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SRE Incident Investigation Environment — Python Client.
EnvClient is async by default. Use .sync() for synchronous code or
'async with' for async code.
Usage (sync — simplest):
from client import SREEnvClient
from models import SREAction
with SREEnvClient(base_url="http://localhost:8000").sync() as env:
result = env.reset(task_id="sre-easy-001")
result = env.step(SREAction(action_type="query_alerts"))
result = env.step(SREAction(
action_type="submit",
root_cause_service="payment-service",
root_cause_type="resource_exhaustion",
affected_services=["payment-service", "api-gateway", "order-service"],
severity="P2",
recommended_action="Increase JVM heap memory limit",
confidence=0.9,
))
print("Score:", result.observation.grader_score)
Usage (async — for training loops):
import asyncio
from client import SREEnvClient
from models import SREAction
async def main():
async with SREEnvClient(base_url="http://localhost:8000") as env:
result = await env.reset_async(task_id="sre-hard-003")
result = await env.step_async(SREAction(action_type="query_alerts"))
result = await env.step_async(SREAction(
action_type="submit",
root_cause_service="recommendation-service",
root_cause_type="configuration_error",
affected_services=["recommendation-service", "cart-service"],
severity="P1",
recommended_action="Rollback feature flag config",
confidence=0.9,
))
print("Score:", result.observation.grader_score)
asyncio.run(main())
"""
from typing import Dict
from openenv.core import EnvClient
from openenv.core.client_types import StepResult
try:
from .models import SREAction, SREObservation, SREState
except ImportError:
from models import SREAction, SREObservation, SREState
class SREEnvClient(EnvClient[SREAction, SREObservation, SREState]):
"""Typed WebSocket client for the SRE Incident Investigation environment."""
def _step_payload(self, action: SREAction) -> Dict:
payload = {"action_type": action.action_type}
for field in ["service", "log_level", "time_window_minutes", "log_query",
"metric_name", "note", "root_cause_service", "root_cause_type",
"affected_services", "severity", "recommended_action", "confidence"]:
v = getattr(action, field, None)
if v is not None:
payload[field] = v
return payload
def _parse_result(self, payload: Dict) -> "StepResult[SREObservation]":
obs_data = payload.get("observation", payload)
observation = SREObservation(
action_taken=obs_data.get("action_taken", ""),
logs=obs_data.get("logs", []),
metrics=obs_data.get("metrics", []),
metric_name=obs_data.get("metric_name"),
alerts=obs_data.get("alerts", []),
annotation_accepted=obs_data.get("annotation_accepted", False),
grader_score=obs_data.get("grader_score"),
grader_breakdown=obs_data.get("grader_breakdown"),
message=obs_data.get("message", ""),
queries_remaining=obs_data.get("queries_remaining", 0),
done=payload.get("done", obs_data.get("done", False)),
reward=payload.get("reward", obs_data.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) -> SREState:
return SREState(
episode_id=payload.get("episode_id"),
task_id=payload.get("task_id", ""),
difficulty=payload.get("difficulty", ""),
step_count=payload.get("step_count", 0),
queries_used=payload.get("queries_used", 0),
max_queries=payload.get("max_queries", 12),
annotations=payload.get("annotations", []),
submitted=payload.get("submitted", False),
final_score=payload.get("final_score"),
)
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