foxhunt/crates/ml/tests/integration_ppo_ensemble.rs

#![allow(
    clippy::assertions_on_constants,
    clippy::assertions_on_result_states,
    clippy::clone_on_copy,
    clippy::decimal_literal_representation,
    clippy::doc_markdown,
    clippy::empty_line_after_doc_comments,
    clippy::field_reassign_with_default,
    clippy::get_unwrap,
    clippy::identity_op,
    clippy::inconsistent_digit_grouping,
    clippy::indexing_slicing,
    clippy::integer_division,
    clippy::len_zero,
    clippy::let_underscore_must_use,
    clippy::manual_div_ceil,
    clippy::manual_let_else,
    clippy::manual_range_contains,
    clippy::modulo_arithmetic,
    clippy::needless_range_loop,
    clippy::non_ascii_literal,
    clippy::redundant_clone,
    clippy::shadow_reuse,
    clippy::shadow_same,
    clippy::shadow_unrelated,
    clippy::single_match_else,
    clippy::str_to_string,
    clippy::string_slice,
    clippy::tests_outside_test_module,
    clippy::too_many_lines,
    clippy::unnecessary_wraps,
    clippy::unseparated_literal_suffix,
    clippy::use_debug,
    clippy::useless_vec,
    clippy::wildcard_enum_match_arm,
    clippy::else_if_without_else,
    clippy::expect_used,
    clippy::missing_const_for_fn,
    clippy::similar_names,
    clippy::type_complexity,
    clippy::collapsible_else_if,
    clippy::doc_lazy_continuation,
    clippy::items_after_test_module,
    clippy::map_clone,
    clippy::multiple_unsafe_ops_per_block,
    clippy::unwrap_or_default,
    clippy::assign_op_pattern,
    clippy::needless_borrow,
    clippy::println_empty_string,
    clippy::unnecessary_cast,
    clippy::used_underscore_binding,
    clippy::create_dir,
    clippy::implicit_saturating_sub,
    clippy::exit,
    clippy::expect_fun_call,
    clippy::too_many_arguments,
    clippy::unnecessary_map_or,
    clippy::unwrap_used,
    dead_code,
    unused_imports,
    unused_variables,
    clippy::cloned_ref_to_slice_refs,
    clippy::neg_multiply,
    clippy::while_let_loop,
    clippy::bool_assert_comparison,
    clippy::excessive_precision,
    clippy::trivially_copy_pass_by_ref,
    clippy::op_ref,
    clippy::redundant_closure,
    clippy::unnecessary_lazy_evaluations,
    clippy::if_then_some_else_none,
    clippy::unnecessary_to_owned,
    clippy::single_component_path_imports,
)]
//! Integration test for PPO checkpoint loading in ensemble coordinator
//!
//! Validates Agent 170's PPO checkpoint loading works in production ensemble context

use ml::ensemble::EnsembleCoordinator;
use ml::Features;

#[tokio::test]
async fn test_ppo_checkpoint_loading_in_ensemble() {
    let coordinator = EnsembleCoordinator::new();

    // Load PPO checkpoint (epoch 420 - production model)
    let result = coordinator
        .load_ppo_checkpoint(
            "PPO_epoch420",
            "ml/trained_models/production/ppo/ppo_actor_epoch_420.safetensors",
            "ml/trained_models/production/ppo/ppo_critic_epoch_420.safetensors",
            0.33,
        )
        .await;

    assert!(
        result.is_ok(),
        "PPO checkpoint loading should succeed: {:?}",
        result.err()
    );

    // Verify model is registered
    assert_eq!(coordinator.model_count().await, 1);

    // Test prediction with loaded PPO model
    let features = Features::new(
        vec![0.5, 0.6, 0.7, 0.8, 0.9],
        vec![
            "f1".to_string(),
            "f2".to_string(),
            "f3".to_string(),
            "f4".to_string(),
            "f5".to_string(),
        ],
    );

    let decision = coordinator.predict(&features).await;
    assert!(
        decision.is_ok(),
        "Prediction should succeed with loaded PPO: {:?}",
        decision.err()
    );

    let decision = decision.unwrap();
    assert!(decision.confidence >= 0.0 && decision.confidence <= 1.0);
    assert!(decision.signal >= -1.0 && decision.signal <= 1.0);
}

