llm_optimizer_decision/
lib.rs

1//! Optimization decision engine for LLM Auto-Optimizer
2//!
3//! This crate provides the decision-making logic for optimizing LLM configurations,
4//! including A/B testing, Thompson Sampling, statistical significance testing,
5//! contextual bandits for reinforcement learning, Pareto optimization, adaptive
6//! parameter tuning, drift & anomaly detection, and a comprehensive model registry
7//! for all major LLM providers.
8
9pub mod ab_testing;
10pub mod thompson_sampling;
11pub mod statistical;
12pub mod variant_generator;
13pub mod experiment_manager;
14pub mod contextual_bandit;
15pub mod context;
16pub mod reward;
17pub mod reinforcement_feedback;
18pub mod pareto;
19pub mod model_registry;
20pub mod adaptive_params;
21pub mod parameter_search;
22pub mod parameter_optimizer;
23pub mod drift_detection;
24pub mod anomaly_detection;
25pub mod threshold_monitor;
26pub mod errors;
27
28pub use ab_testing::ABTestEngine;
29pub use thompson_sampling::ThompsonSampling;
30pub use statistical::{StatisticalTest, ZTest};
31pub use variant_generator::VariantGenerator;
32pub use experiment_manager::ExperimentManager;
33pub use contextual_bandit::{LinUCB, ContextualThompson};
34pub use context::{RequestContext, OutputLengthCategory};
35pub use reward::{RewardCalculator, RewardWeights, UserFeedback, ResponseMetrics};
36pub use reinforcement_feedback::{ReinforcementEngine, BanditAlgorithm, VariantStats};
37pub use pareto::{
38    ModelCandidate, Objectives, ObjectiveWeights, ParetoFrontier, CostCalculator, QualityMetrics,
39};
40pub use model_registry::{
41    ModelRegistry, ModelDefinition, ModelPricing, ModelPerformance, ModelCapabilities,
42    Provider, ModelTier,
43};
44pub use adaptive_params::{
45    AdaptiveParameterTuner, ParameterConfig, ParameterRange, ParameterStats,
46};
47pub use parameter_search::{
48    GridSearch, GridSearchConfig, RandomSearch, LatinHypercubeSampling,
49    ParameterSearchManager, SearchStrategy,
50};
51pub use parameter_optimizer::{
52    ParameterOptimizer, OptimizationPolicy, OptimizationMode,
53};
54pub use drift_detection::{
55    DriftStatus, DriftAlgorithm, ADWIN, PageHinkley, CUSUM, StatisticalDriftDetector,
56};
57pub use anomaly_detection::{
58    AnomalyResult, ZScoreDetector, IQRDetector, MADDetector, MahalanobisDetector,
59};
60pub use threshold_monitor::{
61    ThresholdMonitoringSystem, ThresholdConfig, Alert, AlertType, AlertSeverity,
62};
63pub use errors::{DecisionError, Result};
llm_optimizer_decision/lib.rs

llm_optimizer_decision/
lib.rs
