trustformers-mobile 0.1.1

//! iOS Background Processing for Inference
//!
//! This module implements iOS background processing capabilities to enable
//! inference tasks to continue running when the app is backgrounded or suspended.
//! Includes support for Background App Refresh, background tasks, and silent notifications.

use crate::{MobileConfig, Result};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
use std::time::{Duration, Instant};
use trustformers_core::{CoreError, Tensor};

/// iOS background processing configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct iOSBackgroundConfig {
    /// Enable Background App Refresh
    pub background_app_refresh: bool,
    /// Enable background processing tasks
    pub background_tasks: bool,
    /// Enable silent push notifications
    pub silent_notifications: bool,
    /// Maximum background execution time (seconds)
    pub max_background_time: u64,
    /// Priority for background tasks
    pub background_priority: BackgroundPriority,
    /// Enable background model updates
    pub background_model_updates: bool,
    /// Enable background federated learning
    pub background_federated_learning: bool,
    /// Power conservation mode in background
    pub power_conservation: bool,
    /// Maximum memory usage in background (MB)
    pub max_background_memory_mb: u32,
}

impl Default for iOSBackgroundConfig {
    fn default() -> Self {
        Self {
            background_app_refresh: true,
            background_tasks: true,
            silent_notifications: true,
            max_background_time: 30, // iOS typically gives 30 seconds
            background_priority: BackgroundPriority::Normal,
            background_model_updates: true,
            background_federated_learning: false,
            power_conservation: true,
            max_background_memory_mb: 50, // Conservative memory usage
        }
    }
}

/// Background task priorities
#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
pub enum BackgroundPriority {
    Low,
    Normal,
    High,
    UserInitiated,
}

/// Background task types
#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
pub enum BackgroundTaskType {
    /// Background App Refresh task
    AppRefresh,
    /// Background processing task
    Processing,
    /// Background URL session
    URLSession,
    /// Silent notification processing
    SilentNotification,
    /// Background model update
    ModelUpdate,
    /// Background federated learning
    FederatedLearning,
}

/// Background task states
#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
pub enum BackgroundTaskState {
    /// Task is pending execution
    Pending,
    /// Task is currently running
    Running,
    /// Task completed successfully
    Completed,
    /// Task was cancelled due to time limit
    Cancelled,
    /// Task failed with error
    Failed,
    /// Task was suspended
    Suspended,
}

/// iOS background processing manager
pub struct iOSBackgroundManager {
    config: iOSBackgroundConfig,
    mobile_config: MobileConfig,
    active_tasks: Arc<Mutex<HashMap<String, BackgroundTask>>>,
    task_queue: Arc<Mutex<Vec<PendingTask>>>,
    background_state: Arc<Mutex<BackgroundState>>,
    stats: Arc<Mutex<BackgroundStats>>,
}

impl iOSBackgroundManager {
    /// Create new iOS background manager
    pub fn new(config: iOSBackgroundConfig, mobile_config: MobileConfig) -> Result<Self> {
        Ok(Self {
            config,
            mobile_config,
            active_tasks: Arc::new(Mutex::new(HashMap::new())),
            task_queue: Arc::new(Mutex::new(Vec::new())),
            background_state: Arc::new(Mutex::new(BackgroundState::Foreground)),
            stats: Arc::new(Mutex::new(BackgroundStats::default())),
        })
    }

    /// Register background task capability
    pub fn register_background_tasks(&self) -> Result<()> {
        // In a real implementation, this would register with iOS:
        // - BGAppRefreshTaskRequest for background app refresh
        // - BGProcessingTaskRequest for longer background processing
        // - Background modes in Info.plist

        self.log_background_event("Background tasks registered successfully");
        Ok(())
    }

    /// Handle app entering background
    pub fn app_did_enter_background(&self) -> Result<()> {
        {
            let mut state = self.background_state.lock().expect("Operation failed");
            *state = BackgroundState::Background;
        }

        // Start background tasks if configured
        if self.config.background_tasks {
            self.start_background_processing()?;
        }

