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# 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.
"""Counsel 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 CounselAction, CounselObservation, CounselState
class CounselEnv(
EnvClient[CounselAction, CounselObservation, CounselState]
):
"""
Client for the Counsel 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 CounselEnv(base_url="http://localhost:8000") as client:
... result = client.reset()
... print(result.observation.echoed_message)
...
... result = client.step(CounselAction(message="Hello!"))
... print(result.observation.echoed_message)
Example with Docker:
>>> # Automatically start container and connect
>>> client = CounselEnv.from_docker_image("counsel_env-env:latest")
>>> try:
... result = client.reset()
... result = client.step(CounselAction(message="Test"))
... finally:
... client.close()
"""
def _step_payload(self, action: CounselAction) -> Dict:
"""
Convert CounselAction to JSON payload for step message.
Args:
action: CounselAction instance
Returns:
Dictionary representation suitable for JSON encoding
"""
return {
"tool": action.tool,
"text": action.text,
"exhibit_id": action.exhibit_id,
"reason": action.reason,
}
def _parse_result(self, payload: Dict) -> StepResult[CounselObservation]:
"""
Parse server response into StepResult[CounselObservation].
Args:
payload: JSON response data from server
Returns:
StepResult with CounselObservation
"""
obs_data = payload.get("observation", {})
observation = CounselObservation(
witness_response=obs_data.get("witness_response", ""),
available_evidence=obs_data.get("available_evidence", []),
evidence_descriptions=obs_data.get("evidence_descriptions", {}),
questions_remaining=obs_data.get("questions_remaining", 0),
transcript_tail=obs_data.get("transcript_tail", ""),
case_brief=obs_data.get("case_brief", ""),
case_id=obs_data.get("case_id", ""),
difficulty=obs_data.get("difficulty", ""),
done=obs_data.get("done", payload.get("done", False)),
reward=obs_data.get("reward", payload.get("reward", 0.0)),
reward_components=obs_data.get("reward_components", {}),
)
return StepResult(
observation=observation,
reward=observation.reward,
done=observation.done,
)
def _parse_state(self, payload: Dict) -> CounselState:
"""
Parse server response into State object.
Args:
payload: JSON response from state request
Returns:
State object with episode_id and step_count
"""
data = payload.get("data", payload)
return CounselState(
case_id=data.get("case_id", ""),
difficulty=data.get("difficulty", ""),
contradictions_total=data.get("contradictions_total", 0),
contradictions_triggered=data.get("contradictions_triggered", 0),
contradictions_surfaced=data.get("contradictions_surfaced", 0),
questions_used=data.get("questions_used", 0),
action_count=data.get("action_count", data.get("step_count", 0)),
duplicate_question_count=data.get("duplicate_question_count", 0),
irrelevant_question_count=data.get("irrelevant_question_count", 0),
inadmissible_count=data.get("inadmissible_count", 0),
evidence_timing_successes=data.get("evidence_timing_successes", 0),
step_count=data.get("step_count", data.get("action_count", 0)),
)
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