#!/usr/bin/env python3
"""
Hugging Face Model Upload Script for Advanced Magnus Chess Model
"""

import os
import sys
from pathlib import Path


def upload_magnus_model():
    """Upload the Advanced Magnus Chess Model to Hugging Face"""

    try:
        from huggingface_hub import HfApi, upload_folder, create_repo
    except ImportError:
        print("❌ huggingface_hub not installed!")
        print("Install with: pip install huggingface_hub")
        return False

    # Configuration
    model_name = "advanced-magnus-chess-model"

    print("🔐 Authentication Setup")
    print("You need a Hugging Face account and access token.")
    print("Get a token at: https://huggingface.co/settings/tokens")
    print()

    username = input("Enter your Hugging Face username: ").strip()
    if not username:
        print("❌ Username required!")
        return False

    token = input(
        "Enter your Hugging Face token (or press Enter to use HF_TOKEN env var): "
    ).strip()

    if not token and "HF_TOKEN" in os.environ:
        token = os.environ["HF_TOKEN"]
        print("✅ Using HF_TOKEN from environment")

    if not token:
        print("❌ No Hugging Face token provided!")
        print("Either enter it above or set HF_TOKEN environment variable")
        return False

    repo_id = f"{username}/{model_name}"

    print(f"\n🚀 Uploading model to: {repo_id}")

    # Initialize API
    try:
        api = HfApi(token=token)
        print("✅ Authenticated with Hugging Face")
    except Exception as e:
        print(f"❌ Authentication failed: {e}")
        return False

    # Create repository
    try:
        create_repo(
            repo_id=repo_id,
            token=token,
            repo_type="model",
            exist_ok=True,
            private=False,
        )
        print(f"✅ Repository created/verified: {repo_id}")
    except Exception as e:
        print(f"⚠️ Repository creation issue: {e}")
        print("This might be normal if the repository already exists.")

    # Prepare README for Hugging Face
    readme_content = open("README_HF.md", "r").read()
    with open("README.md", "w") as f:
        f.write(readme_content)
    print("✅ Prepared README for Hugging Face format")

    # Upload the entire folder
    print("\n📤 Starting upload...")
    try:
        upload_folder(
            folder_path=".",
            repo_id=repo_id,
            token=token,
            repo_type="model",
            commit_message="Upload Advanced Magnus Chess Model v20250626 - 2.65M parameters trained on Magnus Carlsen games",
            ignore_patterns=[
                ".git",
                "__pycache__",
                "*.pyc",
                ".DS_Store",
                "upload_instructions.py",
            ],
        )
        print(f"✅ Model uploaded successfully!")
        print(f"\n🌐 View your model at:")
        print(f"   https://huggingface.co/{repo_id}")
        print(f"\n📚 Users can now install and use your model:")
        print(f"   pip install huggingface_hub torch chess")
        print(f"   # Then download and use your model")

    except Exception as e:
        print(f"❌ Upload failed: {e}")
        return False

    return True


if __name__ == "__main__":
    print("🎯 Advanced Magnus Chess Model - Hugging Face Upload")
    print("🏆 2.65M Parameter Neural Network trained on Magnus Carlsen's games")
    print("=" * 70)

    # Check if we're in the right directory
    if not os.path.exists("model.pth"):
        print("❌ model.pth not found in current directory!")
        print("Please run this script from the huggingface_model directory")
        exit(1)

    # Check model file
    model_path = Path("model.pth")
    model_size_mb = model_path.stat().st_size / (1024 * 1024)
    print(f"📁 Model file: {model_path}")
    print(f"📊 Model size: {model_size_mb:.2f} MB")

    # Show model info
    if os.path.exists("config.yaml"):
        try:
            import yaml

            with open("config.yaml", "r") as f:
                config = yaml.safe_load(f)
            print(f"🧠 Architecture: {config['model']['architecture']}")
            print(f"🎯 Parameters: {config['training']['total_params']:,}")
            print(f"📈 Test Accuracy: {config['metrics']['test_accuracy']:.4f}")
        except ImportError:
            print("🧠 Architecture: AdvancedMagnusModel")
            print("🎯 Parameters: 2,651,538")
        except Exception as e:
            print(f"⚠️ Could not read config: {e}")

    print("\n" + "=" * 70)
    proceed = input("Proceed with upload? (y/N): ").strip().lower()

    if proceed == "y":
        success = upload_magnus_model()
        if success:
            print("\n🎉 Upload completed successfully!")
            print("Your Advanced Magnus Chess Model is now available on Hugging Face!")
            print("The chess community can now benefit from your Magnus AI! 🏆")
        else:
            print("\n❌ Upload failed. Please check your credentials and try again.")
    else:
        print("Upload cancelled.")

if __name__ == "__main__":
    print("🎯 Advanced Magnus Chess Model - Hugging Face Upload")
    print("=" * 60)

    # Check if we're in the right directory
    if not os.path.exists("model.pth"):
        print("❌ model.pth not found in current directory!")
        print("Please run this script from the huggingface_model directory")
        exit(1)

    # Check model file
    model_path = Path("model.pth")
    model_size_mb = model_path.stat().st_size / (1024 * 1024)
    print(f"📁 Model file: {model_path}")
    print(f"📊 Model size: {model_size_mb:.2f} MB")

    # Show model info
    if os.path.exists("config.yaml"):
        with open("config.yaml", "r") as f:
            config = yaml.safe_load(f)
        print(f"🧠 Architecture: {config['model']['architecture']}")
        print(f"🎯 Parameters: {config['training']['total_params']:,}")
        print(f"📈 Test Accuracy: {config['metrics']['test_accuracy']:.4f}")

    print("\n" + "=" * 60)
    proceed = input("Proceed with upload? (y/N): ").strip().lower()

    if proceed == "y":
        success = upload_magnus_model()
        if success:
            print("\n🎉 Upload completed successfully!")
            print("Your model is now available on Hugging Face!")
        else:
            print("\n❌ Upload failed. Please check your credentials and try again.")
    else:
        print("Upload cancelled.")