mirror of
https://github.com/JackHopkins/factorio-learning-environment.git
synced 2025-09-06 13:23:58 +00:00
5ee9586e1d
* first iteration * change to support openai api endpoints * Refactor APIFactory to use OpenAI-compatible endpoints - Unified all providers to use OpenAI client format - Eliminated provider-specific conditional branches - Simplified provider detection using dict ordering - Removed unused parameters and added missing return - 90% reduction in code complexity * Further simplify APIFactory - Remove redundant MODELS_WITH_IMAGE_SUPPORT array - Use provider config supports_images instead - Inline _prepare_messages logic - Extract _get_reasoning_length helper - Add missing default return - 20+ line reduction while maintaining functionality * removecomment * Inline reasoning length logic - Remove _get_reasoning_length helper method - Inline reasoning effort logic in o1/o3 handling - Keep code simpler and more direct * add provider sorting for openrouter to get fastest throughput * add nitro * add usage tracking * usage * undo changes that added logging * update config paths * remove offset * offset * Aug 20, 2025 at 20:25 * fix run_idx port offset * make sure there is keyerror if no port * fix
34 lines
1.0 KiB
Python
34 lines
1.0 KiB
Python
from dataclasses import dataclass
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from typing import List, Optional
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from fle.agents.gym_agent import GymAgent
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from fle.env.gym_env.observation_formatter import BasicObservationFormatter
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from fle.eval.tasks import TaskABC
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from a2a.types import AgentCard
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@dataclass
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class GymRunConfig:
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"""Configuration for a single gym environment evaluation run"""
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env_id: str # Gym environment ID from registry (e.g., "Factorio-iron_ore_throughput_16-v0")
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model: str
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version: Optional[int] = None
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observation_formatter: Optional[BasicObservationFormatter] = None
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@dataclass
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class GymEvalConfig:
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"""Configuration for gym evaluation"""
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agents: List[GymAgent]
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version: int
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version_description: str
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task: Optional[TaskABC] = None
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agent_cards: Optional[List[AgentCard]] = None
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env_id: Optional[str] = None # Gym environment ID for registry-based creation
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def __post_init__(self):
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if self.task is None and hasattr(self.agents[0], "task"):
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self.task = self.agents[0].task
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