rrag 0.1.0-alpha.2

//! # Evaluation Benchmarks
//!
//! Standard benchmarks and datasets for RAG system evaluation.

use super::{
    EvaluationData, EvaluationMetadata, EvaluationResult, EvaluationSummary, Evaluator,
    EvaluatorConfig, EvaluatorPerformance, GroundTruth, PerformanceStats, SystemResponse,
    TestQuery,
};
use crate::RragResult;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;

/// Benchmark evaluator
pub struct BenchmarkEvaluator {
    benchmarks: Vec<Box<dyn Benchmark>>,
}

/// Trait for evaluation benchmarks
pub trait Benchmark: Send + Sync {
    /// Benchmark name
    fn name(&self) -> &str;

    /// Generate test queries and ground truth
    fn generate_test_data(&self) -> RragResult<EvaluationData>;

    /// Evaluate system against this benchmark
    fn evaluate_benchmark(
        &self,
        system_responses: &[SystemResponse],
    ) -> RragResult<BenchmarkResult>;

    /// Get benchmark configuration
    fn get_config(&self) -> BenchmarkConfig;
}

/// Configuration for benchmarks
#[derive(Debug, Clone)]
pub struct BenchmarkConfig {
    /// Benchmark name
    pub name: String,

    /// Number of test queries
    pub num_queries: usize,

    /// Difficulty level
    pub difficulty: DifficultyLevel,

    /// Domain focus
    pub domain: BenchmarkDomain,

    /// Evaluation metrics
    pub metrics: Vec<String>,
}

/// Difficulty levels for benchmarks
#[derive(Debug, Clone)]
pub enum DifficultyLevel {
    Easy,
    Medium,
    Hard,
    Expert,
}

/// Benchmark domains
#[derive(Debug, Clone)]
pub enum BenchmarkDomain {
    General,
    Science,
    Technology,
    History,
    Literature,
    Medicine,
    Law,
    Finance,
    Education,
    News,
}

/// Result from benchmark evaluation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BenchmarkResult {
    /// Benchmark name
    pub benchmark_name: String,

    /// Overall score
    pub overall_score: f32,

    /// Detailed scores
    pub detailed_scores: HashMap<String, f32>,

    /// Ranking compared to baseline
    pub ranking_info: RankingInfo,

    /// Performance analysis
    pub performance_analysis: PerformanceAnalysis,

    /// Failure cases
    pub failure_cases: Vec<FailureCase>,
}

/// Ranking information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RankingInfo {
    /// Percentile ranking
    pub percentile: f32,

    /// Comparison to baseline systems
    pub baseline_comparisons: HashMap<String, f32>,

    /// Confidence interval
    pub confidence_interval: (f32, f32),
}

/// Performance analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceAnalysis {
    /// Strengths identified
    pub strengths: Vec<String>,

    /// Weaknesses identified
    pub weaknesses: Vec<String>,

    /// Performance by category
    pub category_performance: HashMap<String, f32>,

    /// Error patterns
    pub error_patterns: Vec<ErrorPattern>,
}

/// Error pattern analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ErrorPattern {
    /// Pattern description
    pub description: String,

    /// Frequency
    pub frequency: f32,

    /// Example queries
    pub example_queries: Vec<String>,

    /// Suggested improvements
    pub improvements: Vec<String>,
}

/// Failure case analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FailureCase {
    /// Query that failed
    pub query: String,

    /// Expected result
    pub expected: String,

    /// Actual result
    pub actual: String,

    /// Failure reason
    pub failure_reason: String,

    /// Severity
    pub severity: FailureSeverity,
}

/// Failure severity levels
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum FailureSeverity {
    Low,
    Medium,
    High,
    Critical,
}

impl BenchmarkEvaluator {
    /// Create new benchmark evaluator
    pub fn new() -> Self {
        let mut evaluator = Self {
            benchmarks: Vec::new(),
        };

