Monitoring

skydiscover-run init.py eval.py -c config.yaml -s adaevolve -i 100

http://localhost:8765

Top 3 Solutions Summary:

1. Program #87 (score: 0.945)
   - Uses hexagonal packing in the center
   - Optimizes corner utilization with smaller circles
   - Achieves 94.5% of theoretical maximum

2. Program #72 (score: 0.923)
   - Similar to #87 but with uniform circle sizes
   - Simpler implementation, slightly lower score
   - Good baseline for further optimization

3. Program #64 (score: 0.901)
   - Grid-based approach
   - Faster evaluation but lower density
   - Useful for understanding trade-offs

# On your local machine
ssh -L 8765:localhost:8765 user@remote-server

http://192.168.1.100:8765

from skydiscover import run_discovery
from skydiscover.config import Config, MonitorConfig

config = Config()
config.monitor = MonitorConfig(
    enabled=True,
    port=8765,
    summary_model="gpt-4o-mini",
    summary_interval=10,  # Auto-generate every 10 programs
)

result = run_discovery(
    evaluator="eval.py",
    initial_program="init.py",
    config=config,
    iterations=100,
)

from skydiscover.extras.monitor import create_monitor_callback, MonitorServer

def my_callback(event: dict):
    """Custom event handler."""
    if event["type"] == "program_evaluated":
        print(f"Program {event['id']}: score={event['score']}")
        # Send to external logging service, etc.

monitor_server = MonitorServer(port=8765)
monitor_server.start()

monitor_callback = create_monitor_callback(monitor_server, custom_handler=my_callback)

# Pass to runner
runner = Runner(
    initial_program_path="init.py",
    evaluation_file="eval.py",
    config=config,
    output_dir="./outputs",
)
runner.monitor_callback = monitor_callback

await runner.run(iterations=100)

skydiscover-viewer outputs/adaevolve/circle_packing_0305_1430/