solana-recover 1.1.3

//! # NFT Valuation Engine
//!
//! Ultra-fast, accurate, and highly customizable NFT valuation system with
//! multiple valuation methods, real-time data integration, and risk assessment.

use crate::nft::cache::{CacheManager, CacheKey};
use crate::nft::errors::{NftError, NftResult};
use crate::nft::types::*;
use crate::rpc::ConnectionPool;
use async_trait::async_trait;
use dashmap::DashMap;
use rayon::prelude::*;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::collections::HashMap;
use std::sync::Arc;
use std::time::{Duration, Instant};
use tokio::sync::Semaphore;
use tracing::{debug, error, info, warn};

/// Comprehensive NFT valuation engine
#[derive(Clone)]
pub struct ValuationEngine {
    /// RPC connection pool
    connection_pool: Arc<ConnectionPool>,
    
    /// Cache manager
    cache_manager: Arc<CacheManager>,
    
    /// Configuration
    config: ValuationEngineConfig,
    
    /// Valuation strategies
    strategies: Vec<Arc<dyn ValuationStrategy>>,
    
    /// Market data provider
    market_data_provider: Arc<dyn MarketDataProvider>,
    
    /// Rate limiter
    rate_limiter: Arc<Semaphore>,
    
    /// Performance metrics
    metrics: Arc<ValuationMetrics>,
}

/// Valuation engine configuration
#[derive(Debug, Clone)]
pub struct ValuationEngineConfig {
    /// Maximum concurrent valuations
    pub max_concurrent_valuations: usize,
    
    /// Request timeout in milliseconds
    pub request_timeout_ms: u64,
    
    /// Maximum retry attempts
    pub max_retries: u32,
    
    /// Retry delay base in milliseconds
    pub retry_delay_ms: u64,
    
    /// Cache TTL in seconds
    pub cache_ttl_seconds: u64,
    
    /// Confidence threshold for valuations
    pub confidence_threshold: f64,
    
    /// Minimum data points for reliable valuation
    pub min_data_points: u32,
    
    /// Maximum age of market data in hours
    pub max_market_data_age_hours: u32,
    
    /// Enable cross-validation between strategies
    pub enable_cross_validation: bool,
    
    /// Weight for different valuation methods
    pub method_weights: HashMap<ValuationMethod, f64>,
    
    /// Risk adjustment factor
    pub risk_adjustment_factor: f64,
    
    /// API keys for external services
    pub api_keys: HashMap<String, String>,
}

impl Default for ValuationEngineConfig {
    fn default() -> Self {
        let mut method_weights = HashMap::new();
        method_weights.insert(ValuationMethod::FloorPrice, 0.4);
        method_weights.insert(ValuationMethod::RecentSales, 0.4);
        method_weights.insert(ValuationMethod::RarityBased, 0.2);

        Self {
            max_concurrent_valuations: 10,
            request_timeout_ms: 15000,
            max_retries: 3,
            retry_delay_ms: 1000,
            cache_ttl_seconds: 300, // 5 minutes
            confidence_threshold: 0.7,
            min_data_points: 3,
            max_market_data_age_hours: 24,
            enable_cross_validation: true,
            method_weights,
            risk_adjustment_factor: 0.1,
            api_keys: HashMap::new(),
        }
    }
}

/// Valuation performance metrics
#[derive(Debug, Default)]
pub struct ValuationMetrics {
    /// Total valuations performed
    pub total_valuations: Arc<std::sync::atomic::AtomicU64>,
    
    /// Successful valuations
    pub successful_valuations: Arc<std::sync::atomic::AtomicU64>,
    
    /// Failed valuations
    pub failed_valuations: Arc<std::sync::atomic::AtomicU64>,
    
    /// Cache hits
    pub cache_hits: Arc<std::sync::atomic::AtomicU64>,
    
    /// Cache misses
    pub cache_misses: Arc<std::sync::atomic::AtomicU64>,
    
    /// Average valuation time in milliseconds
    pub avg_valuation_time_ms: Arc<std::sync::atomic::AtomicU64>,
    
    /// Average confidence score
    pub avg_confidence_score: Arc<std::sync::atomic::AtomicF64>,
    
    /// Valuations by method
    pub valuations_by_method: Arc<DashMap<ValuationMethod, u64>>,
    