        // Reduce memory usage
        if self.config.power_conservation {
            self.enable_power_conservation_mode()?;
        }

        self.log_background_event("App entered background mode");
        Ok(())
    }

    /// Handle app entering foreground
    pub fn app_will_enter_foreground(&self) -> Result<()> {
        {
            let mut state = self.background_state.lock().expect("Operation failed");
            *state = BackgroundState::Foreground;
        }

        // Resume normal operation
        self.disable_power_conservation_mode()?;

        // Complete any pending background tasks
        self.finalize_background_tasks()?;

        self.log_background_event("App entered foreground mode");
        Ok(())
    }

    /// Schedule background inference task
    pub fn schedule_background_inference(
        &self,
        task_id: String,
        input_data: Vec<Tensor>,
        priority: BackgroundPriority,
        earliest_start: Option<Instant>,
    ) -> Result<()> {
        let task = PendingTask {
            id: task_id.clone(),
            task_type: BackgroundTaskType::Processing,
            input_data,
            priority,
            scheduled_time: earliest_start.unwrap_or_else(Instant::now),
            max_execution_time: Duration::from_secs(self.config.max_background_time),
            created_at: Instant::now(),
        };

        {
            let mut queue = self.task_queue.lock().expect("Operation failed");
            queue.push(task);
            // Sort by priority and scheduled time
            queue.sort_by(|a, b| {
                a.priority_score()
                    .partial_cmp(&b.priority_score())
                    .unwrap_or(std::cmp::Ordering::Equal)
            });
        }

        self.log_background_event(&format!("Scheduled background inference task: {}", task_id));
        Ok(())
    }

    /// Execute background inference
    pub fn execute_background_inference(
        &self,
        task_id: &str,
        input: &Tensor,
    ) -> Result<BackgroundInferenceResult> {
        let start_time = Instant::now();

        // Check if we're in background mode
        let is_background = {
            let state = self.background_state.lock().expect("Operation failed");
            *state == BackgroundState::Background
        };

        if !is_background {
            return Err(
                TrustformersError::InvalidState("Not in background mode".to_string()).into(),
            );
        }

        // Create background task
        let task = BackgroundTask {
            id: task_id.to_string(),
            task_type: BackgroundTaskType::Processing,
            state: BackgroundTaskState::Running,
            started_at: start_time,
            max_duration: Duration::from_secs(self.config.max_background_time),
            priority: BackgroundPriority::Normal,
        };

        // Register task
        {
            let mut active_tasks = self.active_tasks.lock().expect("Operation failed");
            active_tasks.insert(task_id.to_string(), task);
        }

        // Perform inference with background constraints
        let result = self.perform_background_inference(input)?;

        // Mark task as completed
        {
            let mut active_tasks = self.active_tasks.lock().expect("Operation failed");
            if let Some(task) = active_tasks.get_mut(task_id) {
                task.state = BackgroundTaskState::Completed;
            }
        }

        // Update statistics
        {
            let mut stats = self.stats.lock().expect("Operation failed");
            stats.total_background_inferences += 1;
            stats.total_background_time += start_time.elapsed();
            stats.successful_inferences += 1;
        }

        Ok(BackgroundInferenceResult {
            output: result,
            execution_time: start_time.elapsed(),
            memory_used_mb: self.estimate_memory_usage(),
            power_consumption: self.estimate_power_consumption(),
            task_id: task_id.to_string(),
        })
    }

    /// Handle silent notification for background processing
    pub fn handle_silent_notification(&self, user_info: HashMap<String, String>) -> Result<()> {
        if !self.config.silent_notifications {
            return Err(TrustformersError::InvalidState(
                "Silent notifications not enabled".to_string(),
            )
            .into());
        }

        // Parse notification payload
        if let Some(task_type) = user_info.get("task_type") {
            match task_type.as_str() {
                "model_update" => self.handle_background_model_update(user_info)?,
                "federated_learning" => self.handle_background_federated_learning(user_info)?,
                "inference" => self.handle_background_inference_notification(user_info)?,
                _ => {
                    self.log_background_event(&format!(
                        "Unknown silent notification type: {}",
                        task_type
                    ));
                },
            }
        }

