#!/bin/bash
set -e

echo "========================================="
echo "PPO Hyperopt Deployment (CORRECTED OBJECTIVE)"
echo "========================================="
echo ""

# Configuration
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
OUTPUT_DIR="ppo_hyperopt_corrected_${TIMESTAMP}"

echo "Configuration:"
echo "  Objective: Episode rewards (CORRECTED from validation loss)"
echo "  Trials: 50"
echo "  Episodes per trial: 2000"
echo "  GPU: RTX A4000 ($0.25/hr)"
echo "  Expected duration: 10-20 min"
echo "  Expected cost: \$0.04-\$0.08"
echo "  Output: /runpod-volume/ml_training/${OUTPUT_DIR}"
echo ""

# Verify Docker image contains fix
echo "Verifying Docker image..."
docker images jgrusewski/foxhunt-hyperopt:latest --format "table {{.Repository}}\t{{.Tag}}\t{{.CreatedAt}}"
echo ""

# Check for .venv activation
if [[ -z "$VIRTUAL_ENV" ]]; then
    echo "ERROR: Virtual environment not activated"
    echo "Run: source .venv/bin/activate"
    exit 1
fi

# Deploy PPO hyperopt with CORRECTED objective
echo "Deploying PPO hyperopt with CORRECTED objective function..."
python3 scripts/runpod_deploy.py \
    --gpu-type "RTX A4000" \
    --image "jgrusewski/foxhunt-hyperopt:latest" \
    --command "hyperopt_ppo_demo --parquet-file /runpod-volume/test_data/ES_FUT_180d.parquet --trials 50 --episodes 2000 --base-dir /runpod-volume/ml_training/${OUTPUT_DIR} --early-stopping-min-epochs 50"

echo ""
echo "✅ PPO hyperopt deployment initiated (CORRECTED OBJECTIVE)"
echo ""
echo "CRITICAL FIX APPLIED:"
echo "  Previous objective: val_policy_loss + val_value_loss (WRONG)"
echo "  New objective: -avg_episode_reward (CORRECT)"
echo ""
echo "Expected Results:"
echo "  Policy LR: Should vary widely (not stuck at 1e-6)"
echo "  Value LR: Should optimize for actual learning"
echo "  Episode rewards: Should maximize trading returns"
echo "  Clip epsilon: Should find sweet spot for policy updates"
echo ""
echo "Next Steps:"
echo "  1. Monitor logs: python3 scripts/runpod_deploy.py --monitor <pod_id>"
echo "  2. Verify results in S3: aws s3 ls s3://se3zdnb5o4/models/ --profile runpod --recursive"
echo "  3. Compare hyperparameters to previous frozen policy (policy_lr=1e-6)"
echo ""