def create_knowledge_graph(df):
    # Create unique constraints
    try:
        # For Neo4j 5.x and later
        graph.run("CREATE CONSTRAINT product_id IF NOT EXISTS FOR (p:Product) REQUIRE p.uniq_id IS UNIQUE")
        graph.run("CREATE CONSTRAINT manufacturer_name IF NOT EXISTS FOR (m:Manufacturer) REQUIRE m.name IS UNIQUE")
        graph.run("CREATE CONSTRAINT category_name IF NOT EXISTS FOR (c:Category) REQUIRE c.name IS UNIQUE")
    except Exception as e:
        # For Neo4j 4.x
        try:
            graph.run("CREATE CONSTRAINT ON (p:Product) ASSERT p.uniq_id IS UNIQUE")
            graph.run("CREATE CONSTRAINT ON (m:Manufacturer) ASSERT m.name IS UNIQUE")
            graph.run("CREATE CONSTRAINT ON (c:Category) ASSERT c.name IS UNIQUE")
        except Exception as e:
            print(f"Warning: Could not create constraints: {e}")

    for _, row in df.iterrows():
        # Create Product node
        product = Node(
            "Product",
            uniq_id=row['uniq_id'],
            name=row['product_name'],
            description=row['product_description'],
            price=float(row['price_value']),
            currency=row['currency'],
            review_rating=float(row['average_review_rating']),
            review_count=int(row['number_of_reviews']),
            stock_type=row['stock_type'] if pd.notna(row['stock_type']) else None,
            description_complete=row['description_complete']
        )

        # Create Manufacturer node
        manufacturer = Node("Manufacturer", name=row['manufacturer'])

        # Create Category nodes from hierarchy
        categories = row['amazon_category_and_sub_category'].split(' > ')
        previous_category = None
        for cat in categories:
            category = Node("Category", name=cat.strip())
            graph.merge(category, "Category", "name")
            if previous_category:
                # Create hierarchical relationship between categories
                rel = Relationship(previous_category, "HAS_SUBCATEGORY", category)
                graph.merge(rel)
            previous_category = category
        # Merge nodes and create relationships
        graph.merge(product, "Product", "uniq_id")
        graph.merge(manufacturer, "Manufacturer", "name")
        # Connect product to manufacturer
        graph.merge(Relationship(product, "MANUFACTURED_BY", manufacturer))
        # Connect product to lowest-level category
        graph.merge(Relationship(product, "BELONGS_TO", previous_category))
# Create the knowledge graph
create_knowledge_graph(df)