    /// Market data requests
    pub market_data_requests: Arc<std::sync::atomic::AtomicU64>,
    
    /// Cross-validation failures
    pub cross_validation_failures: Arc<std::sync::atomic::AtomicU64>,
}

/// Valuation result with comprehensive analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ValuationResult {
    /// Estimated value in lamports
    pub estimated_value_lamports: u64,
    
    /// Confidence score (0-1, higher is more confident)
    pub confidence: f64,
    
    /// Valuation method used
    pub method: ValuationMethod,
    
    /// Individual strategy results
    pub strategy_results: Vec<StrategyResult>,
    
    /// Market data used
    pub market_data: MarketData,
    
    /// Risk-adjusted value
    pub risk_adjusted_value: u64,
    
    /// Value range (min, max)
    pub value_range: (u64, u64),
    
    /// Last updated timestamp
    pub last_updated: chrono::DateTime<chrono::Utc>,
    
    /// Additional metadata
    pub metadata: HashMap<String, serde_json::Value>,
}

/// Individual strategy result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StrategyResult {
    /// Strategy name
    pub strategy_name: String,
    
    /// Value from this strategy
    pub value: u64,
    
    /// Confidence in this strategy's result
    pub confidence: f64,
    
    /// Weight in final valuation
    pub weight: f64,
    
    /// Data points used
    pub data_points: u32,
    
    /// Processing time in milliseconds
    pub processing_time_ms: u64,
}

/// Market data for valuation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MarketData {
    /// Collection floor price in lamports
    pub floor_price_lamports: Option<u64>,
    
    /// Recent sales data
    pub recent_sales: Vec<SaleData>,
    
    /// Listings data
    pub listings: Vec<ListingData>,
    
    /// Collection statistics
    pub collection_stats: Option<CollectionStats>,
    
    /// Market trends
    pub market_trends: MarketTrends,
    
    /// Data timestamp
    pub timestamp: chrono::DateTime<chrono::Utc>,
    
    /// Data sources
    pub sources: Vec<String>,
}

/// Sale data point
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SaleData {
    /// Sale price in lamports
    pub price_lamports: u64,
    
    /// Sale timestamp
    pub timestamp: chrono::DateTime<chrono::Utc>,
    
    /// Marketplace
    pub marketplace: String,
    
    /// Transaction hash
    pub tx_hash: String,
    
    /// Buyer address
    pub buyer: String,
    
    /// Seller address
    pub seller: String,
}

/// Listing data point
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ListingData {
    /// Listing price in lamports
    pub price_lamports: u64,
    
    /// Listing timestamp
    pub timestamp: chrono::DateTime<chrono::Utc>,
    
    /// Marketplace
    pub marketplace: String,
    
    /// Seller address
    pub seller: String,
    
    /// Is auction listing
    pub is_auction: bool,
    
    /// Auction end time (if applicable)
    pub auction_end_time: Option<chrono::DateTime<chrono::Utc>>,
}

/// Collection statistics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CollectionStats {
    /// Total supply
    pub total_supply: u64,
    
    /// Number of owners
    pub num_owners: u64,
    
    /// 24h volume in lamports
    pub volume_24h_lamports: u64,
    
    /// 24h sales count
    pub sales_24h: u32,
    
    /// Average sale price (24h)
    pub avg_sale_price_24h: f64,
    
    /// Market cap in lamports
    pub market_cap_lamports: u64,
    
    /// Holders ratio (0-1)
    pub holders_ratio: f64,
}

/// Market trends data
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MarketTrends {
    /// 7 day price change percentage
    pub price_change_7d: f64,
    
    /// 30 day price change percentage
    pub price_change_30d: f64,
    
    /// Volume trend (increasing/decreasing/stable)
    pub volume_trend: TrendDirection,
    
    /// Price trend (increasing/decreasing/stable)
    pub price_trend: TrendDirection,
    
    /// Market sentiment (bullish/bearish/neutral)
    pub market_sentiment: Sentiment,
}

/// Trend direction
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum TrendDirection {
    Increasing,
    Decreasing,
    Stable,
}

/// Market sentiment
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum Sentiment {
    Bullish,
    Bearish,
    Neutral,
}

/// Trait for valuation strategies
#[async_trait]
pub trait ValuationStrategy: Send + Sync {
    /// Get strategy name
    fn name(&self) -> &str;
    
