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""" | |
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 better theme compatibility | |
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; | |
} | |
/* Make Textbox placeholders more visible */ | |
::placeholder { | |
color: var(--body-text-color-subdued) !important; | |
opacity: 0.7 !important; | |
} | |
/* Make tab labels more visible */ | |
.tab-nav button { | |
color: var(--body-text-color) !important; | |
} | |
/* Improve contrast in dataframes */ | |
table.dataframe th, table.dataframe td { | |
color: var(--body-text-color) !important; | |
} | |
/* Ensure buttons have visible text */ | |
button.primary { | |
color: white !important; | |
} | |
/* Force high contrast for dropdown/select options */ | |
.select-option { | |
color: var(--body-text-color) !important; | |
} | |
/* Improve visibility in dark mode specifically */ | |
@media (prefers-color-scheme: dark) { | |
.info-text { | |
background-color: rgba(53, 130, 220, 0.2); | |
} | |
} | |
""" | |
# 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.Default()) as app: | |
gr.Markdown("# π 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, token_input, user_info = create_login_ui() | |
setup_auth_handlers(login_button, logout_button, token_input, user_info, auth_manager) | |
# Main tabs | |
with gr.Tabs() as tabs: | |
with gr.TabItem("π Leaderboard", id=0): | |
leaderboard_ui = create_leaderboard_ui(leaderboard, db) | |
with gr.TabItem("π Submit Model", id=1): | |
submission_ui = create_model_submission_ui(evaluation_queue, auth_manager, db) | |
with gr.TabItem("π 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"]) | |
# 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() |