๐ฌ LLM Networking OptimizationJuly 16, 2026โ
Tests passing
MikroTik LLM Optimizer
A CLI tool to automate MikroTik router configuration for optimizing networking setups tailored to large language model (LLM) communication. This tool helps AI developers configure Quality of Service (QoS), bandwidth allocation, and port forwarding for efficient LLM data transmission, reducing latency and increasing throughput.
What It Does
A CLI tool to automate MikroTik router configuration for optimizing networking setups tailored to large language model (LLM) communication. This tool helps AI developers configure Quality of Service (QoS), bandwidth allocation, and port forwarding for efficient LLM data transmission, reducing latency.
Installation
Install the required Python package:
pip install routeros-apiUsage
python mikrotik_llm_optimizer.py --host 192.168.88.1 --user admin --password admin --prioritize-ports 8000,8001 --bandwidth-limit 10000Source Code
import argparse
from routeros_api import RouterOsApiPool
def optimize_router(host, user, password, prioritize_ports, bandwidth_limit):
"""
Automates MikroTik router configuration for optimizing networking setups tailored to large language model (LLM) communication.
"""
api_pool = None
try:
# Connect to the MikroTik router
api_pool = RouterOsApiPool(host, username=user, password=password, plaintext_login=True)
api = api_pool.get_api()
# Parse the ports
ports = prioritize_ports.split(',')
# Add firewall mangle rules to mark LLM traffic
for port in ports:
api.get_resource('/ip/firewall/mangle').add(
chain='prerouting',
protocol='tcp',
dst_port=port,
action='mark-connection',
new_connection_mark=f'llm_conn_{port}',
passthrough='yes'
)
api.get_resource('/ip/firewall/mangle').add(
chain='prerouting',
connection_mark=f'llm_conn_{port}',
action='mark-packet',
new_packet_mark=f'llm_packet_{port}',
passthrough='no'
)
# Add queue tree for bandwidth management if bandwidth limit is provided
if bandwidth_limit:
for port in ports:
api.get_resource('/queue/tree').add(
name=f'llm_queue_{port}',
parent='global',
packet_mark=f'llm_packet_{port}',
max_limit=int(bandwidth_limit) * 1024 # Convert kbps to bps
)
print("Router optimization completed successfully.")
except Exception as e:
print(f"Error: {e}")
raise e
finally:
if api_pool:
api_pool.disconnect()
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Optimize MikroTik router for LLM communication.")
parser.add_argument('--host', required=True, help='MikroTik router IP address')
parser.add_argument('--user', required=True, help='MikroTik username')
parser.add_argument('--password', required=True, help='MikroTik password')
parser.add_argument('--prioritize-ports', required=True, help='Comma-separated list of ports to prioritize for LLM traffic')
parser.add_argument('--bandwidth-limit', default=None, type=int, help='Bandwidth limit for LLM traffic in kbps (e.g., 10000 for 10 Mbps)')
args = parser.parse_args()
optimize_router(args.host, args.user, args.password, args.prioritize_ports, args.bandwidth_limit)Community
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Details
- Tool Name
- mikrotik_llm_optimizer
- Category
- LLM Networking Optimization
- Generated
- July 16, 2026
- Tests
- Passing โ
- Fix Loops
- 3
Quick Install
Clone just this tool:
git clone --depth 1 --filter=blob:none --sparse \ https://github.com/ptulin/autoaiforge.git cd autoaiforge git sparse-checkout set generated_tools/2026-07-16/mikrotik_llm_optimizer cd generated_tools/2026-07-16/mikrotik_llm_optimizer pip install -r requirements.txt 2>/dev/null || true python mikrotik_llm_optimizer.py