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__init__.py

@@ -11,8 +11,12 @@ from .models import (
     GradeResult,
 )
 
+# Backward-compatible alias for legacy modules that still import AutoCleanEnv.
+AutoCleanEnv = DataCleaningEnv
+
 __all__ = [
     "DataCleaningEnv",
+    "AutoCleanEnv",
     "DataCleaningClient",
     "DataCleaningAction",
     "DataCleaningObservation",

server/app.py

@@ -1,81 +1,16 @@
-from fastapi import FastAPI, File, UploadFile, HTTPException
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.staticfiles import StaticFiles
-from fastapi.responses import FileResponse
-import pandas as pd
-import io
-import json
-from inference import AutoCleanAgent
+"""Compatibility shim for the canonical OpenEnv FastAPI app."""
 
-app = FastAPI(title="AutoClean AI PRO API", version="2.0.0")
+try:
+    from ..app import app, startup_event
+except ImportError:  # pragma: no cover - direct execution fallback
+    from env.app import app, startup_event
 
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
 
-app.mount("/static", StaticFiles(directory="static"), name="static")
-
-# Lazy initialized agent - created only on first request
-agent = None
-
-def get_agent():
-    global agent
-    if agent is None:
-        agent = AutoCleanAgent()
-    return agent
-
-
-@app.get("/")
-async def root():
-    return FileResponse('static/index.html')
-
-
-@app.post("/api/clean")
-async def clean_dataset(file: UploadFile = File(...)):
-    try:
-        contents = await file.read()
-        
-        if file.filename.endswith('.csv'):
-            df = pd.read_csv(io.BytesIO(contents))
-        elif file.filename.endswith('.xlsx'):
-            df = pd.read_excel(io.BytesIO(contents))
-        else:
-            raise HTTPException(status_code=400, detail="Unsupported file format")
-            
-        report = get_agent().run(df)
-        
-        return {
-            "success": True,
-            "filename": file.filename,
-            "initial_score": report['initial_score'],
-            "final_score": report['final_score'],
-            "improvement": report['improvement'],
-            "steps": report['steps_taken'],
-            "history": report['history'],
-            "metrics": report['final_metrics'],
-            "cleaned_data": json.loads(report['cleaned_dataset'].to_json(orient='records'))
-        }
-        
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-@app.get("/api/status")
-async def status():
-    return {
-        "status": "online",
-        "version": "2.0.0",
-        "name": "AutoClean AI PRO"
-    }
+def main() -> None:
+    import uvicorn
 
+    uvicorn.run("env.app:app", host="0.0.0.0", port=8000)
 
-def main():
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
 
 if __name__ == "__main__":
     main()