Fix stateful HTTP endpoints and add HF Spaces deployment config

- Add HF Spaces YAML frontmatter to README.md (sdk: docker, app_port: 8000)
- Rewrite app.py to use stateful shared environment instance instead of
framework's stateless per-request design
- Fix inference.py step payload to use {"action": {"command": ...}} format

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

README.md

@@ -1,3 +1,12 @@
+---
+title: DataCleanEnv
+emoji: 🧹
+colorFrom: blue
+colorTo: green
+sdk: docker
+app_port: 8000
+---
+
 # DataCleanEnv — Data Quality Analysis & Cleaning Environment
 
 A real-world OpenEnv environment where AI agents learn to identify and fix data quality issues through iterative inspection, correction, and validation.

data_clean_env/server/app.py

@@ -1,6 +1,9 @@
 """FastAPI application for the DataClean Environment."""
 
-from openenv.core.env_server.http_server import create_app
+from fastapi import FastAPI, Body
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel
+from typing import Any, Dict, List, Optional
 
 try:
     from .environment import DataCleanEnvironment
@@ -11,12 +14,72 @@ except ImportError:
     from server.environment import DataCleanEnvironment
     from models import DataCleanAction, DataCleanObservation
 
-app = create_app(
-    DataCleanEnvironment,
-    DataCleanAction,
-    DataCleanObservation,
-    env_name="data_clean_env",
-)
+app = FastAPI(title="DataCleanEnv", version="1.0.0")
+
+# Shared stateful environment instance
+_env = DataCleanEnvironment()
+
+
+# ---------------------------------------------------------------------------
+# Request / response models
+# ---------------------------------------------------------------------------
+class ResetRequest(BaseModel):
+    task_id: str = "customer_contacts"
+    seed: Optional[int] = None
+    episode_id: Optional[str] = None
+    model_config = {"extra": "allow"}
+
+
+class StepRequest(BaseModel):
+    action: Dict[str, Any]
+    model_config = {"extra": "allow"}
+
+
+def _obs_dict(obs: DataCleanObservation) -> dict:
+    return obs.model_dump()
+
+
+# ---------------------------------------------------------------------------
+# Endpoints
+# ---------------------------------------------------------------------------
+@app.get("/health")
+async def health():
+    return {"status": "ok"}
+
+
+@app.post("/reset")
+async def reset(request: ResetRequest = Body(default_factory=ResetRequest)):
+    obs = _env.reset(seed=request.seed, episode_id=request.episode_id, task_id=request.task_id)
+    return {"observation": _obs_dict(obs), "reward": None, "done": False}
+
+
+@app.post("/step")
+async def step(request: StepRequest):
+    action = DataCleanAction(**request.action)
+    obs = _env.step(action)
+    return {"observation": _obs_dict(obs), "reward": obs.reward, "done": obs.done}
+
+
+@app.get("/state")
+async def state():
+    return _env.state.model_dump()
+
+
+@app.get("/metadata")
+async def metadata():
+    return {
+        "env_name": "data_clean_env",
+        "action_schema": DataCleanAction.model_json_schema(),
+        "observation_schema": DataCleanObservation.model_json_schema(),
+    }
+
+
+@app.get("/schema")
+async def schema():
+    return {
+        "action": DataCleanAction.model_json_schema(),
+        "observation": DataCleanObservation.model_json_schema(),
+    }
 
 
 def main():

inference.py

@@ -94,7 +94,7 @@ def env_step(command: str) -> Dict[str, Any]:
     """Execute a command in the environment."""
     resp = requests.post(
         f"{ENV_URL}/step",
-        json={"command": command},
+        json={"action": {"command": command}},
         timeout=30,
     )
     resp.raise_for_status()