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from unique_product_mapping import product_to_category, goal_format | |
def get_recommendations(selected_item, goal_format): | |
# Find the class/category of the selected item | |
selected_class_dict = product_to_category.get(selected_item, None) | |
if selected_class_dict is None: | |
print("Product not found.") | |
return None, [] | |
selected_class = selected_class_dict.get('category', None) | |
if not selected_class: | |
print("Category not found for the selected product.") | |
return None, [] | |
print(f"Selected Category: {selected_class}") | |
# Filter all products in the same class/category | |
same_class_products = goal_format.get(selected_class, []) | |
# Remove the selected item itself from the list of recommendations (optional) | |
if selected_item in same_class_products: | |
same_class_products.remove(selected_item) | |
# Prepare a list of recommendations with their image paths | |
recommendations_with_images = [ | |
{"product": product, "image": product_to_category.get(product, {}).get('image', 'No image available')} | |
for product in same_class_products | |
] | |
return selected_class, recommendations_with_images | |
def cat_recc(selected_item): | |
category, recommendations = get_recommendations(selected_item, goal_format) | |
print(f"Selected Item: {selected_item}") | |
print("Recommended:") | |
for recommendation in recommendations: | |
print(f"Product: {recommendation['product']}, Image Path: {recommendation['image']}") | |