//! Speculative Template Loader
//!
//! AI-predicted template prefetching for instant loads.

use std::collections::{HashMap, VecDeque};

/// Prediction engine for template access patterns
#[derive(Debug)]
pub struct PredictionEngine {
    /// Access history (template_hash -> next template hashes)
    transitions: HashMap<u64, Vec<(u64, u32)>>,
    /// Recent access sequence
    history: VecDeque<u64>,
    /// Maximum history length
    max_history: usize,
    /// Minimum confidence threshold
    confidence_threshold: f32,
}

impl PredictionEngine {
    /// Create a new prediction engine
    pub fn new() -> Self {
        Self {
            transitions: HashMap::new(),
            history: VecDeque::new(),
            max_history: 100,
            confidence_threshold: 0.3,
        }
    }

    /// Record a template access
    pub fn record_access(&mut self, template_hash: u64) {
        // Update transitions from previous template
        if let Some(&prev) = self.history.back() {
            let transitions = self.transitions.entry(prev).or_default();

            if let Some((_, count)) = transitions.iter_mut().find(|(h, _)| *h == template_hash) {
                *count += 1;
            } else {
                transitions.push((template_hash, 1));
            }
        }

        // Add to history
        self.history.push_back(template_hash);
        if self.history.len() > self.max_history {
            self.history.pop_front();
        }
    }

    /// Predict next templates to prefetch
    pub fn predict(&self, current_template: u64, max_predictions: usize) -> Vec<u64> {
        let transitions = match self.transitions.get(&current_template) {
            Some(t) => t,
            None => return Vec::new(),
        };

        let total: u32 = transitions.iter().map(|(_, c)| c).sum();
        if total == 0 {
            return Vec::new();
        }

        // Sort by count and filter by confidence
        let mut predictions: Vec<_> = transitions
            .iter()
            .filter(|(_, count)| *count as f32 / total as f32 >= self.confidence_threshold)
            .copied()
            .collect();

        predictions.sort_by(|a, b| b.1.cmp(&a.1));

        predictions
            .into_iter()
            .take(max_predictions)
            .map(|(hash, _)| hash)
            .collect()
    }

    /// Get confidence for a specific transition
    pub fn confidence(&self, from: u64, to: u64) -> f32 {
        let transitions = match self.transitions.get(&from) {
            Some(t) => t,
            None => return 0.0,
        };

        let total: u32 = transitions.iter().map(|(_, c)| c).sum();
        if total == 0 {
            return 0.0;
        }

        transitions
            .iter()
            .find(|(h, _)| *h == to)
            .map(|(_, count)| *count as f32 / total as f32)
            .unwrap_or(0.0)
    }

    /// Clear prediction data
    pub fn clear(&mut self) {
        self.transitions.clear();
        self.history.clear();
    }
}

impl Default for PredictionEngine {
    fn default() -> Self {
        Self::new()
    }
}

/// Speculative loader for prefetching templates
#[derive(Debug)]
pub struct SpeculativeLoader {
    /// Prediction engine
    prediction: PredictionEngine,
    /// Prefetch queue
    prefetch_queue: VecDeque<u64>,
    /// Maximum prefetch queue size
    max_prefetch: usize,
    /// Templates currently being prefetched
    in_flight: Vec<u64>,
}

impl SpeculativeLoader {
    /// Create a new speculative loader
    pub fn new() -> Self {
        Self {
            prediction: PredictionEngine::new(),
            prefetch_queue: VecDeque::new(),
            max_prefetch: 3,
            in_flight: Vec::new(),
        }
    }

    /// Record template access and trigger prefetch
    pub fn on_access(&mut self, template_hash: u64) {
        self.prediction.record_access(template_hash);

        // Get predictions and queue for prefetch
        let predictions = self.prediction.predict(template_hash, self.max_prefetch);

        for pred in predictions {
            if !self.prefetch_queue.contains(&pred) && !self.in_flight.contains(&pred) {
                self.prefetch_queue.push_back(pred);
            }
        }

        // Limit queue size
        while self.prefetch_queue.len() > self.max_prefetch * 2 {
            self.prefetch_queue.pop_front();
        }
    }

    /// Get next template to prefetch
    pub fn next_prefetch(&mut self) -> Option<u64> {
        let hash = self.prefetch_queue.pop_front()?;
        self.in_flight.push(hash);
        Some(hash)
    }

    /// Mark prefetch as complete
    pub fn prefetch_complete(&mut self, template_hash: u64) {
        self.in_flight.retain(|&h| h != template_hash);
    }

    /// Get pending prefetch count
    pub fn pending_count(&self) -> usize {
        self.prefetch_queue.len() + self.in_flight.len()
    }

    /// Get prediction accuracy estimate
    pub fn accuracy(&self) -> f32 {
        // This would need actual hit/miss tracking
        // Placeholder implementation
        0.75
    }
}

impl Default for SpeculativeLoader {
    fn default() -> Self {
        Self::new()
    }
}

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

    #[test]
    fn test_prediction() {
        let mut engine = PredictionEngine::new();

        // Create pattern: 1 -> 2 -> 3 -> 1 -> 2 -> 3
        for _ in 0..10 {
            engine.record_access(1);
            engine.record_access(2);
            engine.record_access(3);
        }

        // Should predict 2 after 1
        let predictions = engine.predict(1, 1);
        assert_eq!(predictions, vec![2]);

        // Should predict 3 after 2
        let predictions = engine.predict(2, 1);
        assert_eq!(predictions, vec![3]);
    }

    #[test]
    fn test_speculative_loader() {
        let mut loader = SpeculativeLoader::new();

        // Create access pattern
        for _ in 0..5 {
            loader.on_access(1);
            loader.on_access(2);
        }

        // After accessing 1, should queue 2 for prefetch
        loader.on_access(1);
        assert!(loader.pending_count() > 0);
    }
}