        // Initialize standard benchmarks
        evaluator.initialize_benchmarks();

        evaluator
    }

    /// Initialize standard benchmarks
    fn initialize_benchmarks(&mut self) {
        self.benchmarks
            .push(Box::new(GeneralKnowledgeBenchmark::new()));
        self.benchmarks
            .push(Box::new(FactualAccuracyBenchmark::new()));
        self.benchmarks.push(Box::new(ReasoningBenchmark::new()));
        self.benchmarks
            .push(Box::new(DomainSpecificBenchmark::new()));
        self.benchmarks.push(Box::new(MultiHopBenchmark::new()));
        self.benchmarks
            .push(Box::new(ConversationalBenchmark::new()));
    }

    /// Run all benchmarks
    pub async fn run_all_benchmarks(&self) -> RragResult<HashMap<String, BenchmarkResult>> {
        let mut results = HashMap::new();

        for benchmark in &self.benchmarks {
            println!("Running benchmark: {}", benchmark.name());

            // Generate test data
            let test_data = benchmark.generate_test_data()?;

            // For demonstration, create mock system responses
            let system_responses = self.create_mock_responses(&test_data);

            // Evaluate benchmark
            match benchmark.evaluate_benchmark(&system_responses) {
                Ok(result) => {
                    results.insert(benchmark.name().to_string(), result);
                    println!("✅ {} completed", benchmark.name());
                }
                Err(e) => {
                    eprintln!("❌ {} failed: {}", benchmark.name(), e);
                }
            }
        }

        Ok(results)
    }

    /// Create mock system responses for demonstration
    fn create_mock_responses(&self, test_data: &EvaluationData) -> Vec<SystemResponse> {
        use super::{RetrievedDocument, SystemTiming};

        test_data
            .queries
            .iter()
            .map(|query| SystemResponse {
                query_id: query.id.clone(),
                retrieved_docs: vec![RetrievedDocument {
                    doc_id: format!("doc_{}", query.id),
                    content: format!("Relevant content for: {}", query.query),
                    score: 0.8,
                    rank: 0,
                    metadata: HashMap::new(),
                }],
                generated_answer: Some(format!("Generated answer for: {}", query.query)),
                timing: SystemTiming {
                    total_time_ms: 1000.0 + (query.id.len() as f32 * 100.0),
                    retrieval_time_ms: 600.0,
                    generation_time_ms: Some(300.0),
                    reranking_time_ms: Some(100.0),
                },
                metadata: HashMap::new(),
            })
            .collect()
    }
}

impl Evaluator for BenchmarkEvaluator {
    fn name(&self) -> &str {
        "Benchmark"
    }

    fn evaluate(&self, data: &EvaluationData) -> RragResult<EvaluationResult> {
        let start_time = std::time::Instant::now();
        let mut overall_scores = HashMap::new();
        let per_query_results = Vec::new();

        // Evaluate against each benchmark
        for benchmark in &self.benchmarks {
            match benchmark.evaluate_benchmark(&data.system_responses) {
                Ok(result) => {
                    overall_scores.insert(benchmark.name().to_string(), result.overall_score);
                }
                Err(e) => {
                    eprintln!("Warning: Benchmark {} failed: {}", benchmark.name(), e);
                }
            }
        }

        // Calculate overall benchmark score
        let overall_score = if overall_scores.is_empty() {
            0.0
        } else {
            overall_scores.values().sum::<f32>() / overall_scores.len() as f32
        };

        overall_scores.insert("overall_benchmark_score".to_string(), overall_score);

        let total_time = start_time.elapsed().as_millis() as f32;

        // Generate insights
        let insights = self.generate_insights(&overall_scores);
        let recommendations = self.generate_recommendations(&overall_scores);

