"""
OCR Arena - Main Application
A Gradio web application for comparing OCR results from different AI models.
"""

import gradio as gr
import logging
import os
import datetime
from dotenv import load_dotenv
from storage import upload_file_to_bucket
from db import add_vote, get_all_votes, calculate_elo_ratings_from_votes
from ocr_models import process_model_ocr, initialize_gemini, initialize_mistral, initialize_openai
from ui_helpers import (
    get_model_display_name, select_random_models, format_votes_table, 
    format_elo_leaderboard
)

# Load environment variables
load_dotenv()

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
logger = logging.getLogger(__name__)

# Initialize API keys and models
initialize_gemini()
initialize_mistral()
initialize_openai()

# Get Supabase credentials
SUPABASE_URL = os.getenv("SUPABASE_URL")
SUPABASE_KEY = os.getenv("SUPABASE_KEY")

# Global variables
current_gemini_output = ""
current_mistral_output = ""
current_openai_output = ""
current_gpt5_output = ""
current_image_url = ""
current_model_a = ""
current_model_b = ""


def process_image_single_click(image):
    """Process uploaded image and run OCR for both models in one click."""
    global current_gemini_output, current_mistral_output, current_openai_output, current_gpt5_output
    global current_model_a, current_model_b, current_image_url

    if image is None:
        return "Please upload an image.", "Please upload an image.", gr.update(visible=False), gr.update(visible=False)

    # Select two random models
    model_a, model_b = select_random_models()
    current_model_a = model_a
    current_model_b = model_b

    # Save image temporarily
    temp_filename = f"temp_image_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.png"
    image.save(temp_filename)

    # Upload image to Supabase
    try:
        upload_result = upload_file_to_bucket(
            file_path=temp_filename,
            bucket_name="images",
            storage_path=f"ocr_images/{temp_filename}",
            file_options={"cache-control": "3600", "upsert": "false"}
        )
        if upload_result["success"]:
            current_image_url = upload_result.get("public_url") or f"{SUPABASE_URL}/storage/v1/object/public/images/ocr_images/{temp_filename}"
        else:
            current_image_url = ""
            logger.error(f"Image upload failed: {upload_result.get('error')}")
    finally:
        try:
            os.remove(temp_filename)
        except Exception as e:
            logger.warning(f"Could not remove temp file: {e}")

    # Run OCR for both models
    output_a = process_model_ocr(image, model_a)
    output_b = process_model_ocr(image, model_b)

    # Store outputs in globals
    def store_output(model, output):
        global current_gemini_output, current_mistral_output, current_openai_output, current_gpt5_output
        if model == "gemini":
            current_gemini_output = output
        elif model == "mistral":
            current_mistral_output = output
        elif model == "openai":
            current_openai_output = output
        elif model == "gpt5":
            current_gpt5_output = output

    store_output(model_a, output_a)
    store_output(model_b, output_b)

    return output_a, output_b, gr.update(visible=True), gr.update(visible=True)


def load_vote_data():
    """Load and format vote data for display."""
    try:
        votes = get_all_votes()
        return format_votes_table(votes)
    except Exception as e:
        logger.error(f"Error loading vote data: {e}")
        return f"<p style='color:red;'>Error loading data: {e}</p>"


def load_elo_leaderboard():
    """Load and format ELO leaderboard data."""
    try:
        votes = get_all_votes()
        elo_ratings = calculate_elo_ratings_from_votes(votes)
        vote_counts = {"gemini": 0, "mistral": 0, "openai": 0, "gpt5": 0}
        for vote in votes:
            model_a, model_b, vote_choice = vote.get("model_a"), vote.get("model_b"), vote.get("vote")
            if vote_choice == "model_a" and model_a in vote_counts:
                vote_counts[model_a] += 1
            elif vote_choice == "model_b" and model_b in vote_counts:
                vote_counts[model_b] += 1
        return format_elo_leaderboard(elo_ratings, vote_counts)
    except Exception as e:
        logger.error(f"Error loading leaderboard: {e}")
        return f"<p style='color:red;'>Error loading leaderboard: {e}</p>"


with gr.Blocks(title="OCR Comparison", css="""
    .output-box {border:2px solid #e0e0e0; border-radius:8px; padding:15px; margin:10px 0; background-color:#f9f9f9; min-height:200px;}
    .vote-table {border-collapse: collapse; width:100%; margin:10px 0; min-width:800px;}
    .vote-table th, .vote-table td {border:1px solid #ddd; padding:6px; text-align:left; vertical-align:top;}
    .vote-table th {background-color:#f2f2f2; font-weight:bold; position:sticky; top:0; z-index:10;}
    .vote-table tr:nth-child(even){background-color:#f9f9f9;}
""") as demo:

    with gr.Tabs():

        # Arena Tab
        with gr.Tab("⚔️ Arena"):
            gr.Markdown("# ⚔️ OCR Arena")
            gr.Markdown("Upload an image to compare two randomly selected OCR models.")

            with gr.Row():
                gemini_output = gr.Markdown(label="Model A Output", elem_classes=["output-box"])
                image_input = gr.Image(type="pil", label="Upload or Paste Image")
                mistral_output = gr.Markdown(label="Model B Output", elem_classes=["output-box"])

            with gr.Row():
                gemini_vote_btn = gr.Button("A is better", variant="primary", size="sm", visible=False)
                mistral_vote_btn = gr.Button("B is better", variant="primary", size="sm", visible=False)

            process_btn = gr.Button("🔍 Run OCR", variant="primary")

        # Data Tab
        with gr.Tab("📊 Data"):
            gr.Markdown("# 📊 Vote Data")
            refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
            votes_table = gr.HTML("<p>Loading vote data...</p>")

        # Leaderboard Tab
        with gr.Tab("🏆 Leaderboard"):
            gr.Markdown("# 🏆 ELO Leaderboard")
            refresh_leaderboard_btn = gr.Button("🔄 Refresh Leaderboard", variant="secondary")
            leaderboard_display = gr.HTML("<p>Loading ELO leaderboard...</p>")

    # Event handlers
    process_btn.click(
        process_image_single_click,
        inputs=[image_input],
        outputs=[gemini_output, mistral_output, gemini_vote_btn, mistral_vote_btn]
    )

    refresh_btn.click(load_vote_data, inputs=None, outputs=[votes_table])
    refresh_leaderboard_btn.click(load_elo_leaderboard, inputs=None, outputs=[leaderboard_display])

    # Load data and leaderboard on start
    demo.load(fn=load_vote_data, inputs=None, outputs=[votes_table])
    demo.load(fn=load_elo_leaderboard, inputs=None, outputs=[leaderboard_display])

if __name__ == "__main__":
    logger.info("Starting OCR Comparison App...")
    demo.launch(share=True)