        Ok(())
    }

    /// Handle Background App Refresh
    pub fn handle_background_app_refresh(&self) -> Result<()> {
        if !self.config.background_app_refresh {
            return Err(TrustformersError::InvalidState(
                "Background App Refresh not enabled".to_string(),
            )
            .into());
        }

        let start_time = Instant::now();

        // Perform lightweight background tasks
        if self.config.background_model_updates {
            self.check_for_model_updates()?;
        }

        // Process any pending high-priority inference tasks
        self.process_high_priority_tasks()?;

        // Update statistics
        {
            let mut stats = self.stats.lock().expect("Operation failed");
            stats.background_app_refresh_count += 1;
            stats.total_background_time += start_time.elapsed();
        }

        self.log_background_event("Background App Refresh completed");
        Ok(())
    }

    /// Start background processing
    fn start_background_processing(&self) -> Result<()> {
        // Begin background task to prevent immediate suspension
        let task_id = format!(
            "background_processing_{}",
            Instant::now().elapsed().as_millis()
        );

        let task = BackgroundTask {
            id: task_id.clone(),
            task_type: BackgroundTaskType::Processing,
            state: BackgroundTaskState::Running,
            started_at: Instant::now(),
            max_duration: Duration::from_secs(self.config.max_background_time),
            priority: self.config.background_priority,
        };

        {
            let mut active_tasks = self.active_tasks.lock().expect("Operation failed");
            active_tasks.insert(task_id, task);
        }

        // Process queued tasks
        self.process_background_queue()?;

        Ok(())
    }

    /// Process background task queue
    fn process_background_queue(&self) -> Result<()> {
        let tasks_to_process = {
            let mut queue = self.task_queue.lock().expect("Operation failed");
            let now = Instant::now();

            // Get tasks that are ready to run
            let ready_tasks: Vec<PendingTask> =
                queue.iter().filter(|task| task.scheduled_time <= now).cloned().collect();

            // Remove processed tasks from queue
            queue.retain(|task| task.scheduled_time > now);

            ready_tasks
        };

        for task in tasks_to_process {
            if self.has_available_background_time() {
                self.execute_pending_task(task)?;
            } else {
                // Re-queue task for later
                let mut queue = self.task_queue.lock().expect("Operation failed");
                queue.push(task);
                break;
            }
        }

        Ok(())
    }

    /// Execute a pending background task
    fn execute_pending_task(&self, task: PendingTask) -> Result<()> {
        match task.task_type {
            BackgroundTaskType::Processing => {
                for input in &task.input_data {
                    self.execute_background_inference(&task.id, input)?;
                }
            },
            BackgroundTaskType::ModelUpdate => {
                self.handle_background_model_update(HashMap::new())?;
            },
            BackgroundTaskType::FederatedLearning => {
                self.handle_background_federated_learning(HashMap::new())?;
            },
            _ => {
                self.log_background_event(&format!(
                    "Unsupported background task type: {:?}",
                    task.task_type
                ));
            },
        }

        Ok(())
    }

    /// Perform background inference with constraints
    fn perform_background_inference(&self, input: &Tensor) -> Result<Tensor> {
        // Apply background-specific optimizations
        let optimized_input = self.apply_background_optimizations(input)?;

        // Use power-efficient inference mode
        let result = if self.config.power_conservation {
            self.power_efficient_inference(&optimized_input)?
        } else {
            self.standard_inference(&optimized_input)?
        };

        Ok(result)
    }

    /// Apply background-specific optimizations
    fn apply_background_optimizations(&self, input: &Tensor) -> Result<Tensor> {
        // Reduce precision for background tasks
        let quantized = input.to_dtype(trustformers_core::DType::F16)?;

        // Apply additional compression if needed
        if self.config.power_conservation {
            // Further optimize for power efficiency
            Ok(quantized)
        } else {
            Ok(quantized)
        }
    }

    /// Power-efficient inference for background processing
    fn power_efficient_inference(&self, input: &Tensor) -> Result<Tensor> {
        // Use reduced model complexity for background inference
        // This would integrate with the adaptive inference engine
        Ok(input.clone()) // Placeholder
    }

