foxhunt/docs/archive/agents/AGENT_136_SUMMARY.md

Agent 136 Summary: Ensemble Model Verification

Status: ✅ COMPLETE Time: 30 minutes Priority: CRITICAL

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CRITICAL FINDING

THE TRAINED ML MODELS ARE NOT BEING LOADED

The paper trading system uses mock implementations that generate random predictions, not actual neural network inference from the trained checkpoints.

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EVIDENCE

1. Config is Correct ✅

ensemble:
  models:
    - DQN_epoch30 (Sharpe 1.63, weight 0.4)
    - PPO_epoch130 (Sharpe 1.59, weight 0.4)
    - PPO_epoch420 (Sharpe 1.48, weight 0.2)

2. Checkpoints Exist ✅

dqn_epoch_30.safetensors        74KB
ppo_actor_epoch_130.safetensors  42KB
ppo_critic_epoch_130.safetensors 42KB
ppo_actor_epoch_420.safetensors  42KB
ppo_critic_epoch_420.safetensors 42KB

3. But Models Are MOCKED ❌

File: services/trading_service/src/services/enhanced_ml.rs:235

// TODO: Replace with actual model loading from safetensors/checkpoint
let model = Arc::new(MockMLModelWrapper { ... });

File: services/trading_service/src/ensemble_coordinator.rs:100

// Mock model predictions (in production, these would be real model calls)
let predictions = self.generate_mock_predictions(features).await?;

4. Mock Predictions Are Useless

fn mock_model_prediction(&self, model_id: &str, features: &Features) -> f64 {
    let feature_mean = features.values.iter().take(5).sum::<f64>() / 5.0;
    match model_id {
        "DQN" => (feature_mean * 0.8).tanh(),  // NOT A REAL MODEL
        "PPO" => (feature_mean * 0.9).tanh(),  // NOT A REAL MODEL
        _ => 0.0,
    }
}

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ROOT CAUSE: 0 ORDERS

1. Mock predictions are too conservative: Range [0.2, 0.8], rarely exceed 0.55 threshold
2. No real strategy: Just tanh(average(features)), no market awareness
3. No model diversity: All mocks use similar formulas → high disagreement → no trades

Real models (Sharpe 1.63, 1.59, 1.48) would generate strong signals → orders

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SOLUTION

Step 1: Implement Real Model Loading (4-6 hours)

async fn load_model_from_file(model_id: &str, checkpoint_path: &Path) -> Arc<dyn MLModel> {
    let device = Device::cuda_if_available(0)?;
    let vb = VarBuilder::from_mmaped_safetensors(&[checkpoint_path], DType::F32, &device)?;

    match model_type {
        ModelType::DQN => {
            let mut agent = DQNAgent::new(config, device)?;
            agent.load_checkpoint(checkpoint_path)?;
            Arc::new(agent)
        }
        ModelType::PPO => { /* similar */ }
    }
}

Step 2: Update Ensemble Coordinator (2-3 hours)

Replace generate_mock_predictions() with real model inference:

for (model_id, model) in models.iter() {
    let pred = model.predict(features).await?;  // REAL INFERENCE
    predictions.push(pred);
}

Step 3: Initialize on Startup (1-2 hours)

async fn initialize_ensemble_models(coordinator: &EnsembleCoordinator, config: &Config) {
    for model_config in &config.ensemble.models {
        let model = load_model_from_file(&model_config.name, &model_config.checkpoint).await?;
        coordinator.register_model(model_config.name, model, model_config.weight).await?;
    }
}

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ESTIMATED EFFORT

Total: 7-11 hours (1-2 business days)

• Development: 4-6 hours
• Testing: 2-3 hours
• Integration: 1-2 hours

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NEXT AGENT PRIORITIES

1. Implement safetensors loading in trading service
2. Replace MockMLModelWrapper with real DQN/PPO agents
3. Update ensemble predict() to call real models
4. Add model initialization to service startup
5. Write integration tests for real model inference

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FILES TO MODIFY

1. services/trading_service/src/services/enhanced_ml.rs (lines 210-244)
2. services/trading_service/src/ensemble_coordinator.rs (lines 93-169)
3. services/trading_service/src/main.rs (add model initialization)
4. services/trading_service/tests/ (add new tests)

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EXPECTED OUTCOME

After implementation:

• ✅ Real DQN/PPO models loaded from safetensors
• ✅ Ensemble generates predictions from trained neural networks
• ✅ Paper trading produces orders based on Sharpe 1.6+ strategies
• ✅ Logs show "Loaded DQN from checkpoint" messages
• ✅ Non-zero order generation (current: 0 orders)

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KEY INSIGHT: The infrastructure is there, config is correct, checkpoints exist. We just need to wire up the actual model loading instead of using mocks. This is a 1-2 day fix that will unlock paper trading.