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| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the BSD-style license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| """Job Scheduler Env Environment Client.""" | |
| from typing import Dict | |
| from openenv.core import EnvClient | |
| from openenv.core.client_types import StepResult | |
| from openenv.core.env_server.types import State | |
| from models import JobSchedulerEnvAction, JobSchedulerEnvObservation | |
| class JobSchedulerEnvEnv( | |
| EnvClient[JobSchedulerEnvAction, JobSchedulerEnvObservation, State] | |
| ): | |
| """ | |
| Client for the Job Scheduler Env Environment. | |
| This client maintains a persistent WebSocket connection to the environment server, | |
| enabling efficient multi-step interactions with lower latency. | |
| Each client instance has its own dedicated environment session on the server. | |
| Example: | |
| >>> # Connect to a running server | |
| >>> with JobSchedulerEnvEnv(base_url="http://localhost:8000") as client: | |
| ... result = client.reset() | |
| ... print(result.observation.echoed_message) | |
| ... | |
| ... result = client.step(JobSchedulerEnvAction(message="Hello!")) | |
| ... print(result.observation.echoed_message) | |
| Example with Docker: | |
| >>> # Automatically start container and connect | |
| >>> client = JobSchedulerEnvEnv.from_docker_image("Job_Scheduler_Env-env:latest") | |
| >>> try: | |
| ... result = client.reset() | |
| ... result = client.step(JobSchedulerEnvAction(message="Test")) | |
| ... finally: | |
| ... client.close() | |
| """ | |
| def _step_payload(self, action: JobSchedulerEnvAction) -> Dict: | |
| """ | |
| Convert JobSchedulerEnvAction to JSON payload for step message. | |
| Args: | |
| action: JobSchedulerEnvAction instance | |
| Returns: | |
| Dictionary representation suitable for JSON encoding | |
| """ | |
| return { | |
| "action": action.action, | |
| } | |
| def _parse_result(self, payload: Dict) -> StepResult[JobSchedulerEnvObservation]: | |
| """ | |
| Parse server response into StepResult[JobSchedulerEnvObservation]. | |
| Args: | |
| payload: JSON response data from server | |
| Returns: | |
| StepResult with JobSchedulerEnvObservation | |
| """ | |
| obs_data = payload.get("observation", {}) | |
| observation = JobSchedulerEnvObservation( | |
| current_time=obs_data.get("current_time", 0), | |
| job_info=obs_data.get("job_info", []), | |
| machine_info=obs_data.get("machine_info", []), | |
| llm_description=obs_data.get("llm_description", ""), | |
| done=payload.get("done", False), | |
| reward=payload.get("reward", 0), | |
| ) | |
| return StepResult( | |
| observation=observation, | |
| reward=payload.get("reward"), | |
| done=payload.get("done", False), | |
| ) | |
| def _parse_state(self, payload: Dict) -> State: | |
| """ | |
| Parse server response into State object. | |
| Args: | |
| payload: JSON response from state request | |
| Returns: | |
| State object with episode_id and step_count | |
| """ | |
| return State( | |
| episode_id=payload.get("episode_id"), | |
| step_count=payload.get("step_count", 0), | |
| ) | |