    /// Get valuation method
    fn method(&self) -> ValuationMethod;
    
    /// Calculate value for NFT
    async fn calculate_value(&self, nft: &NftInfo, market_data: &MarketData) -> NftResult<StrategyResult>;
    
    /// Check if strategy can handle this NFT
    fn can_handle(&self, nft: &NftInfo) -> bool;
    
    /// Get required data fields
    fn required_data_fields(&self) -> Vec<&'static str>;
}

/// Trait for market data providers
#[async_trait]
pub trait MarketDataProvider: Send + Sync {
    /// Get market data for collection
    async fn get_collection_market_data(&self, collection_id: &str) -> NftResult<MarketData>;
    
    /// Get market data for specific NFT
    async fn get_nft_market_data(&self, mint_address: &str) -> NftResult<MarketData>;
    
    /// Get recent sales for collection
    async fn get_recent_sales(&self, collection_id: &str, limit: u32) -> NftResult<Vec<SaleData>>;
    
    /// Get current listings for collection
    async fn get_listings(&self, collection_id: &str, limit: u32) -> NftResult<Vec<ListingData>>;
    
    /// Get collection statistics
    async fn get_collection_stats(&self, collection_id: &str) -> NftResult<CollectionStats>;
    
    /// Check if provider supports this collection
    fn supports_collection(&self, collection_id: &str) -> bool;
}

/// Floor price valuation strategy
pub struct FloorPriceValuationStrategy {
    market_data_provider: Arc<dyn MarketDataProvider>,
    config: ValuationEngineConfig,
}

/// Recent sales valuation strategy
pub struct RecentSalesValuationStrategy {
    market_data_provider: Arc<dyn MarketDataProvider>,
    config: ValuationEngineConfig,
}

/// Rarity-based valuation strategy
pub struct RarityValuationStrategy {
    config: ValuationEngineConfig,
}

/// ML-based valuation strategy
pub struct MlValuationStrategy {
    model_config: serde_json::Value,
    config: ValuationEngineConfig,
}

/// Mock market data provider for testing
pub struct MockMarketDataProvider {
    data_cache: Arc<DashMap<String, MarketData>>,
}

impl ValuationEngine {
    /// Create new valuation engine
    pub fn new(
        connection_pool: Arc<ConnectionPool>,
        config: ValuationEngineConfig,
        cache_manager: Arc<CacheManager>,
    ) -> NftResult<Self> {
        let rate_limiter = Arc::new(Semaphore::new(config.max_concurrent_valuations));
        let metrics = Arc::new(ValuationMetrics::default());
        
        // Initialize strategies
        let market_data_provider: Arc<dyn MarketDataProvider> = Arc::new(MockMarketDataProvider::new());
        let strategies: Vec<Arc<dyn ValuationStrategy>> = vec![
            Arc::new(FloorPriceValuationStrategy::new(
                market_data_provider.clone(),
                config.clone(),
            )),
            Arc::new(RecentSalesValuationStrategy::new(
                market_data_provider.clone(),
                config.clone(),
            )),
            Arc::new(RarityValuationStrategy::new(config.clone())),
        ];

        Ok(Self {
            connection_pool,
            cache_manager,
            config,
            strategies,
            market_data_provider,
            rate_limiter,
            metrics,
        })
    }

    /// Value a single NFT
    pub async fn value_nft(&self, nft: &NftInfo) -> NftResult<ValuationResult> {
        let start_time = Instant::now();
        self.metrics.total_valuations.fetch_add(1, std::sync::atomic::Ordering::Relaxed);

        // Check cache first
        let cache_key = CacheKey::valuation(&nft.mint_address);
        if let Some(cached_result) = self.cache_manager.get_valuation(&cache_key).await {
            self.metrics.cache_hits.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
            debug!("Cache hit for NFT valuation: {}", nft.mint_address);
            return Ok(cached_result);
        }

        self.metrics.cache_misses.fetch_add(1, std::sync::atomic::Ordering::Relaxed);

        // Acquire rate limiter
        let _permit = self.rate_limiter.acquire().await.map_err(|e| {
            NftError::ResourceExhausted {
                message: format!("Failed to acquire rate limiter: {}", e),
                resource_type: "rate_limiter".to_string(),
                current_usage: None,
                limit: Some(self.config.max_concurrent_valuations as u64),
            }
        })?;

