#!/bin/bash
# Quick DQN Deployment Script
# Date: 2025-10-24
# Purpose: Deploy DQN training to RunPod with correct binary selection

set -euo pipefail

echo "=========================================="
echo "RunPod DQN Training Deployment"
echo "=========================================="
echo ""
echo "Using: deploy_runpod_graphql.py (CORRECT script)"
echo "Binary: train_dqn"
echo "Dataset: ES_FUT_small.parquet (~13K bars)"
echo "GPU: RTX A4000 (16GB, $0.25/hr)"
echo "Expected time: ~1 minute"
echo "Expected cost: ~$0.004"
echo ""

# Deploy DQN training
python3 scripts/deploy_runpod_graphql.py \
  --binary train_dqn \
  --parquet-file /runpod-volume/test_data/ES_FUT_small.parquet \
  --epochs 100 \
  --gpu-type "NVIDIA RTX A4000" \
  --pod-name foxhunt-dqn-training

echo ""
echo "=========================================="
echo "Deployment Complete"
echo "=========================================="
echo ""
echo "Next steps:"
echo "1. Copy the Pod ID from output above"
echo "2. Monitor training:"
echo "   ssh root@POD_ID.ssh.runpod.io"
echo "   nvidia-smi -l 1"
echo "3. Check models after training:"
echo "   ls -lh /runpod-volume/models/"
echo "4. Terminate pod to stop billing"
echo ""