import gradio as gr from gradio_leaderboard import Leaderboard import pandas as pd from huggingface_hub import snapshot_download, create_repo from huggingface_hub.utils import RepositoryNotFoundError import os from src.about import ( INTRODUCTION_TEXT, LLM_BENCHMARKS_TEXT, TITLE, ) from src.display.css_html_js import custom_css from src.display.utils import ( BENCHMARK_COLS, COLS, AutoEvalColumn, fields, ) from src.envs import API, EVAL_RESULTS_PATH, RESULTS_REPO, TOKEN, OWNER from src.populate import get_leaderboard_df from src.evaluation.dynamic_eval import run_dynamic_perplexity_eval def init_leaderboard(dataframe): if dataframe is None: raise ValueError("Leaderboard DataFrame is None.") print("\n=== Initializing Leaderboard ===", flush=True) print(f"DataFrame shape: {dataframe.shape}", flush=True) print(f"DataFrame columns: {dataframe.columns.tolist()}", flush=True) return Leaderboard( value=dataframe, select_columns=[c.name for c in fields(AutoEvalColumn) if not c.hidden], search_columns=[AutoEvalColumn.model.name], hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden], filter_columns=[ AutoEvalColumn.model_type.name, AutoEvalColumn.precision.name, ], ) def refresh_leaderboard(): import sys import traceback try: sys.stderr.write("Refreshing leaderboard data...\n") sys.stderr.flush() # Get fresh leaderboard data df = get_leaderboard_df(EVAL_RESULTS_PATH, COLS, BENCHMARK_COLS) sys.stderr.write(f"Got DataFrame with shape: {df.shape}\n") sys.stderr.write(f"DataFrame columns: {df.columns.tolist()}\n") sys.stderr.flush() # Check if DataFrame is valid for leaderboard if df is None: sys.stderr.write("DataFrame is None, cannot create leaderboard\n") sys.stderr.flush() raise ValueError("DataFrame is None") if df.empty: sys.stderr.write("DataFrame is empty, creating minimal valid DataFrame\n") sys.stderr.flush() # Create a minimal valid DataFrame that won't crash the leaderboard import pandas as pd empty_df = pd.DataFrame(columns=COLS) # Add one dummy row to prevent leaderboard component from crashing dummy_row = {col: 0 if col in BENCHMARK_COLS or col == AutoEvalColumn.average.name else "" for col in COLS} dummy_row[AutoEvalColumn.model.name] = "No models evaluated yet" dummy_row[AutoEvalColumn.model_type_symbol.name] = "?" empty_df = pd.DataFrame([dummy_row]) return init_leaderboard(empty_df) sys.stderr.write("Creating leaderboard with valid DataFrame\n") sys.stderr.flush() return init_leaderboard(df) except Exception as e: error_msg = str(e) traceback_str = traceback.format_exc() sys.stderr.write(f"Error in refresh_leaderboard: {error_msg}\n") sys.stderr.write(f"Traceback: {traceback_str}\n") sys.stderr.flush() raise def run_perplexity_test(model_name, revision, precision): """Run perplexity evaluation on demand.""" import sys import traceback if not model_name: return "Please enter a model name.", None try: # Use stderr for more reliable logging in HF Spaces sys.stderr.write(f"\n=== Running Perplexity Test ===\n") sys.stderr.write(f"Model: {model_name}\n") sys.stderr.write(f"Revision: {revision}\n") sys.stderr.write(f"Precision: {precision}\n") sys.stderr.flush() success, result = run_dynamic_perplexity_eval(model_name, revision, precision) sys.stderr.write(f"Evaluation result - Success: {success}, Result: {result}\n") sys.stderr.flush() if success: try: # Try to refresh leaderboard sys.stderr.write("Attempting to refresh leaderboard...\n") sys.stderr.flush() new_leaderboard = refresh_leaderboard() sys.stderr.write("Leaderboard refresh successful\n") sys.stderr.flush() return f"✅ Perplexity evaluation completed!\nPerplexity: {result:.4f}\n\nResults saved to leaderboard.", new_leaderboard except Exception as refresh_error: # If leaderboard refresh fails, still show success but don't update leaderboard error_msg = str(refresh_error) traceback_str = traceback.format_exc() sys.stderr.write(f"Leaderboard refresh failed: {error_msg}\n") sys.stderr.write(f"Traceback: {traceback_str}\n") sys.stderr.flush() return f"✅ Perplexity evaluation completed!\nPerplexity: {result:.4f}\n\n⚠️ Results saved but leaderboard refresh failed: {error_msg}\n\nPlease refresh the page to see updated results.", None else: return f"❌ Evaluation failed: {result}", None except Exception as e: error_msg = str(e) traceback_str = traceback.format_exc() sys.stderr.write(f"Critical error in run_perplexity_test: {error_msg}\n") sys.stderr.write(f"Traceback: {traceback_str}\n") sys.stderr.flush() return f"❌ Critical error: {error_msg}", None # Initialize results repository and directory try: # Try to download existing repository try: snapshot_download( repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN ) except RepositoryNotFoundError: # Create the repository if it doesn't exist print(f"Creating new results repository: {RESULTS_REPO}") create_repo( repo_id=RESULTS_REPO, repo_type="dataset", private=False, token=TOKEN ) # Create local directory os.makedirs(EVAL_RESULTS_PATH, exist_ok=True) except Exception as e: print(f"Error initializing results: {e}") # Ensure local directory exists even if repo operations fail os.makedirs(EVAL_RESULTS_PATH, exist_ok=True) # Get initial leaderboard data LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, COLS, BENCHMARK_COLS) # Create the Gradio interface demo = gr.Blocks(css=custom_css) with demo: gr.HTML(TITLE) gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") with gr.Tabs(elem_classes="tab-buttons") as tabs: with gr.TabItem("🏅 Leaderboard", elem_id="leaderboard-tab", id=0): leaderboard = init_leaderboard(LEADERBOARD_DF) with gr.TabItem("📝 About", elem_id="about-tab", id=1): gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text") with gr.TabItem("🧪 Test Model", elem_id="test-model-tab", id=2): gr.Markdown("## Run Perplexity Test\n\nTest any Hugging Face model for perplexity evaluation.") with gr.Row(): with gr.Column(): model_name = gr.Textbox(label="Model name", placeholder="openai-community/gpt2") revision = gr.Textbox(label="Revision", placeholder="main", value="main") precision = gr.Dropdown( choices=["float16", "bfloat16"], label="Precision", value="float16" ) debug_mode = gr.Checkbox(label="Enable debug mode (more verbose logging)", value=True) with gr.Column(): test_button = gr.Button("🚀 Run Perplexity Test", variant="primary") result = gr.Markdown() gr.Markdown(""" ### Tips: - Check stderr logs in HF Spaces for detailed debugging information - If evaluation succeeds but leaderboard doesn't update, try refreshing the page - Example models to test: `openai-community/gpt2`, `EleutherAI/gpt-neo-1.3B` """) test_button.click( run_perplexity_test, [model_name, revision, precision], [result, leaderboard] ) demo.queue(default_concurrency_limit=5).launch()