app.py

"""
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

# Set essential OAuth environment variables
os.environ["OAUTH_CLIENT_ID"] = "hf"
os.environ["OAUTH_CLIENT_SECRET"] = "hf"
os.environ["OAUTH_AUTHORIZATION_URL"] = "https://huggingface.co/oauth/authorize"
os.environ["OAUTH_TOKEN_URL"] = "https://huggingface.co/oauth/token"
os.environ["OAUTH_SCOPES"] = "inference"
os.environ["OPENID_PROVIDER_URL"] = "https://huggingface.co"

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);
}

/* Login section styling */
.login-section {
    padding: 10px;
    margin-bottom: 15px;
    border-radius: 8px;
    background-color: rgba(250, 250, 250, 0.1);
    text-align: center;
}

/* Login button styling */
.login-button {
    background-color: #4CAF50 !important;
    color: white !important;
    font-weight: bold;
}

/* 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

# Function to trigger HuggingFace OAuth login
def trigger_hf_oauth():
    return """
    <script>
    // Redirect to HuggingFace Space login
    window.location.href = window.location.origin + "?__space_auth_callback=true";
    </script>
    """

# 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 - without theme to avoid OAuth issues
with gr.Blocks(css=css, title="Dynamic Highscores") as app:
    login_info = gr.LoginButton(visible=True)
    auth_status = gr.State(None)  # Store user auth state
    
    # Add a prominent login section at the top
    with gr.Row(visible=True, elem_classes=["login-section"]) as login_section:
        with gr.Column():
            login_status = gr.Markdown("### 🔒 Not logged in", elem_id="login-status")
            login_button = gr.Button("Login with HuggingFace", size="lg", variant="primary", elem_classes=["login-button"])
    
    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"])
    
    # 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"])
    
    # 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)
                
                # Update UI for logged in state
                return user, f"### ✅ Logged in as {username}", gr.update(visible=False)
        
        # Not logged in - make sure login section is visible
        return None, "### 🔒 Not logged in", gr.update(visible=True)
    
    # Connect event handlers
    login_button.click(
        fn=trigger_hf_oauth,
        inputs=[],
        outputs=[gr.HTML()]
    )
    
    # Check auth on load
    app.load(
        fn=check_auth_on_load, 
        inputs=[],
        outputs=[auth_status, login_status, login_section]
    )

# 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()