| """ | |
| OMEGA-Reasoner POC — loadable via: | |
| from huggingface_hub import hf_hub_download | |
| p = hf_hub_download("YOUR_ORG/omega-reasoner-poc", "agent.py") | |
| """ | |
| from .agi_agent_world import AGIAgentWorld | |
| from .agentworld_bench import (WorldModelAgent, evaluate, load_all, | |
| report_to_markdown) | |
| from .deep_swe import (load_all_tasks, run_benchmark, | |
| run_task, report_to_markdown as ds_md) | |
| def make_agent(vocab_size: int = 256, dim: int = 64, n_layers: int = 2, | |
| max_steps: int = 12) -> AGIAgentWorld: | |
| """Factory for the autonomous agent.""" | |
| return AGIAgentWorld(vocab_size=vocab_size, dim=dim, | |
| n_layers=n_layers, max_steps=max_steps) | |
| def evaluate_synthetic(data_dir: str) -> str: | |
| """Evaluate on a synthetic AgentWorldBench directory. Returns markdown.""" | |
| records = load_all(data_dir) | |
| rep = evaluate(WorldModelAgent(), records) | |
| return report_to_markdown(rep) | |
| __all__ = ["AGIAgentWorld", "WorldModelAgent", "evaluate", "load_all", | |
| "load_all_tasks", "run_benchmark", "run_task", | |
| "make_agent", "evaluate_synthetic"] |