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8c686ce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | """Master script to run multiple agents and evaluate them."""
import argparse
import json
from pathlib import Path
from ontology_architect.config import load_config
from ontology_architect.server.ontology_architect_environment import OntologyArchitectEnvironment
from ontology_architect.agents.random_agent import RandomAgent
from ontology_architect.agents.heuristic_agent import HeuristicAgent
from ontology_architect.agents.llm_agent import LLMAgent
from ontology_architect.agents.base_agent import BaseAgent
from ontology_architect.reward import theory_structural_distance
from ontology_architect.baselines import get_baseline
class OracleAgent(BaseAgent):
def act(self, observation):
from ontology_architect.models import OntologyArchitectAction
return OntologyArchitectAction(
theory_module=get_baseline("dual_fluid_dsl"),
revision_note="Oracle theory",
paradigm_shift_claim=False
)
def run_agent(agent: BaseAgent, config, steps: int):
env = OntologyArchitectEnvironment(config)
obs = env.reset()
metrics = []
previous_theory = None
for step in range(steps):
action = agent.act(obs)
obs = env.step(action)
# Track Diversity
diversity_score = 1.0
if previous_theory:
diversity_score = theory_structural_distance(action.theory_module, previous_theory)
previous_theory = action.theory_module
step_metadata = obs.metadata.get("last_metrics", {})
metrics.append({
"step": step,
"reward": obs.reward,
"execution_ok": step_metadata.get("execution_ok", False),
"log_likelihood": step_metadata.get("log_likelihood", 0.0),
"mdl_penalty": step_metadata.get("mdl_penalty", 0.0),
"diversity_score": diversity_score
})
if obs.done:
break
return metrics
def main():
parser = argparse.ArgumentParser(description="Evaluate agents.")
parser.add_argument("--config", default="configs/dual_fluid_demo.json")
parser.add_argument("--steps", type=int, default=100)
parser.add_argument("--output", default="artifacts/grader_report.json")
args = parser.parse_args()
config = load_config(args.config)
agents = [
RandomAgent(),
HeuristicAgent(),
LLMAgent(),
OracleAgent(name="oracle_agent")
]
report = {}
for agent in agents:
print(f"Running {agent.name}...")
metrics = run_agent(agent, config, args.steps)
report[agent.name] = metrics
out_path = Path(args.output)
out_path.parent.mkdir(parents=True, exist_ok=True)
with out_path.open("w") as f:
json.dump(report, f, indent=2)
print(f"Grader report saved to {args.output}")
if __name__ == "__main__":
main()
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