        Ok(EvaluationResult {
            id: uuid::Uuid::new_v4().to_string(),
            evaluation_type: "Benchmark".to_string(),
            overall_scores: overall_scores.clone(),
            per_query_results,
            summary: EvaluationSummary {
                total_queries: data.queries.len(),
                avg_scores: overall_scores.clone(),
                std_deviations: HashMap::new(),
                performance_stats: PerformanceStats {
                    avg_eval_time_ms: total_time,
                    total_eval_time_ms: total_time,
                    peak_memory_usage_mb: 200.0,
                    throughput_qps: data.queries.len() as f32 / (total_time / 1000.0),
                },
                insights,
                recommendations,
            },
            metadata: EvaluationMetadata {
                timestamp: chrono::Utc::now(),
                evaluation_version: "1.0.0".to_string(),
                system_config: HashMap::new(),
                environment: std::env::vars().collect(),
                git_commit: None,
            },
        })
    }

    fn supported_metrics(&self) -> Vec<String> {
        self.benchmarks
            .iter()
            .map(|b| b.name().to_string())
            .collect()
    }

    fn get_config(&self) -> EvaluatorConfig {
        EvaluatorConfig {
            name: "Benchmark".to_string(),
            version: "1.0.0".to_string(),
            metrics: self.supported_metrics(),
            performance: EvaluatorPerformance {
                avg_time_per_sample_ms: 500.0,
                memory_usage_mb: 200.0,
                accuracy: 0.95,
            },
        }
    }
}

impl BenchmarkEvaluator {
    /// Generate insights based on benchmark results
    fn generate_insights(&self, scores: &HashMap<String, f32>) -> Vec<String> {
        let mut insights = Vec::new();

        // Overall performance insights
        if let Some(&overall_score) = scores.get("overall_benchmark_score") {
            if overall_score > 0.8 {
                insights.push("🏆 Excellent performance across benchmarks".to_string());
            } else if overall_score < 0.6 {
                insights.push("⚠️ Below-average performance on standard benchmarks".to_string());
            }
        }

        // Specific benchmark insights
        if let Some(&general_score) = scores.get("GeneralKnowledge") {
            if general_score < 0.6 {
                insights.push("📚 General knowledge capabilities need improvement".to_string());
            }
        }

        if let Some(&factual_score) = scores.get("FactualAccuracy") {
            if factual_score < 0.7 {
                insights.push("📊 Factual accuracy is below acceptable threshold".to_string());
            }
        }

        if let Some(&reasoning_score) = scores.get("Reasoning") {
            if reasoning_score < 0.6 {
                insights.push("🧠 Reasoning capabilities require enhancement".to_string());
            }
        }

        insights
    }

    /// Generate recommendations based on benchmark results
    fn generate_recommendations(&self, scores: &HashMap<String, f32>) -> Vec<String> {
        let mut recommendations = Vec::new();

        if let Some(&general_score) = scores.get("GeneralKnowledge") {
            if general_score < 0.6 {
                recommendations.push(
                    "📖 Expand knowledge base with diverse, high-quality sources".to_string(),
                );
                recommendations.push(
                    "🔍 Improve retrieval to find relevant background information".to_string(),
                );
            }
        }

        if let Some(&factual_score) = scores.get("FactualAccuracy") {
            if factual_score < 0.7 {
                recommendations
                    .push("✅ Implement fact-checking and verification mechanisms".to_string());
                recommendations.push("📑 Use more authoritative and recent sources".to_string());
            }
        }

        if let Some(&reasoning_score) = scores.get("Reasoning") {
            if reasoning_score < 0.6 {
                recommendations.push("🔄 Implement chain-of-thought reasoning prompts".to_string());
                recommendations.push("🧩 Add step-by-step problem decomposition".to_string());
            }
        }

        recommendations
    }
}

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

// Individual benchmark implementations
struct GeneralKnowledgeBenchmark;

impl GeneralKnowledgeBenchmark {
    fn new() -> Self {
        Self
    }
}

impl Benchmark for GeneralKnowledgeBenchmark {
    fn name(&self) -> &str {
        "GeneralKnowledge"
    }

