element
"""
benchmarks_info = get_benchmark_info()
# Start with model header (column 0)
headers_html = "\n"
headers_html += ' | Model ↕ | \n'
# Add benchmark headers (columns 1+)
for idx, bench_key in enumerate(selected_benchmarks, start=1):
bench_info = benchmarks_info.get(bench_key, {})
bench_name = bench_info.get("name", bench_key)
headers_html += f' {bench_name} ↕ | \n'
headers_html += "
\n"
return headers_html
def generate_model_cell(row: pd.Series, provider_logos: Dict[str, str]) -> str:
"""
Generate HTML for the model cell (sticky first column).
Args:
row: DataFrame row containing model data
provider_logos: Dictionary mapping provider names to logo URLs
Returns:
str: HTML string for model element
"""
model_id = row.get("model_id", "")
model_name = row.get("model_name", model_id)
provider = row.get("provider", "Unknown")
# Try parameters_display first (formatted), then parameters_billions
params = row.get("parameters_display", row.get("parameters", "Unknown"))
# Get provider logo - first try logo_url column, then fallback to provider_logos dict
provider_logo_url = row.get("logo_url")
if not provider_logo_url or pd.isna(provider_logo_url):
provider_logo_url = provider_logos.get(provider)
if provider_logo_url:
logo_html = f' '
else:
# Fallback: show first 2 letters of provider name
initials = provider[:2].upper() if provider and provider != "Unknown" else "??"
logo_html = f'{initials}'
# Format HuggingFace link - use model_name which contains the repo path (e.g., "Meta/Llama-3")
hf_link = f"https://huggingface.co/{model_name}" if model_name else "#"
cell_html = f''' |
| '''
return cell_html
def generate_score_cell(score, benchmark_key: str) -> str:
"""
Generate HTML for a score cell with category-specific color.
Args:
score: The benchmark score (float, None, or NaN)
benchmark_key: The benchmark key (for color coding)
Returns:
str: HTML string for score element
"""
# Check if score is missing/invalid
if pd.isna(score) or score is None:
return ' | — | '
try:
score_float = float(score)
color = get_benchmark_category_color(benchmark_key)
score_display = f"{score_float:.1f}"
return f' | '
except (ValueError, TypeError):
return ' — | '
def generate_table_rows(
df: pd.DataFrame, selected_benchmarks: List[str], provider_logos: Dict[str, str]
) -> str:
"""
Generate HTML for all table rows.
Args:
df: DataFrame containing leaderboard data
selected_benchmarks: List of benchmark keys to display
provider_logos: Dictionary mapping provider names to logo URLs
Returns:
str: HTML string for