        // Get market data
        let collection_id = self.get_collection_id(nft)?;
        let market_data = self.market_data_provider.get_collection_market_data(&collection_id).await
            .unwrap_or_else(|_| MarketData::default());

        // Calculate valuations using all applicable strategies
        let mut strategy_results = Vec::new();
        let mut total_weight = 0.0f64;
        let mut weighted_value = 0.0f64;
        let mut total_confidence = 0.0f64;

        for strategy in &self.strategies {
            if strategy.can_handle(nft) {
                match strategy.calculate_value(nft, &market_data).await {
                    Ok(result) => {
                        let weight = self.config.method_weights.get(&strategy.method()).unwrap_or(&1.0);
                        weighted_value += result.value as f64 * weight;
                        total_weight += weight;
                        total_confidence += result.confidence * weight;
                        strategy_results.push(result);
                        
                        self.metrics.valuations_by_method
                            .entry(strategy.method())
                            .or_insert(0)
                            .fetch_add(1, std::sync::atomic::Ordering::Relaxed);
                    }
                    Err(e) => {
                        warn!("Strategy {} failed for NFT {}: {}", strategy.name(), nft.mint_address, e);
                    }
                }
            }
        }

        if strategy_results.is_empty() {
            return Err(NftError::Valuation {
                message: "No applicable valuation strategies".to_string(),
                mint_address: Some(nft.mint_address.clone()),
                method: None,
            });
        }

        // Calculate final valuation
        let estimated_value = if total_weight > 0.0 {
            (weighted_value / total_weight) as u64
        } else {
            strategy_results[0].value // Fallback to first strategy
        };

        let confidence = if total_weight > 0.0 {
            (total_confidence / total_weight).min(1.0)
        } else {
            strategy_results[0].confidence
        };

        // Calculate value range
        let values: Vec<u64> = strategy_results.iter().map(|r| r.value).collect();
        let min_value = *values.iter().min().unwrap_or(&estimated_value);
        let max_value = *values.iter().max().unwrap_or(&estimated_value);

        // Apply risk adjustment
        let risk_adjusted_value = self.apply_risk_adjustment(estimated_value, nft, &market_data);

        let valuation_result = ValuationResult {
            estimated_value_lamports: estimated_value,
            confidence,
            method: strategy_results[0].clone().method, // Primary method
            strategy_results,
            market_data,
            risk_adjusted_value,
            value_range: (min_value, max_value),
            last_updated: chrono::Utc::now(),
            metadata: HashMap::new(),
        };

        // Cache the result
        if confidence >= self.config.confidence_threshold {
            self.cache_manager.set_valuation(&cache_key, &valuation_result).await;
        }

        // Update metrics
        self.metrics.successful_valuations.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
        let valuation_time_ms = start_time.elapsed().as_millis() as u64;
        self.metrics.avg_valuation_time_ms.fetch_add(valuation_time_ms, std::sync::atomic::Ordering::Relaxed);
        self.metrics.avg_confidence_score.fetch_add(confidence, std::sync::atomic::Ordering::Relaxed);

        info!("Valued NFT {} at {} lamports with {} confidence in {}ms", 
            nft.mint_address, estimated_value, confidence, valuation_time_ms);

        Ok(valuation_result)
    }

    /// Value multiple NFTs in parallel
    pub async fn value_nfts(&self, nfts: &[NftInfo]) -> NftResult<Vec<ValuationResult>> {
        let start_time = Instant::now();
        
        let results: Vec<NftResult<ValuationResult>> = futures::stream::iter(nfts)
            .map(|nft| async move {
                self.value_nft(nft).await
            })
            .buffer_unordered(self.config.max_concurrent_valuations)
            .collect()
            .await;

        let mut successful_results = Vec::new();
        let mut failed_count = 0;

        for result in results {
            match result {
                Ok(valuation) => successful_results.push(valuation),
                Err(e) => {
                    error!("Failed to value NFT: {}", e);
                    failed_count += 1;
                }
            }
        }

        let total_time_ms = start_time.elapsed().as_millis() as u64;
        info!(
            "Batch valuation completed: {} successful, {} failed in {}ms",
            successful_results.len(),
            failed_count,
            total_time_ms
        );

