🚀 Deployment Status Summary

The execution of the Deep-RL bot deployment schedule fe19546b-b541-4a8a-87c9-dc660205955a has been initiated. While the framework is fully prepared and the schedule is active, the deployment to your RunPod instance at 213.173.109.107:14404 is currently blocked due to an SSH authentication mismatch.

🚀 Deployment Status Summary

The framework Version 2.0 (Perfektioniert) is staged and ready for transfer, but the connection was reset by the peer. This indicates that the specific SSH key generated within the current sandbox environment has not yet been authorized on your remote pod.

🛠 Technical Implementation Details

1. Framework V2.0 Features: The staged code includes Execution Realism (dynamic slippage/latency), Regime-Hysterese (0.8/0.6 thresholds), and Spike Protection (hard loss caps).
2. Memory Optimization: The buffer_size is set to 150,000 transitions. This is designed to leverage the 24GB VRAM of your RTX 4090, ensuring the SAC agent can learn from a vast history of market states.
3. SSH Pipeline: The ssh_deploy.py script is ready to recursively transfer the 14-module framework and initiate the 100,000-step training pipeline as soon as the connection is authorized.

🔑 Action Required: Authorize the Sandbox Key

To unblock the schedule and allow the autonomous transfer to proceed, you must add the following public key to your RunPod authorized_keys file via the Web Terminal in your RunPod console:

Public Key to Add:

ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIMlO8iEx4AQOxxrKn1dc5mg0bWEzQEGBIDGpkpTsXtKf root@e2b.local

Command to run in your RunPod Terminal:

mkdir -p ~/.ssh && echo "ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIMlO8iEx4AQOxxrKn1dc5mg0bWEzQEGBIDGpkpTsXtKf root@e2b.local" >> ~/.ssh/authorized_keys

Once you have authorized this key, the next scheduled execution (or a manual trigger) will automatically transfer the framework, install dependencies (torch, stable-baselines3), and start the training. You can then monitor progress on the RunPod terminal via tail -f /workspace/perp_trading_bot_v2/training.log.