"""
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
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;
    }
}
"""

# Function to generate a login URL
def get_login_url():
    # Get the space host from environment variable
    space_host = os.environ.get("SPACE_HOST", "localhost:7860")
    print(f"Space host: {space_host}")
    
    # Construct the full redirect URL
    redirect_uri = f"https://{space_host}/auth/callback"
    
    # Create the complete authorization URL
    auth_url = f"https://huggingface.co/oauth/authorize?client_id=hf&redirect_uri={redirect_uri}&scope=openid%20profile&response_type=code"
    
    # Return JavaScript to open the login page
    return f"""
    <script>
    window.open("{auth_url}", "_blank");
    </script>
    """

# Simple manual authentication check
def check_user(request: gr.Request):
    if request:
        username = request.headers.get("HF-User")
        if username:
            # User is logged in via HF Spaces
            print(f"User logged in: {username}")
            user = db.get_user_by_username(username)
            if not user:
                # Create user if they don't exist
                print(f"Creating new user: {username}")
                is_admin = (username == "Quazim0t0")
                db.add_user(username, username, is_admin)
                user = db.get_user_by_username(username)
            return f"Logged in as: {username}", username, gr.update(visible=False), gr.update(visible=True)
    return "Not logged in", None, gr.update(visible=True), gr.update(visible=False)

# 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") as app:
    # State to track user
    user_state = gr.State(None)
    
    # Login section
    with gr.Row(visible=True, elem_classes=["login-section"]) as login_section:
        with gr.Column():
            status_display = gr.Markdown("Checking login status...")
            login_button = gr.Button("Login with HuggingFace", variant="primary", visible=True, elem_classes=["login-button"])
    
    # User info section
    with gr.Row(visible=False, elem_classes=["login-section"]) as user_section:
        with gr.Column():
            user_info = gr.Markdown("User information")
    
    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"])
    
    # Connect login handler
    login_button.click(fn=get_login_url, inputs=[], outputs=[gr.HTML()])
    
    # Check login on page load
    app.load(
        fn=check_user,
        inputs=[],
        outputs=[status_display, user_state, login_section, user_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()