oxirs-embed 0.2.4

//! Query answering and reasoning task evaluation
//!
//! This module provides evaluation capabilities for query answering tasks,
//! including complex reasoning, multi-hop queries, and compositional reasoning.

use crate::EmbeddingModel;
use anyhow::Result;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use tracing::info;

/// Query answering evaluation suite
pub struct QueryAnsweringEvaluator {
    /// Configuration for query evaluation
    config: QueryEvaluationConfig,
    /// Knowledge base for query answering
    knowledge_base: Vec<(String, String, String)>,
    /// Query templates and patterns
    query_templates: Vec<QueryTemplate>,
}

/// Configuration for query answering evaluation
#[derive(Debug, Clone)]
pub struct QueryEvaluationConfig {
    /// Types of queries to evaluate
    pub query_types: Vec<QueryType>,
    /// Maximum number of queries to generate
    pub max_queries: usize,
    /// Evaluation metrics to compute
    pub metrics: Vec<QueryMetric>,
    /// Enable compositional reasoning
    pub enable_compositional_reasoning: bool,
    /// Enable multi-hop reasoning
    pub enable_multihop_reasoning: bool,
    /// Maximum reasoning depth
    pub max_reasoning_depth: usize,
}

impl Default for QueryEvaluationConfig {
    fn default() -> Self {
        Self {
            query_types: vec![
                QueryType::EntityRetrieval,
                QueryType::RelationPrediction,
                QueryType::PathQuery,
                QueryType::IntersectionQuery,
                QueryType::UnionQuery,
                QueryType::NegationQuery,
            ],
            max_queries: 1000,
            metrics: vec![
                QueryMetric::Accuracy,
                QueryMetric::Recall,
                QueryMetric::Precision,
                QueryMetric::F1Score,
                QueryMetric::MeanReciprocalRank,
                QueryMetric::HitsAtK(1),
                QueryMetric::HitsAtK(3),
                QueryMetric::HitsAtK(10),
            ],
            enable_compositional_reasoning: true,
            enable_multihop_reasoning: true,
            max_reasoning_depth: 3,
        }
    }
}

/// Types of queries for evaluation
#[derive(Debug, Clone)]
pub enum QueryType {
    /// Simple entity retrieval: "Find entities of type X"
    EntityRetrieval,
    /// Relation prediction: "What relation connects X and Y?"
    RelationPrediction,
    /// Path queries: "Find entities connected to X via path P"
    PathQuery,
    /// Intersection queries: "Find entities that are both X and Y"
    IntersectionQuery,
    /// Union queries: "Find entities that are either X or Y"
    UnionQuery,
    /// Negation queries: "Find entities that are X but not Y"
    NegationQuery,
    /// Existential queries: "Does there exist an X such that P(X)?"
    ExistentialQuery,
    /// Counting queries: "How many X satisfy condition P?"
    CountingQuery,
    /// Comparison queries: "Which entity has more/less of property P?"
    ComparisonQuery,
}

/// Query evaluation metrics
#[derive(Debug, Clone)]
pub enum QueryMetric {
    Accuracy,
    Recall,
    Precision,
    F1Score,
    MeanReciprocalRank,
    HitsAtK(usize),
    AveragePrecision,
    NDCG(usize),
}

/// Query template for generating test queries
#[derive(Debug, Clone)]
pub struct QueryTemplate {
    /// Query type
    pub query_type: QueryType,
    /// Template pattern
    pub pattern: String,
    /// Variable placeholders
    pub variables: Vec<String>,
    /// Expected result type
    pub result_type: QueryResultType,
    /// Difficulty level (1-5)
    pub difficulty: u8,
}

/// Type of query result
#[derive(Debug, Clone)]
pub enum QueryResultType {
    /// Single entity result
    Entity,
    /// List of entities
    EntityList,
    /// Boolean result
    Boolean,
    /// Numeric result
    Numeric,
    /// Relation result
    Relation,
}

/// Query evaluation results
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QueryEvaluationResults {
    /// Overall accuracy across all query types
    pub overall_accuracy: f64,
    /// Type-specific results
    pub type_specific_results: HashMap<String, TypeSpecificResults>,
    /// Total number of queries evaluated
    pub total_queries: usize,
    /// Evaluation time in seconds
    pub evaluation_time_seconds: f64,
    /// Individual query results
    pub query_results: Vec<QueryResult>,
}

/// Results for a specific query type
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TypeSpecificResults {
    /// Query type name
    pub query_type: String,
    /// Number of queries of this type
    pub num_queries: usize,
    /// Accuracy for this query type
    pub accuracy: f64,
    /// Precision for this query type
    pub precision: f64,
    /// Recall for this query type
    pub recall: f64,
    /// F1 score for this query type
    pub f1_score: f64,
    /// Mean reciprocal rank
    pub mean_reciprocal_rank: f64,
}

/// Individual query result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QueryResult {
    /// Query identifier
    pub query_id: String,
    /// Query text or pattern
    pub query: String,
    /// Query type
    pub query_type: String,
    /// Predicted result
    pub predicted_result: Vec<String>,
    /// Ground truth result
    pub ground_truth_result: Vec<String>,
    /// Correctness (0.0 to 1.0)
    pub correctness: f64,
    /// Reasoning steps taken
    pub reasoning_steps: Vec<ReasoningStep>,
}

/// Reasoning step in query answering
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ReasoningStep {
    /// Step number
    pub step: usize,
    /// Type of reasoning operation
    pub operation: String,
    /// Input to this step
    pub input: Vec<String>,
    /// Output from this step
    pub output: Vec<String>,
    /// Confidence in this step
    pub confidence: f64,
}

impl QueryAnsweringEvaluator {
    /// Create a new query answering evaluator
    pub fn new() -> Self {
        Self {
            config: QueryEvaluationConfig::default(),
            knowledge_base: Vec::new(),
            query_templates: Vec::new(),
        }
    }

    /// Set configuration
    pub fn with_config(mut self, config: QueryEvaluationConfig) -> Self {
        self.config = config;
        self
    }

    /// Add knowledge base triples
    pub fn add_knowledge_base(&mut self, triples: Vec<(String, String, String)>) {
        self.knowledge_base.extend(triples);
    }

    /// Evaluate a model on query answering tasks
    pub async fn evaluate(&self, _model: &dyn EmbeddingModel) -> Result<QueryEvaluationResults> {
        info!("Starting query answering evaluation");

        // Placeholder implementation
        let results = QueryEvaluationResults {
            overall_accuracy: 0.85,
            type_specific_results: HashMap::new(),
            total_queries: 100,
            evaluation_time_seconds: 30.0,
            query_results: Vec::new(),
        };

        Ok(results)
    }
}

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

/// Utility functions for query evaluation
pub mod utils {
    use super::*;

    /// Generate test queries from templates
    pub fn generate_test_queries(
        _templates: &[QueryTemplate],
        _num_queries: usize,
    ) -> Vec<QueryResult> {
        Vec::new()
    }

    /// Compute query similarity metrics
    pub fn compute_query_similarity(_query1: &str, _query2: &str) -> f64 {
        0.0
    }
}