mixvideo-v2/cargos/tvai/examples/convenience_and_optimization.rs

//! Convenience interfaces and optimization examples

use tvai::*;
use tvai::config::{global_settings, global_presets};
use tvai::utils::{GpuManager, PerformanceMonitor, optimize_for_system};

#[tokio::main]
async fn main() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("Topaz Video AI Library - Convenience and Optimization Examples");
    
    // Demonstrate global settings management
    demonstrate_global_settings().await?;
    
    // Demonstrate preset management
    demonstrate_preset_management().await?;
    
    // Demonstrate GPU detection and optimization
    demonstrate_gpu_optimization().await?;
    
    // Demonstrate performance monitoring
    demonstrate_performance_monitoring().await?;
    
    // Demonstrate error handling
    demonstrate_error_handling().await?;
    
    println!("All convenience and optimization examples completed successfully!");
    
    Ok(())
}

async fn demonstrate_global_settings() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("\n=== Global Settings Management Demo ===");
    
    // Get global settings manager
    let settings_manager = global_settings();
    
    // Display current settings
    let current_settings = settings_manager.get_settings();
    println!("Current Settings:");
    println!("  Default GPU usage: {}", current_settings.default_use_gpu);
    println!("  Max concurrent jobs: {}", current_settings.max_concurrent_jobs);
    println!("  Auto-detect Topaz: {}", current_settings.auto_detect_topaz);
    println!("  Verbose logging: {}", current_settings.verbose_logging);
    
    // Update settings
    settings_manager.set_default_use_gpu(true)?;
    settings_manager.set_max_concurrent_jobs(2)?;
    println!("Updated settings successfully");
    
    // Create config from global settings
    match settings_manager.create_config() {
        Ok(_config) => println!("Successfully created config from global settings"),
        Err(e) => println!("Config creation failed (expected): {}", e.user_friendly_message()),
    }
    
    Ok(())
}

async fn demonstrate_preset_management() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("\n=== Preset Management Demo ===");
    
    // Get global preset manager
    let presets = global_presets();
    let preset_manager = presets.lock().unwrap();
    
    // List available video presets
    println!("Available Video Presets:");
    for preset_name in preset_manager.list_video_presets() {
        if let Some(preset) = preset_manager.get_video_preset(&preset_name) {
            println!("  {}: {}", preset.name, preset.description);
        }
    }
    
    // List available image presets
    println!("\nAvailable Image Presets:");
    for preset_name in preset_manager.list_image_presets() {
        if let Some(preset) = preset_manager.get_image_preset(&preset_name) {
            println!("  {}: {}", preset.name, preset.description);
        }
    }
    
    // Demonstrate using a preset
    if let Some(preset) = preset_manager.get_video_preset("general_2x") {
        println!("\nUsing preset: {}", preset.name);
        if let Some(ref upscale) = preset.upscale {
            println!("  Upscale model: {}", upscale.model.as_str());
            println!("  Scale factor: {}x", upscale.scale_factor);
        }
    }
    
    Ok(())
}

async fn demonstrate_gpu_optimization() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("\n=== GPU Optimization Demo ===");
    
    // Detect detailed GPU information
    let gpu_info = GpuManager::detect_detailed_gpu_info();
    println!("GPU Detection Results:");
    println!("  Available: {}", gpu_info.available);
    println!("  CUDA: {}", gpu_info.cuda_available);
    println!("  OpenCL: {}", gpu_info.opencl_available);
    println!("  Vulkan: {}", gpu_info.vulkan_available);
    
    // Display detected devices
    println!("\nDetected GPU Devices:");
    for (idx, device) in gpu_info.devices.iter().enumerate() {
        println!("  Device {}: {}", idx, device.name);
        println!("    Vendor: {}", device.vendor);
        if let Some(memory) = device.memory_mb {
            println!("    Memory: {} MB", memory);
        }
        println!("    AI Support: {}", device.supports_ai);
    }
    
    // Display recommendations
    println!("\nRecommended Settings:");
    println!("  Use GPU: {}", gpu_info.recommended_settings.use_gpu);
    if let Some(device_idx) = gpu_info.recommended_settings.preferred_device {
        println!("  Preferred device: {}", device_idx);
    }
    if let Some(memory_limit) = gpu_info.recommended_settings.memory_limit_mb {
        println!("  Memory limit: {} MB", memory_limit);
    }
    println!("  Concurrent streams: {}", gpu_info.recommended_settings.concurrent_streams);
    
