't find a recommendation for your mood and genre combination.")