    fn generate_test_data(&self) -> RragResult<EvaluationData> {
        let queries = vec![
            TestQuery {
                id: "gk_1".to_string(),
                query: "What is the capital of France?".to_string(),
                query_type: Some("factual".to_string()),
                metadata: HashMap::new(),
            },
            TestQuery {
                id: "gk_2".to_string(),
                query: "Who wrote Romeo and Juliet?".to_string(),
                query_type: Some("factual".to_string()),
                metadata: HashMap::new(),
            },
            TestQuery {
                id: "gk_3".to_string(),
                query: "What is photosynthesis?".to_string(),
                query_type: Some("conceptual".to_string()),
                metadata: HashMap::new(),
            },
        ];

        let ground_truth = vec![
            GroundTruth {
                query_id: "gk_1".to_string(),
                relevant_docs: vec!["france_capital".to_string()],
                expected_answer: Some("Paris".to_string()),
                relevance_judgments: HashMap::new(),
                metadata: HashMap::new(),
            },
            GroundTruth {
                query_id: "gk_2".to_string(),
                relevant_docs: vec!["shakespeare_works".to_string()],
                expected_answer: Some("William Shakespeare".to_string()),
                relevance_judgments: HashMap::new(),
                metadata: HashMap::new(),
            },
            GroundTruth {
                query_id: "gk_3".to_string(),
                relevant_docs: vec!["biology_photosynthesis".to_string()],
                expected_answer: Some(
                    "Process by which plants convert light energy into chemical energy".to_string(),
                ),
                relevance_judgments: HashMap::new(),
                metadata: HashMap::new(),
            },
        ];

        Ok(EvaluationData {
            queries,
            ground_truth,
            system_responses: Vec::new(),
            context: HashMap::new(),
        })
    }

    fn evaluate_benchmark(&self, responses: &[SystemResponse]) -> RragResult<BenchmarkResult> {
        let mut correct_answers = 0;
        let total_questions = responses.len();

        // Simplified evaluation - check if answer is present
        for response in responses {
            if let Some(answer) = &response.generated_answer {
                if !answer.trim().is_empty() {
                    correct_answers += 1;
                }
            }
        }

        let overall_score = if total_questions > 0 {
            correct_answers as f32 / total_questions as f32
        } else {
            0.0
        };

        let mut detailed_scores = HashMap::new();
        detailed_scores.insert("accuracy".to_string(), overall_score);
        detailed_scores.insert("coverage".to_string(), 1.0); // All questions attempted

        Ok(BenchmarkResult {
            benchmark_name: self.name().to_string(),
            overall_score,
            detailed_scores,
            ranking_info: RankingInfo {
                percentile: overall_score * 100.0,
                baseline_comparisons: HashMap::new(),
                confidence_interval: (overall_score - 0.1, overall_score + 0.1),
            },
            performance_analysis: PerformanceAnalysis {
                strengths: vec!["Good response generation".to_string()],
                weaknesses: if overall_score < 0.7 {
                    vec!["Factual accuracy needs improvement".to_string()]
                } else {
                    vec![]
                },
                category_performance: HashMap::new(),
                error_patterns: Vec::new(),
            },
            failure_cases: Vec::new(),
        })
    }

    fn get_config(&self) -> BenchmarkConfig {
        BenchmarkConfig {
            name: self.name().to_string(),
            num_queries: 3,
            difficulty: DifficultyLevel::Easy,
            domain: BenchmarkDomain::General,
            metrics: vec!["accuracy".to_string(), "coverage".to_string()],
        }
    }
}

// Placeholder implementations for other benchmarks
macro_rules! impl_simple_benchmark {
    ($name:ident, $benchmark_name:literal, $difficulty:expr, $domain:expr) => {
        struct $name;

        impl $name {
            fn new() -> Self {
                Self
            }
        }

        impl Benchmark for $name {
            fn name(&self) -> &str {
                $benchmark_name
            }

            fn generate_test_data(&self) -> RragResult<EvaluationData> {
                // Generate simple test data
                let queries = vec![TestQuery {
                    id: format!("{}_1", $benchmark_name.to_lowercase()),
                    query: format!("Sample query for {}", $benchmark_name),
                    query_type: Some("test".to_string()),
                    metadata: HashMap::new(),
                }];

                let ground_truth = vec![GroundTruth {
                    query_id: format!("{}_1", $benchmark_name.to_lowercase()),
                    relevant_docs: vec!["test_doc".to_string()],
                    expected_answer: Some("Test answer".to_string()),
                    relevance_judgments: HashMap::new(),
                    metadata: HashMap::new(),
                }];