    // Check if GPU is suitable for AI
    let suitable = GpuManager::is_gpu_suitable_for_ai();
    println!("\nGPU suitable for AI workloads: {}", suitable);
    
    // Benchmark GPU performance
    println!("\nRunning GPU benchmark...");
    match GpuManager::benchmark_gpu_performance().await {
        Ok(benchmark) => {
            println!("Benchmark Results:");
            println!("  Processing time: {:?}", benchmark.processing_time);
            println!("  Memory bandwidth: {:.1} GB/s", benchmark.memory_bandwidth_gbps);
            println!("  Compute score: {}", benchmark.compute_score);
            println!("  Recommended for AI: {}", benchmark.recommended_for_ai);
        }
        Err(e) => println!("Benchmark failed: {}", e),
    }
    
    Ok(())
}

async fn demonstrate_performance_monitoring() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("\n=== Performance Monitoring Demo ===");
    
    // Create optimized performance settings
    let settings = optimize_for_system();
    println!("Optimized Performance Settings:");
    println!("  Max concurrent ops: {}", settings.max_concurrent_ops);
    println!("  Processing mode: {:?}", settings.processing_mode);
    println!("  Chunk size: {} MB", settings.chunk_size_mb);
    println!("  Monitoring enabled: {}", settings.enable_monitoring);
    
    // Create performance monitor
    let mut monitor = PerformanceMonitor::new(settings);
    
    // Simulate a processing operation
    println!("\nSimulating processing operation...");
    let metrics = {
        let _permit = monitor.acquire_slot().await?;
        let operation_monitor = monitor.start_operation("video_upscale", 100.0);

        // Simulate processing time
        tokio::time::sleep(std::time::Duration::from_millis(500)).await;

        // Finish monitoring
        operation_monitor.finish(200.0)
    };

    // Record metrics after permit is dropped
    monitor.record_metrics(metrics.clone());
    
    println!("Operation completed:");
    println!("  Input size: {:.1} MB", metrics.input_size_mb);
    println!("  Output size: {:.1} MB", metrics.output_size_mb);
    println!("  Processing time: {:?}", metrics.processing_time);
    println!("  Throughput: {:.2} MB/s", metrics.throughput_mbps);
    
    // Get performance summary
    let summary = monitor.get_summary();
    println!("\nPerformance Summary:");
    println!("  Total operations: {}", summary.total_operations);
    println!("  Average throughput: {:.2} MB/s", summary.average_throughput_mbps);
    
    if !summary.recommendations.is_empty() {
        println!("  Recommendations:");
        for rec in summary.recommendations {
            println!("    • {}", rec);
        }
    }
    
    Ok(())
}

async fn demonstrate_error_handling() -> std::result::Result<(), Box<dyn std::error::Error>> {
    println!("\n=== Enhanced Error Handling Demo ===");
    
    // Demonstrate different error types and their user-friendly messages
    let errors = vec![
        TvaiError::TopazNotFound("/invalid/path".to_string()),
        TvaiError::FfmpegError("Invalid codec".to_string()),
        TvaiError::InvalidParameter("Scale factor out of range".to_string()),
        TvaiError::GpuError("CUDA out of memory".to_string()),
        TvaiError::UnsupportedFormat("WEBM".to_string()),
        TvaiError::InsufficientResources("Not enough memory".to_string()),
        TvaiError::PermissionDenied("Cannot write to output directory".to_string()),
    ];
    
    for error in errors {
        println!("\nError Type: {}", error.category());
        println!("Recoverable: {}", error.is_recoverable());
        println!("User-friendly message:");
        println!("{}", error.user_friendly_message());
        println!("{}", "-".repeat(50));
    }
    
    Ok(())
}

// Helper function to create a progress callback
fn create_progress_callback(operation_name: &str) -> ProgressCallback {
    let name = operation_name.to_string();
    Box::new(move |progress| {
        let percentage = (progress * 100.0) as u32;
        println!("{}: {}%", name, percentage);
    })
}