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---
## Base Classes (from `openenv.core.env_server`)
### Action
```python
from openenv.core.env_server import Action
class Action(BaseModel):
model_config = ConfigDict(extra="forbid")
metadata: Dict[str, Any] = Field(default_factory=dict)
```
### Observation
```python
from openenv.core.env_server import Observation
class Observation(BaseModel):
model_config = ConfigDict(extra="forbid")
done: bool = Field(default=False)
reward: bool | int | float | None = Field(default=None)
metadata: Dict[str, Any] = Field(default_factory=dict)
```
### State
```python
from openenv.core.env_server import State
class State(BaseModel):
model_config = ConfigDict(extra="allow") # NOTE: allows extra fields
episode_id: Optional[str] = Field(default=None)
step_count: int = Field(default=0, ge=0)
```
---
## Environment Base Class
```python
from openenv.core.env_server.interfaces import Environment
class Environment(ABC, Generic[ActT, ObsT, StateT]):
SUPPORTS_CONCURRENT_SESSIONS: bool = False
rubric: Optional[Rubric] = None
def __init__(self, transform=None, rubric=None): ...
# --- YOU MUST IMPLEMENT THESE ---
@abstractmethod
def reset(self, seed=None, episode_id=None, **kwargs) -> ObsT: ...
@abstractmethod
def step(self, action: ActT, timeout_s=None, **kwargs) -> ObsT: ...
@property
@abstractmethod
def state(self) -> StateT: ...
# --- OPTIONAL OVERRIDES ---
def get_metadata(self) -> EnvironmentMetadata: ...
def close(self): ...
# --- BUILT-IN HELPERS ---
def _apply_transform(self, observation): ...
def _apply_rubric(self, action, observation) -> float: ...
def _reset_rubric(self): ...
```
---
## EnvClient Base Class
```python
from openenv.core.env_client import EnvClient
class EnvClient(ABC, Generic[ActT, ObsT, StateT]):
def __init__(self, base_url, connect_timeout_s=10.0,
message_timeout_s=60.0, max_message_size_mb=100.0,
provider=None, mode=None): ...
# --- YOU MUST IMPLEMENT THESE ---
@abstractmethod
def _step_payload(self, action: ActT) -> Dict[str, Any]: ...
@abstractmethod
def _parse_result(self, payload: Dict[str, Any]) -> StepResult[ObsT]: ...
@abstractmethod
def _parse_state(self, payload: Dict[str, Any]) -> StateT: ...
# --- PROVIDED (don't override) ---
async def reset(**kwargs) -> StepResult[ObsT]: ...
async def step(action, **kwargs) -> StepResult[ObsT]: ...
async def state() -> StateT: ...
def sync() -> SyncEnvClient: ... # synchronous wrapper
# --- FACTORY METHODS ---
@classmethod
async def from_docker_image(cls, image, provider=None, **kwargs): ...
@classmethod
async def from_env(cls, repo_id, use_docker=True, ...): ...
```
---
## StepResult
```python
from openenv.core.client_types import StepResult
@dataclass
class StepResult(Generic[ObsT]):
observation: ObsT
reward: Optional[float] = None
done: bool = False
```
---
## Server Factory
```python
from openenv.core.env_server import create_app
app = create_app(
env=MyEnvironment, # Environment CLASS (not instance)
action_cls=MyAction, # Action subclass
observation_cls=MyObservation, # Observation subclass
env_name="my_env", # optional
max_concurrent_envs=1, # optional
)
```
**Auto-generated endpoints:**
| Endpoint | Method | Purpose |
|----------|--------|---------|
| `/reset` | POST | Initialize new episode |
| `/step` | POST | Execute action |
| `/state` | GET | Get current state |
| `/health` | GET | Health check |
| `/metadata` | GET | Environment info |
| `/schema` | GET | JSON schemas |
| `/ws` | WS | WebSocket sessions |
| `/mcp` | POST | MCP JSON-RPC |
| `/docs` | GET | Swagger UI |
---
## Rubric Base Class
```python
from openenv.core.rubrics.base import Rubric
class Rubric(ABC):
last_score: float
@abstractmethod
def forward(self, action, observation) -> float: ...
def reset(self): ...
def state_dict(self) -> dict: ...
def load_state_dict(self, state_dict): ...
```
---
## openenv.yaml Format
```yaml
spec_version: 1
name: my_env
type: space
runtime: fastapi
app: server.app:app
port: 8000
```
---
## CLI Commands
```bash
openenv init my_env # scaffold project
openenv validate # validate locally
openenv validate --url https://space.hf.space # validate remote
openenv push --repo-id user/my-env # deploy to HF Spaces
```
---
## Project Structure (from openenv init)
```
my_env/
βββ __init__.py # exports
βββ models.py # Action, Observation, State
βββ client.py # EnvClient subclass
βββ openenv.yaml # manifest
βββ pyproject.toml # deps
βββ inference.py # baseline (hackathon requirement)
βββ README.md
βββ server/
βββ __init__.py
βββ environment.py # Environment subclass
βββ app.py # create_app()
βββ requirements.txt
βββ Dockerfile
```
---
## Dependencies (openenv-core 0.2.3)
```
# Core
fastapi>=0.104.0
pydantic>=2.0.0
uvicorn>=0.24.0
requests>=2.25.0
websockets>=15.0.1
httpx>=0.28.1
# CLI
typer>=0.9.0
rich>=13.0.0
pyyaml>=6.0
huggingface_hub>=0.20.0
openai>=2.7.2
tomli>=2.3.0
tomli-w>=1.2.0
# MCP + UI
fastmcp>=3.0.0
gradio>=4.0.0
```
Python >= 3.10 required.
---
## Sync Usage Pattern (for inference.py)
```python
from my_env import MyEnv, MyAction
with MyEnv(base_url="https://your-space.hf.space").sync() as env:
result = env.reset()
observation = result.observation
result = env.step(MyAction(field="value"))
print(result.observation)
print(result.reward)
print(result.done)
state = env.state()
print(state.episode_id, state.step_count)
```
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