Starlight Features Test: Verifying New Integration

This article tests all the new Starlight-inspired features added to Groundy.

Expressive Code Blocks

Here’s a Python example with syntax highlighting:

def calculate_embedding_similarity(vec1, vec2):
    """Calculate cosine similarity between two vectors."""
    dot_product = sum(a * b for a, b in zip(vec1, vec2))
    magnitude1 = sum(a * a for a in vec1) ** 0.5
    magnitude2 = sum(b * b for b in vec2) ** 0.5
    return dot_product / (magnitude1 * magnitude2)

# Example usage
embedding1 = [0.1, 0.2, 0.3, 0.4]
embedding2 = [0.2, 0.3, 0.4, 0.5]
similarity = calculate_embedding_similarity(embedding1, embedding2)
print(f"Similarity: {similarity:.4f}")

Asides and Callouts

Comparison Tables

Task Lists

Implementation checklist:

• Install vector database
• Configure embedding model
• Index documents
• Test query performance
• Deploy to production

Footnotes

Vector embeddings capture semantic meaning through high-dimensional numerical representations.¹ This enables machines to understand conceptual similarity between pieces of content.²

Blockquote Callouts (Legacy)

💡 Tip: Legacy blockquote syntax still works for backward compatibility.

⚠️ Warning: This is the old way of creating callouts.

Inline Code

Use pip install zvec to install the package. The calculate_embedding_similarity() function returns a float between -1 and 1.

Strikethrough

Old approach New approach is recommended for better performance.

Frequently Asked Questions

Q: Do the new aside directives work correctly? A: Yes, they render with colored borders and appropriate icons.

Q: Are code blocks enhanced with copy buttons? A: Yes, expressive-code adds copy functionality and syntax highlighting.

Q: Do tables render properly? A: Yes, with responsive scrolling and styled headers.