"""
Utility — GPU Detection
Auto-detect CUDA availability and recommend settings.
"""

import logging
import subprocess

logger = logging.getLogger(__name__)


def detect_gpu() -> dict:
    """
    Detect GPU availability and return system info.
    """
    info = {
        "cuda_available": False,
        "gpu_name": None,
        "gpu_memory_mb": 0,
        "recommended_device": "cpu",
        "recommended_compute": "int8",
        "recommended_batch_size": 4,
    }

    try:
        import torch
        if torch.cuda.is_available():
            info["cuda_available"] = True
            info["gpu_name"] = torch.cuda.get_device_name(0)
            info["gpu_memory_mb"] = torch.cuda.get_device_properties(0).total_mem // (1024 * 1024)
            info["recommended_device"] = "cuda"
            info["recommended_compute"] = "float16"
            info["recommended_batch_size"] = 16 if info["gpu_memory_mb"] > 8000 else 8

            logger.info(f"GPU detected: {info['gpu_name']} ({info['gpu_memory_mb']} MB)")
        else:
            logger.info("PyTorch installed but no CUDA GPU detected.")
    except ImportError:
        logger.info("PyTorch not installed. Using CPU mode.")

    # Fallback: check nvidia-smi
    if not info["cuda_available"]:
        try:
            result = subprocess.run(
                ["nvidia-smi", "--query-gpu=name,memory.total", "--format=csv,noheader"],
                capture_output=True, text=True, timeout=5
            )
            if result.returncode == 0 and result.stdout.strip():
                parts = result.stdout.strip().split(",")
                info["gpu_name"] = parts[0].strip()
                logger.info(f"nvidia-smi found GPU: {info['gpu_name']} (but PyTorch CUDA not available)")
        except (FileNotFoundError, subprocess.TimeoutExpired):
            pass

    return info


def get_system_report() -> str:
    """Generate a human-readable system readiness report."""
    gpu = detect_gpu()
    lines = [
        "=== System Report ===",
        f"GPU: {gpu['gpu_name'] or 'None detected'}",
        f"CUDA: {'Yes' if gpu['cuda_available'] else 'No'}",
        f"VRAM: {gpu['gpu_memory_mb']} MB" if gpu['gpu_memory_mb'] else "VRAM: N/A",
        f"Mode: {gpu['recommended_device'].upper()}",
        f"Compute: {gpu['recommended_compute']}",
        f"Batch size: {gpu['recommended_batch_size']}",
        "",
        "Estimated processing times for 2.5hr video:",
    ]

    if gpu["cuda_available"] and gpu["gpu_memory_mb"] > 8000:
        lines.append("  Transcription: ~15-25 min")
        lines.append("  TTS Generation: ~20-30 min")
        lines.append("  Total: ~45-75 min")
    elif gpu["cuda_available"]:
        lines.append("  Transcription: ~25-40 min")
        lines.append("  TTS Generation: ~30-45 min")
        lines.append("  Total: ~75-120 min")
    else:
        lines.append("  Transcription: ~2-4 hours (CPU)")
        lines.append("  TTS Generation: ~1-2 hours (CPU)")
        lines.append("  Total: ~3-6 hours")
        lines.append("  ⚠ GPU strongly recommended for videos > 30 min")

    return "\n".join(lines)