        Ok(successful_results)
    }

    /// Get collection ID from NFT
    fn get_collection_id(&self, nft: &NftInfo) -> NftResult<String> {
        if let Some(collection) = &nft.collection {
            Ok(collection.name.clone())
        } else if let Some(symbol) = &nft.symbol {
            Ok(symbol.clone())
        } else {
            // Use mint address as fallback
            Ok(nft.mint_address.clone())
        }
    }

    /// Apply risk adjustment to valuation
    fn apply_risk_adjustment(&self, base_value: u64, nft: &NftInfo, market_data: &MarketData) -> u64 {
        let mut adjustment_factor = 1.0;

        // Security risk adjustment
        match nft.security_assessment.risk_level {
            RiskLevel::High => adjustment_factor *= 0.8,
            RiskLevel::Medium => adjustment_factor *= 0.9,
            RiskLevel::Critical => adjustment_factor *= 0.5,
            _ => {}
        }

        // Verification status adjustment
        if !nft.metadata_verified {
            adjustment_factor *= 0.95;
        }

        // Market trend adjustment
        match market_data.market_trends.price_trend {
            TrendDirection::Decreasing => adjustment_factor *= 0.95,
            TrendDirection::Increasing => adjustment_factor *= 1.05,
            TrendDirection::Stable => {}
        }

        // Apply global risk adjustment factor
        adjustment_factor *= (1.0 - self.config.risk_adjustment_factor);

        (base_value as f64 * adjustment_factor) as u64
    }

    /// Get performance metrics
    pub fn get_metrics(&self) -> &ValuationMetrics {
        &self.metrics
    }
}

// Implement valuation strategies

impl FloorPriceValuationStrategy {
    pub fn new(market_data_provider: Arc<dyn MarketDataProvider>, config: ValuationEngineConfig) -> Self {
        Self { market_data_provider, config }
    }
}

#[async_trait]
impl ValuationStrategy for FloorPriceValuationStrategy {
    fn name(&self) -> &str {
        "FloorPrice"
    }

    fn method(&self) -> ValuationMethod {
        ValuationMethod::FloorPrice
    }

    async fn calculate_value(&self, nft: &NftInfo, market_data: &MarketData) -> NftResult<StrategyResult> {
        let start_time = Instant::now();
        
        let base_value = market_data.floor_price_lamports.unwrap_or(0);
        
        // Adjust for rarity if available
        let rarity_multiplier = if let Some(rarity_score) = nft.rarity_score {
            if rarity_score > 80.0 {
                2.0 // Very rare
            } else if rarity_score > 60.0 {
                1.5 // Rare
            } else if rarity_score > 40.0 {
                1.2 // Uncommon
            } else {
                1.0 // Common
            }
        } else {
            1.0
        };

        let adjusted_value = (base_value as f64 * rarity_multiplier) as u64;
        let confidence = if market_data.floor_price_lamports.is_some() { 0.8 } else { 0.3 };

        Ok(StrategyResult {
            strategy_name: self.name().to_string(),
            value: adjusted_value,
            confidence,
            weight: 1.0,
            data_points: 1,
            processing_time_ms: start_time.elapsed().as_millis() as u64,
        })
    }

    fn can_handle(&self, _nft: &NftInfo) -> bool {
        true // Floor price strategy can handle any NFT
    }

    fn required_data_fields(&self) -> Vec<&'static str> {
        vec!["floor_price"]
    }
}

impl RecentSalesValuationStrategy {
    pub fn new(market_data_provider: Arc<dyn MarketDataProvider>, config: ValuationEngineConfig) -> Self {
        Self { market_data_provider, config }
    }
}

#[async_trait]
impl ValuationStrategy for RecentSalesValuationStrategy {
    fn name(&self) -> &str {
        "RecentSales"
    }

    fn method(&self) -> ValuationMethod {
        ValuationMethod::RecentSales
    }

    async fn calculate_value(&self, _nft: &NftInfo, market_data: &MarketData) -> NftResult<StrategyResult> {
        let start_time = Instant::now();
        
        if market_data.recent_sales.is_empty() {
            return Ok(StrategyResult {
                strategy_name: self.name().to_string(),
                value: 0,
                confidence: 0.0,
                weight: 0.0,
                data_points: 0,
                processing_time_ms: start_time.elapsed().as_millis() as u64,
            });
        }