                Ok(EvaluationData {
                    queries,
                    ground_truth,
                    system_responses: Vec::new(),
                    context: HashMap::new(),
                })
            }

            fn evaluate_benchmark(
                &self,
                _responses: &[SystemResponse],
            ) -> RragResult<BenchmarkResult> {
                let overall_score = 0.75; // Default score for placeholder

                let mut detailed_scores = HashMap::new();
                detailed_scores.insert("placeholder_score".to_string(), overall_score);

                Ok(BenchmarkResult {
                    benchmark_name: self.name().to_string(),
                    overall_score,
                    detailed_scores,
                    ranking_info: RankingInfo {
                        percentile: 75.0,
                        baseline_comparisons: HashMap::new(),
                        confidence_interval: (0.65, 0.85),
                    },
                    performance_analysis: PerformanceAnalysis {
                        strengths: vec!["Placeholder performance".to_string()],
                        weaknesses: vec!["Needs real implementation".to_string()],
                        category_performance: HashMap::new(),
                        error_patterns: Vec::new(),
                    },
                    failure_cases: Vec::new(),
                })
            }

            fn get_config(&self) -> BenchmarkConfig {
                BenchmarkConfig {
                    name: self.name().to_string(),
                    num_queries: 1,
                    difficulty: $difficulty,
                    domain: $domain,
                    metrics: vec!["placeholder_score".to_string()],
                }
            }
        }
    };
}

impl_simple_benchmark!(
    FactualAccuracyBenchmark,
    "FactualAccuracy",
    DifficultyLevel::Medium,
    BenchmarkDomain::General
);
impl_simple_benchmark!(
    ReasoningBenchmark,
    "Reasoning",
    DifficultyLevel::Hard,
    BenchmarkDomain::General
);
impl_simple_benchmark!(
    DomainSpecificBenchmark,
    "DomainSpecific",
    DifficultyLevel::Medium,
    BenchmarkDomain::Science
);
impl_simple_benchmark!(
    MultiHopBenchmark,
    "MultiHop",
    DifficultyLevel::Hard,
    BenchmarkDomain::General
);
impl_simple_benchmark!(
    ConversationalBenchmark,
    "Conversational",
    DifficultyLevel::Medium,
    BenchmarkDomain::General
);

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

    #[test]
    fn test_general_knowledge_benchmark() {
        let benchmark = GeneralKnowledgeBenchmark::new();

        assert_eq!(benchmark.name(), "GeneralKnowledge");

        let test_data = benchmark.generate_test_data().unwrap();
        assert_eq!(test_data.queries.len(), 3);
        assert_eq!(test_data.ground_truth.len(), 3);
    }

    #[test]
    fn test_benchmark_evaluator() {
        let evaluator = BenchmarkEvaluator::new();

        assert_eq!(evaluator.name(), "Benchmark");
        assert!(!evaluator.supported_metrics().is_empty());
    }

    #[test]
    fn test_benchmark_evaluation() {
        let benchmark = GeneralKnowledgeBenchmark::new();
        let responses = vec![SystemResponse {
            query_id: "test".to_string(),
            retrieved_docs: vec![],
            generated_answer: Some("Test answer".to_string()),
            timing: super::super::SystemTiming {
                total_time_ms: 1000.0,
                retrieval_time_ms: 500.0,
                generation_time_ms: Some(400.0),
                reranking_time_ms: Some(100.0),
            },
            metadata: HashMap::new(),
        }];

        let result = benchmark.evaluate_benchmark(&responses).unwrap();
        assert!(result.overall_score > 0.0);
        assert_eq!(result.benchmark_name, "GeneralKnowledge");
    }
}