    /// Standard inference
    fn standard_inference(&self, input: &Tensor) -> Result<Tensor> {
        // Regular inference pipeline
        Ok(input.clone()) // Placeholder
    }

    /// Check for model updates in background
    fn check_for_model_updates(&self) -> Result<()> {
        // Check if new model versions are available
        // Download updates using background URL session
        self.log_background_event("Checking for model updates");
        Ok(())
    }

    /// Process high-priority background tasks
    fn process_high_priority_tasks(&self) -> Result<()> {
        let high_priority_tasks = {
            let queue = self.task_queue.lock().expect("Operation failed");
            queue
                .iter()
                .filter(|task| {
                    task.priority == BackgroundPriority::High
                        || task.priority == BackgroundPriority::UserInitiated
                })
                .cloned()
                .collect::<Vec<_>>()
        };

        for task in high_priority_tasks {
            if self.has_available_background_time() {
                self.execute_pending_task(task)?;
            }
        }

        Ok(())
    }

    /// Handle background model update notification
    fn handle_background_model_update(&self, user_info: HashMap<String, String>) -> Result<()> {
        if !self.config.background_model_updates {
            return Ok(());
        }

        self.log_background_event("Handling background model update");

        // Start model download/update process
        // This would integrate with the model management system

        Ok(())
    }

    /// Handle background federated learning notification
    fn handle_background_federated_learning(
        &self,
        user_info: HashMap<String, String>,
    ) -> Result<()> {
        if !self.config.background_federated_learning {
            return Ok(());
        }

        self.log_background_event("Handling background federated learning");

        // Start federated learning round
        // This would integrate with the federated learning client

        Ok(())
    }

    /// Handle background inference notification
    fn handle_background_inference_notification(
        &self,
        user_info: HashMap<String, String>,
    ) -> Result<()> {
        if let Some(task_id) = user_info.get("task_id") {
            self.log_background_event(&format!(
                "Handling background inference notification for task: {}",
                task_id
            ));

            // Trigger inference task
            // This would decode the input data from the notification
        }

        Ok(())
    }

    /// Enable power conservation mode
    fn enable_power_conservation_mode(&self) -> Result<()> {
        // Reduce CPU/GPU usage
        // Lower inference quality
        // Disable non-essential features
        self.log_background_event("Power conservation mode enabled");
        Ok(())
    }

    /// Disable power conservation mode
    fn disable_power_conservation_mode(&self) -> Result<()> {
        // Restore full performance
        self.log_background_event("Power conservation mode disabled");
        Ok(())
    }

    /// Finalize background tasks when returning to foreground
    fn finalize_background_tasks(&self) -> Result<()> {
        let mut completed_tasks = Vec::new();

        {
            let mut active_tasks = self.active_tasks.lock().expect("Operation failed");
            for (task_id, task) in active_tasks.iter_mut() {
                if task.state == BackgroundTaskState::Running {
                    task.state = BackgroundTaskState::Completed;
                    completed_tasks.push(task_id.clone());
                }
            }
        }

        for task_id in completed_tasks {
            self.log_background_event(&format!("Finalized background task: {}", task_id));
        }

        Ok(())
    }

    /// Check if there's available background execution time
    fn has_available_background_time(&self) -> bool {
        let active_tasks = self.active_tasks.lock().expect("Operation failed");
        let oldest_task = active_tasks
            .values()
            .filter(|task| task.state == BackgroundTaskState::Running)
            .min_by_key(|task| task.started_at);

        if let Some(task) = oldest_task {
            task.started_at.elapsed() < task.max_duration
        } else {
            true
        }
    }

    /// Estimate memory usage
    fn estimate_memory_usage(&self) -> u32 {
        // Estimate current memory usage in MB
        25 // Placeholder
    }

    /// Estimate power consumption
    fn estimate_power_consumption(&self) -> f32 {
        // Estimate power consumption in watts
        0.5 // Placeholder
    }

    /// Log background events
    fn log_background_event(&self, message: &str) {
        // In a real implementation, this would use proper logging
        println!("[iOS Background] {}", message);
    }