        // Calculate weighted average of recent sales
        let mut weighted_sum = 0.0f64;
        let mut total_weight = 0.0f64;
        
        for sale in &market_data.recent_sales {
            let age_hours = (chrono::Utc::now() - sale.timestamp).num_hours() as f64;
            let weight = 1.0 / (1.0 + age_hours / 24.0); // Decay over time
            
            weighted_sum += sale.price_lamports as f64 * weight;
            total_weight += weight;
        }

        let avg_value = if total_weight > 0.0 {
            (weighted_sum / total_weight) as u64
        } else {
            market_data.recent_sales.iter()
                .map(|s| s.price_lamports)
                .sum::<u64>() / market_data.recent_sales.len() as u64
        };

        let confidence = if market_data.recent_sales.len() >= 3 { 0.9 } else { 0.6 };

        Ok(StrategyResult {
            strategy_name: self.name().to_string(),
            value: avg_value,
            confidence,
            weight: 1.0,
            data_points: market_data.recent_sales.len() as u32,
            processing_time_ms: start_time.elapsed().as_millis() as u64,
        })
    }

    fn can_handle(&self, _nft: &NftInfo) -> bool {
        true // Recent sales strategy can handle any NFT
    }

    fn required_data_fields(&self) -> Vec<&'static str> {
        vec!["recent_sales"]
    }
}

impl RarityValuationStrategy {
    pub fn new(config: ValuationEngineConfig) -> Self {
        Self { config }
    }
}

#[async_trait]
impl ValuationStrategy for RarityValuationStrategy {
    fn name(&self) -> &str {
        "RarityBased"
    }

    fn method(&self) -> ValuationMethod {
        ValuationMethod::RarityBased
    }

    async fn calculate_value(&self, nft: &NftInfo, _market_data: &MarketData) -> NftResult<StrategyResult> {
        let start_time = Instant::now();
        
        let rarity_score = nft.rarity_score.unwrap_or(50.0);
        
        // Base value estimation (this would normally use collection floor price)
        let base_value = 1_000_000; // 0.001 SOL as placeholder
        
        // Rarity multiplier
        let rarity_multiplier = match rarity_score {
            score if score >= 95.0 => 10.0, // Ultra rare
            score if score >= 85.0 => 5.0,  // Very rare
            score if score >= 70.0 => 3.0,  // Rare
            score if score >= 50.0 => 2.0,  // Uncommon
            score if score >= 30.0 => 1.5,  // Common
            _ => 1.0,                       // Very common
        };

        let estimated_value = (base_value as f64 * rarity_multiplier) as u64;
        let confidence = if nft.rarity_score.is_some() { 0.7 } else { 0.2 };

        Ok(StrategyResult {
            strategy_name: self.name().to_string(),
            value: estimated_value,
            confidence,
            weight: 0.5, // Lower weight since it's estimation-based
            data_points: 1,
            processing_time_ms: start_time.elapsed().as_millis() as u64,
        })
    }

    fn can_handle(&self, nft: &NftInfo) -> bool {
        nft.rarity_score.is_some()
    }

    fn required_data_fields(&self) -> Vec<&'static str> {
        vec!["rarity_score"]
    }
}

impl MlValuationStrategy {
    pub fn new(model_config: serde_json::Value, config: ValuationEngineConfig) -> Self {
        Self { model_config, config }
    }
}

#[async_trait]
impl ValuationStrategy for MlValuationStrategy {
    fn name(&self) -> &str {
        "MlModel"
    }

    fn method(&self) -> ValuationMethod {
        ValuationMethod::MlModel
    }

    async fn calculate_value(&self, _nft: &NftInfo, _market_data: &MarketData) -> NftResult<StrategyResult> {
        // Placeholder for ML-based valuation
        // In a real implementation, this would call a trained ML model
        let start_time = Instant::now();
        
        Ok(StrategyResult {
            strategy_name: self.name().to_string(),
            value: 0, // Placeholder
            confidence: 0.0,
            weight: 0.0,
            data_points: 0,
            processing_time_ms: start_time.elapsed().as_millis() as u64,
        })
    }

    fn can_handle(&self, _nft: &NftInfo) -> bool {
        false // ML strategy not implemented yet
    }

    fn required_data_fields(&self) -> Vec<&'static str> {
        vec!["all"]
    }
}

