Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

vendor/ruvector/crates/ruvector-dag/src/lib.rs

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+//! RuVector DAG - Directed Acyclic Graph structures for query plan optimization
+//!
+//! This crate provides efficient DAG data structures and algorithms for representing
+//! and manipulating query execution plans with neural learning capabilities.
+//!
+//! ## Features
+//!
+//! - **DAG Data Structures**: Efficient directed acyclic graph representation for query plans
+//! - **7 Attention Mechanisms**: Topological, Causal Cone, Critical Path, MinCut Gated, and more
+//! - **SONA Learning**: Self-Optimizing Neural Architecture with MicroLoRA adaptation (non-WASM only)
+//! - **MinCut Optimization**: Subpolynomial O(n^0.12) bottleneck detection
+//! - **Self-Healing**: Autonomous anomaly detection and repair (non-WASM only)
+//! - **QuDAG Integration**: Quantum-resistant distributed pattern learning (non-WASM only)
+//!
+//! ## Quick Start
+//!
+//! ```rust
+//! use ruvector_dag::{QueryDag, OperatorNode, OperatorType};
+//! use ruvector_dag::attention::{TopologicalAttention, DagAttention};
+//!
+//! // Build a query DAG
+//! let mut dag = QueryDag::new();
+//! let scan = dag.add_node(OperatorNode::seq_scan(0, "users"));
+//! let filter = dag.add_node(OperatorNode::filter(1, "age > 18"));
+//! dag.add_edge(scan, filter).unwrap();
+//!
+//! // Compute attention scores
+//! let attention = TopologicalAttention::new(Default::default());
+//! let scores = attention.forward(&dag).unwrap();
+//! ```
+//!
+//! ## Modules
+//!
+//! - [`dag`] - Core DAG data structures and algorithms
+//! - [`attention`] - Neural attention mechanisms for node importance
+//! - [`sona`] - Self-Optimizing Neural Architecture with adaptive learning (requires `full` feature)
+//! - [`mincut`] - Subpolynomial bottleneck detection and optimization
+//! - [`healing`] - Self-healing system with anomaly detection (requires `full` feature)
+//! - [`qudag`] - QuDAG network integration for distributed learning (requires `full` feature)
+
+// Core modules (always available)
+pub mod attention;
+pub mod dag;
+pub mod mincut;
+
+// Modules requiring async runtime (non-WASM only)
+#[cfg(feature = "full")]
+pub mod healing;
+#[cfg(feature = "full")]
+pub mod qudag;
+#[cfg(feature = "full")]
+pub mod sona;
+
+pub use dag::{
+    BfsIterator, DagDeserializer, DagError, DagSerializer, DfsIterator, OperatorNode, OperatorType,
+    QueryDag, TopologicalIterator,
+};
+
+pub use mincut::{
+    Bottleneck, BottleneckAnalysis, DagMinCutEngine, FlowEdge, LocalKCut, MinCutConfig,
+    MinCutResult, RedundancyStrategy, RedundancySuggestion,
+};
+
+pub use attention::{
+    AttentionConfig, AttentionError, AttentionScores, CausalConeAttention, CausalConeConfig,
+    CriticalPathAttention, CriticalPathConfig, DagAttention, FlowCapacity,
+    MinCutConfig as AttentionMinCutConfig, MinCutGatedAttention, TopologicalAttention,
+    TopologicalConfig,
+};
+
+#[cfg(feature = "full")]
+pub use qudag::QuDagClient;
+
+// Re-export crypto security functions for easy access (requires full feature)
+#[cfg(feature = "full")]
+pub use qudag::crypto::{
+    check_crypto_security, is_production_ready, security_status, SecurityStatus,
+};
+
+#[cfg(feature = "full")]
+pub use healing::{
+    Anomaly, AnomalyConfig, AnomalyDetector, AnomalyType, DriftMetric, DriftTrend,
+    HealingCycleResult, HealingOrchestrator, HealthStatus, IndexCheckResult, IndexHealth,
+    IndexHealthChecker, IndexThresholds, IndexType, LearningDriftDetector, RepairResult,
+    RepairStrategy,
+};
+
+#[cfg(feature = "full")]
+pub use sona::{
+    DagPattern, DagReasoningBank, DagSonaEngine, DagTrajectory, DagTrajectoryBuffer, EwcConfig,
+    EwcPlusPlus, MicroLoRA, MicroLoRAConfig, ReasoningBankConfig,
+};
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_basic_dag_creation() {
+        let dag = QueryDag::new();
+        assert_eq!(dag.node_count(), 0);
+        assert_eq!(dag.edge_count(), 0);
+    }
+}