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client.py — Step 3: Create Client
EnvClient subclass for the Cross-Session Continuity environment.
Connects over HTTP/WebSocket to the OpenEnv FastAPI server.
Usage:
from client import ContinuityEnvClient, ContinuityAction
# Connect to local server
with ContinuityEnvClient(base_url="http://localhost:7860") as client:
obs = client.reset(difficulty="easy", seed=42)
result = client.step(ContinuityAction(tool="run_tests"))
print(result.observation.output)
# Connect to HF Space
with ContinuityEnvClient(
base_url="https://aswini-kumar-cross-session-continuity-env.hf.space"
) as client:
obs = client.reset(difficulty="medium")
"""
from typing import Dict
try:
from openenv.core import EnvClient
from openenv.core.client_types import StepResult
from openenv.core.env_server.types import State
_HAS_OPENENV = True
except ImportError:
_HAS_OPENENV = False
EnvClient = object # type: ignore[misc,assignment]
StepResult = None
State = None
try:
from models import ContinuityAction, ContinuityObservation
except ImportError:
from models import ContinuityAction, ContinuityObservation # type: ignore
class ContinuityEnvClient(EnvClient): # type: ignore[misc]
"""
Client for the Cross-Session Continuity RL Environment.
Wraps the OpenEnv HTTP server with typed Action/Observation classes.
Session flow:
1. reset() → Session 1 starts
2. step(read_file) → read starter code
3. step(write_file) → write partial implementation
4. step(run_tests) → check progress
5. step(write_handoff) → end Session 1
6. step(parse_handoff) → Session 2 cold start
7. step(write_file) → complete implementation
8. step(submit) → scored; done=True
"""
def _step_payload(self, action: ContinuityAction) -> Dict:
return {
"tool": action.tool,
"path": action.path,
"content": action.content,
}
def _parse_result(self, payload: Dict) -> "StepResult":
obs_data = payload.get("observation", {})
observation = ContinuityObservation(
output=obs_data.get("output", ""),
session=obs_data.get("session", 1),
passed=obs_data.get("passed", 0),
total=obs_data.get("total", 0),
auxiliary_reward=obs_data.get("auxiliary_reward", 0.0),
error=obs_data.get("error", ""),
warning=obs_data.get("warning", ""),
message=obs_data.get("message", ""),
retries_left=obs_data.get("retries_left", 3),
done=payload.get("done", False),
reward=payload.get("reward", 0.0),
)
from openenv.core.client_types import StepResult as SR
return SR(
observation=observation,
reward=payload.get("reward", 0.0),
done=payload.get("done", False),
)
def _parse_state(self, payload: Dict) -> "State":
from openenv.core.env_server.types import State as S
return S(
episode_id=payload.get("episode_id", ""),
step_count=payload.get("step_count", 0),
)
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