""" Main application for Dynamic Highscores system. This file integrates all components into a unified application. """ import os import gradio as gr import threading import time from database_schema import DynamicHighscoresDB from auth import HuggingFaceAuth, create_login_ui, setup_auth_handlers from benchmark_selection import BenchmarkSelector, create_benchmark_selection_ui from evaluation_queue import EvaluationQueue, create_model_submission_ui from leaderboard import Leaderboard, create_leaderboard_ui from sample_benchmarks import add_sample_benchmarks # Initialize components in main thread db = DynamicHighscoresDB() auth_manager = HuggingFaceAuth(db) benchmark_selector = BenchmarkSelector(db, auth_manager) evaluation_queue = EvaluationQueue(db, auth_manager) leaderboard = Leaderboard(db) # Initialize sample benchmarks if none exist print("Checking for existing benchmarks...") benchmarks = db.get_benchmarks() if not benchmarks or len(benchmarks) == 0: print("No benchmarks found. Adding sample benchmarks...") try: # Make sure the database path is clear print(f"Database path: {db.db_path}") # Import and call the function directly num_added = add_sample_benchmarks() print(f"Added {num_added} sample benchmarks.") except Exception as e: print(f"Error adding sample benchmarks: {str(e)}") # Try direct DB insertion as fallback try: print("Attempting direct benchmark insertion...") db.add_benchmark( name="MMLU (Massive Multitask Language Understanding)", dataset_id="cais/mmlu", description="Tests knowledge across 57 subjects" ) print("Added fallback benchmark.") except Exception as inner_e: print(f"Fallback insertion failed: {str(inner_e)}") else: print(f"Found {len(benchmarks)} existing benchmarks.") # Custom CSS with theme awareness css = """ /* Theme-adaptive colored info box */ .info-text { background-color: rgba(53, 130, 220, 0.1); padding: 12px; border-radius: 8px; border-left: 4px solid #3498db; margin: 12px 0; } /* High-contrast text for elements - works in light and dark themes */ .info-text, .header, .footer, .tab-content, button, input, textarea, select, option, .gradio-container *, .markdown-text { color: var(--text-color, inherit) !important; } /* Container styling */ .container { max-width: 1200px; margin: 0 auto; } /* Header styling */ .header { text-align: center; margin-bottom: 20px; font-weight: bold; font-size: 24px; } /* Footer styling */ .footer { text-align: center; margin-top: 40px; padding: 20px; border-top: 1px solid var(--border-color-primary, #eee); } /* Force high contrast on specific input areas */ input[type="text"], input[type="password"], textarea { background-color: var(--background-fill-primary) !important; color: var(--body-text-color) !important; } /* Force text visibility in multiple contexts */ .gradio-markdown p, .gradio-markdown h1, .gradio-markdown h2, .gradio-markdown h3, .gradio-markdown h4, .gradio-markdown li { color: var(--body-text-color) !important; } /* Fix dark mode text visibility */ @media (prefers-color-scheme: dark) { input, textarea, select { color: #ffffff !important; } ::placeholder { color: rgba(255, 255, 255, 0.5) !important; } } """ # Check if the server is running in a HuggingFace Space def is_running_in_hf_space(): return 'SPACE_ID' in os.environ # Start evaluation queue worker def start_queue_worker(): # Wait a moment to ensure app is initialized time.sleep(2) try: print("Starting evaluation queue worker...") evaluation_queue.start_worker() except Exception as e: print(f"Error starting queue worker: {e}") # Create Gradio app with gr.Blocks(css=css, title="Dynamic Highscores", theme=gr.themes.Soft()) as app: auth_status = gr.State(None) # Store user auth state # Auth status check on page load def check_auth_on_load(request: gr.Request): # Check if running in HF Space with OAuth if is_running_in_hf_space(): username = request.headers.get("HF-User") if username: print(f"Detected logged-in user via Space OAuth: {username}") # Get or create user user = db.get_user_by_username(username) if not user: print(f"Creating new user: {username}") is_admin = (username == "Quazim0t0") # Replace with your admin username db.add_user(username, username, is_admin) user = db.get_user_by_username(username) return user, f"Logged in as {username}" else: # Fallback to cookie-based auth for local development user = auth_manager.check_login(request) if user: return user, f"Logged in as {user['username']}" return None, "Not logged in" gr.Markdown("# 🏆 Dynamic Highscores", elem_classes=["header"]) gr.Markdown(""" Welcome to Dynamic Highscores - a community benchmark platform for evaluating and comparing language models. - **Add your own benchmarks** from HuggingFace datasets - **Submit your models** for CPU-only evaluation - **Compare performance** across different models and benchmarks - **Filter results** by model type (Merge, Agent, Reasoning, Coding, etc.) """, elem_classes=["info-text"]) # Authentication UI login_button, logout_button, user_info = create_login_ui() setup_auth_handlers(login_button, logout_button, user_info, auth_manager) # Main tabs with gr.Tabs() as tabs: with gr.TabItem("📊 Leaderboard", id=0): leaderboard_ui = create_leaderboard_ui(leaderboard, db) with gr.TabItem("🚀 Submit Model", id=1): submission_ui = create_model_submission_ui(evaluation_queue, auth_manager, db) with gr.TabItem("🔍 Benchmarks", id=2): benchmark_ui = create_benchmark_selection_ui(benchmark_selector, auth_manager) gr.Markdown(""" ### About Dynamic Highscores This platform allows users to select benchmarks from HuggingFace datasets and evaluate models against them. Each user can submit one benchmark per day (admin users are exempt from this limit). All evaluations run on CPU only to ensure fair comparisons. Created by Quazim0t0 """, elem_classes=["footer"]) # Check auth on load app.load( fn=check_auth_on_load, inputs=[], outputs=[auth_status, user_info] ) # Launch the app if __name__ == "__main__": # Start queue worker in a separate thread queue_thread = threading.Thread(target=start_queue_worker) queue_thread.daemon = True queue_thread.start() app.launch()