| """HR Onboarding/Offboarding Environment Client.""" |
|
|
| from typing import Dict |
|
|
| from openenv.core.client_types import StepResult |
| from openenv.core.env_server.types import State |
| from openenv.core import EnvClient |
|
|
| from .models import HROnboardingAction, HROnboardingObservation |
|
|
|
|
| class HROnboardingEnv( |
| EnvClient[HROnboardingAction, HROnboardingObservation] |
| ): |
| """ |
| Client for the HR Onboarding/Offboarding Environment. |
| |
| Maintains a persistent WebSocket connection to the environment server. |
| Each client instance has its own dedicated environment session. |
| |
| Example: |
| >>> with HROnboardingEnv(base_url="http://localhost:7860") as client: |
| ... result = client.reset() |
| ... print(result.observation.instruction) |
| ... |
| ... result = client.step(HROnboardingAction( |
| ... tool_name="hr_read_employee", |
| ... arguments={"emp_id": "emp_0001"} |
| ... )) |
| ... print(result.observation.tool_result) |
| |
| Example with Docker: |
| >>> client = HROnboardingEnv.from_docker_image("hr-onboarding-env:latest") |
| >>> try: |
| ... result = client.reset() |
| ... result = client.step(HROnboardingAction( |
| ... tool_name="hr_search_employees", |
| ... arguments={"department": "Engineering"} |
| ... )) |
| ... finally: |
| ... client.close() |
| """ |
|
|
| def _step_payload(self, action: HROnboardingAction) -> Dict: |
| """Convert HROnboardingAction to JSON payload for step message.""" |
| return { |
| "tool_name": action.tool_name, |
| "arguments": action.arguments, |
| } |
|
|
| def _parse_result(self, payload: Dict) -> StepResult[HROnboardingObservation]: |
| """Parse server response into StepResult[HROnboardingObservation].""" |
| obs_data = payload.get("observation", {}) |
| observation = HROnboardingObservation( |
| task_id=obs_data.get("task_id", ""), |
| instruction=obs_data.get("instruction", ""), |
| tool_name=obs_data.get("tool_name", ""), |
| tool_result=obs_data.get("tool_result", {}), |
| step=obs_data.get("step", 0), |
| max_steps=obs_data.get("max_steps", 15), |
| available_tools=obs_data.get("available_tools", []), |
| done=payload.get("done", False), |
| reward=payload.get("reward"), |
| metadata=obs_data.get("metadata", {}), |
| ) |
|
|
| 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.""" |
| return State( |
| episode_id=payload.get("episode_id"), |
| step_count=payload.get("step_count", 0), |
| ) |
|
|