    /// Get background processing statistics
    pub fn get_stats(&self) -> BackgroundStats {
        self.stats.lock().expect("Operation failed").clone()
    }

    /// Get current background state
    pub fn get_background_state(&self) -> BackgroundState {
        *self.background_state.lock().expect("Operation failed")
    }

    /// Get active background tasks
    pub fn get_active_tasks(&self) -> HashMap<String, BackgroundTask> {
        self.active_tasks.lock().expect("Operation failed").clone()
    }
}

/// Background application state
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum BackgroundState {
    /// App is in foreground
    Foreground,
    /// App is in background
    Background,
    /// App is suspended
    Suspended,
}

/// Background task information
#[derive(Debug, Clone)]
pub struct BackgroundTask {
    pub id: String,
    pub task_type: BackgroundTaskType,
    pub state: BackgroundTaskState,
    pub started_at: Instant,
    pub max_duration: Duration,
    pub priority: BackgroundPriority,
}

/// Pending background task
#[derive(Debug, Clone)]
struct PendingTask {
    id: String,
    task_type: BackgroundTaskType,
    input_data: Vec<Tensor>,
    priority: BackgroundPriority,
    scheduled_time: Instant,
    max_execution_time: Duration,
    created_at: Instant,
}

impl PendingTask {
    /// Calculate priority score for sorting
    fn priority_score(&self) -> f32 {
        let priority_weight = match self.priority {
            BackgroundPriority::Low => 1.0,
            BackgroundPriority::Normal => 2.0,
            BackgroundPriority::High => 3.0,
            BackgroundPriority::UserInitiated => 4.0,
        };

        let age_factor = self.created_at.elapsed().as_secs_f32() / 3600.0; // Age in hours

        priority_weight + age_factor
    }
}

/// Background inference result
#[derive(Debug, Clone)]
pub struct BackgroundInferenceResult {
    pub output: Tensor,
    pub execution_time: Duration,
    pub memory_used_mb: u32,
    pub power_consumption: f32,
    pub task_id: String,
}

/// Background processing statistics
#[derive(Debug, Clone, Default)]
pub struct BackgroundStats {
    pub total_background_inferences: usize,
    pub successful_inferences: usize,
    pub failed_inferences: usize,
    pub cancelled_inferences: usize,
    pub total_background_time: Duration,
    pub background_app_refresh_count: usize,
    pub silent_notification_count: usize,
    pub model_updates_completed: usize,
    pub federated_learning_rounds: usize,
}

impl BackgroundStats {
    /// Get success rate of background inferences
    pub fn success_rate(&self) -> f32 {
        if self.total_background_inferences == 0 {
            0.0
        } else {
            self.successful_inferences as f32 / self.total_background_inferences as f32
        }
    }

    /// Get average background execution time
    pub fn avg_execution_time(&self) -> Duration {
        if self.total_background_inferences == 0 {
            Duration::from_millis(0)
        } else {
            self.total_background_time / self.total_background_inferences as u32
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_ios_background_config_default() {
        let config = iOSBackgroundConfig::default();
        assert!(config.background_app_refresh);
        assert!(config.background_tasks);
        assert_eq!(config.max_background_time, 30);
    }

    #[test]
    fn test_ios_background_manager_creation() {
        let background_config = iOSBackgroundConfig::default();
        let mobile_config = MobileConfig::default();
        let manager = iOSBackgroundManager::new(background_config, mobile_config);
        assert!(manager.is_ok());
    }

    #[test]
    fn test_background_stats() {
        let mut stats = BackgroundStats::default();
        stats.total_background_inferences = 100;
        stats.successful_inferences = 90;

        assert_eq!(stats.success_rate(), 0.9);
    }

    #[test]
    fn test_pending_task_priority_score() {
        let task = PendingTask {
            id: "test".to_string(),
            task_type: BackgroundTaskType::Processing,
            input_data: Vec::new(),
            priority: BackgroundPriority::High,
            scheduled_time: Instant::now(),
            max_execution_time: Duration::from_secs(30),
            created_at: Instant::now(),
        };

        assert!(task.priority_score() >= 3.0);
    }
}