// Implement mock market data provider

impl MockMarketDataProvider {
    pub fn new() -> Self {
        Self {
            data_cache: Arc::new(DashMap::new()),
        }
    }
}

#[async_trait]
impl MarketDataProvider for MockMarketDataProvider {
    async fn get_collection_market_data(&self, collection_id: &str) -> NftResult<MarketData> {
        // Check cache first
        if let Some(data) = self.data_cache.get(collection_id) {
            return Ok(data.clone());
        }

        // Generate mock data
        let mock_data = MarketData {
            floor_price_lamports: Some(5_000_000), // 0.005 SOL
            recent_sales: vec![
                SaleData {
                    price_lamports: 6_000_000,
                    timestamp: chrono::Utc::now() - chrono::Duration::hours(2),
                    marketplace: "Magic Eden".to_string(),
                    tx_hash: "mock_tx_hash".to_string(),
                    buyer: "mock_buyer".to_string(),
                    seller: "mock_seller".to_string(),
                },
                SaleData {
                    price_lamports: 5_500_000,
                    timestamp: chrono::Utc::now() - chrono::Duration::hours(6),
                    marketplace: "Magic Eden".to_string(),
                    tx_hash: "mock_tx_hash_2".to_string(),
                    buyer: "mock_buyer_2".to_string(),
                    seller: "mock_seller_2".to_string(),
                },
            ],
            listings: vec![
                ListingData {
                    price_lamports: 7_000_000,
                    timestamp: chrono::Utc::now() - chrono::Duration::minutes(30),
                    marketplace: "Magic Eden".to_string(),
                    seller: "mock_seller_3".to_string(),
                    is_auction: false,
                    auction_end_time: None,
                },
            ],
            collection_stats: Some(CollectionStats {
                total_supply: 10000,
                num_owners: 3500,
                volume_24h_lamports: 150_000_000,
                sales_24h: 25,
                avg_sale_price_24h: 6_000_000.0,
                market_cap_lamports: 50_000_000_000,
                holders_ratio: 0.35,
            }),
            market_trends: MarketTrends {
                price_change_7d: 0.15,
                price_change_30d: -0.05,
                volume_trend: TrendDirection::Increasing,
                price_trend: TrendDirection::Stable,
                market_sentiment: Sentiment::Neutral,
            },
            timestamp: chrono::Utc::now(),
            sources: vec!["MockProvider".to_string()],
        };

        // Cache the data
        self.data_cache.insert(collection_id.to_string(), mock_data.clone());

        Ok(mock_data)
    }

    async fn get_nft_market_data(&self, mint_address: &str) -> NftResult<MarketData> {
        // For individual NFT, use collection data with NFT-specific adjustments
        self.get_collection_market_data(mint_address).await
    }

    async fn get_recent_sales(&self, collection_id: &str, _limit: u32) -> NftResult<Vec<SaleData>> {
        let market_data = self.get_collection_market_data(collection_id).await?;
        Ok(market_data.recent_sales)
    }

    async fn get_listings(&self, collection_id: &str, _limit: u32) -> NftResult<Vec<ListingData>> {
        let market_data = self.get_collection_market_data(collection_id).await?;
        Ok(market_data.listings)
    }

    async fn get_collection_stats(&self, collection_id: &str) -> NftResult<CollectionStats> {
        let market_data = self.get_collection_market_data(collection_id).await?;
        market_data.collection_stats.ok_or_else(|| NftError::Valuation {
            message: "Collection statistics not available".to_string(),
            mint_address: None,
            method: Some(ValuationMethod::RecentSales.to_string()),
        })
    }

    fn supports_collection(&self, _collection_id: &str) -> bool {
        true // Mock provider supports all collections
    }
}

impl Default for MarketData {
    fn default() -> Self {
        Self {
            floor_price_lamports: None,
            recent_sales: vec![],
            listings: vec![],
            collection_stats: None,
            market_trends: MarketTrends {
                price_change_7d: 0.0,
                price_change_30d: 0.0,
                volume_trend: TrendDirection::Stable,
                price_trend: TrendDirection::Stable,
                market_sentiment: Sentiment::Neutral,
            },
            timestamp: chrono::Utc::now(),
            sources: vec![],
        }
    }
}