#[tokio::test]
async fn test_ppo_ensemble_with_multiple_models() {
    let coordinator = EnsembleCoordinator::new();

    // Load PPO epoch 420
    coordinator
        .load_ppo_checkpoint(
            "PPO_epoch420",
            "ml/trained_models/production/ppo/ppo_actor_epoch_420.safetensors",
            "ml/trained_models/production/ppo/ppo_critic_epoch_420.safetensors",
            0.33,
        )
        .await
        .expect("PPO epoch 420 should load");

    // Load PPO epoch 130 (alternative checkpoint)
    coordinator
        .load_ppo_checkpoint(
            "PPO_epoch130",
            "ml/trained_models/production/ppo/ppo_actor_epoch_130.safetensors",
            "ml/trained_models/production/ppo/ppo_critic_epoch_130.safetensors",
            0.33,
        )
        .await
        .expect("PPO epoch 130 should load");

    // Register mock DQN for ensemble
    coordinator
        .register_model("DQN_mock".to_string(), 0.34)
        .await
        .expect("DQN mock should register");

    // Verify all models registered
    assert_eq!(coordinator.model_count().await, 3);

    // Test ensemble prediction
    let features = Features::new(
        vec![0.1, 0.2, 0.3, 0.4, 0.5],
        vec![
            "price_momentum".to_string(),
            "volume".to_string(),
            "volatility".to_string(),
            "spread".to_string(),
            "rsi".to_string(),
        ],
    );

    let decision = coordinator
        .predict(&features)
        .await
        .expect("Ensemble prediction should succeed");

    // Verify ensemble decision
    assert_eq!(decision.model_count(), 3);
    assert!(decision.confidence >= 0.0 && decision.confidence <= 1.0);
    assert!(decision.signal >= -1.0 && decision.signal <= 1.0);
}

#[tokio::test]
async fn test_ppo_hot_swap() {
    let coordinator = EnsembleCoordinator::new();

    // Load initial PPO model (epoch 130)
    coordinator
        .load_ppo_checkpoint(
            "PPO_active",
            "ml/trained_models/production/ppo/ppo_actor_epoch_130.safetensors",
            "ml/trained_models/production/ppo/ppo_critic_epoch_130.safetensors",
            0.50,
        )
        .await
        .expect("Initial PPO should load");

    // Get initial prediction
    let features = Features::new(
        vec![0.5, 0.5, 0.5, 0.5, 0.5],
        vec![
            "f1".to_string(),
            "f2".to_string(),
            "f3".to_string(),
            "f4".to_string(),
            "f5".to_string(),
        ],
    );

    let decision1 = coordinator
        .predict(&features)
        .await
        .expect("Initial prediction should succeed");

    // Hot-swap to newer PPO model (epoch 420)
    coordinator
        .load_ppo_checkpoint(
            "PPO_active",
            "ml/trained_models/production/ppo/ppo_actor_epoch_420.safetensors",
            "ml/trained_models/production/ppo/ppo_critic_epoch_420.safetensors",
            0.50,
        )
        .await
        .expect("Hot-swap should succeed");

    // Get prediction with swapped model
    let decision2 = coordinator
        .predict(&features)
        .await
        .expect("Post-swap prediction should succeed");

    // Both predictions should be valid (values may differ due to different models)
    assert!(decision1.confidence >= 0.0 && decision1.confidence <= 1.0);
    assert!(decision2.confidence >= 0.0 && decision2.confidence <= 1.0);

    // Model count should remain 1 (same model_id replaced)
    assert_eq!(coordinator.model_count().await, 1);
}

#[tokio::test]
async fn test_ppo_checkpoint_path_validation() {
    let coordinator = EnsembleCoordinator::new();

    // Test with invalid checkpoint path
    let result = coordinator
        .load_ppo_checkpoint(
            "PPO_invalid",
            "nonexistent_actor.safetensors",
            "nonexistent_critic.safetensors",
            0.50,
        )
        .await;

    // Should still succeed at registration level (actual loading happens in enhanced_ml.rs)
    // The ensemble coordinator only manages checkpoint paths
    assert!(result.is_ok());
}