⚡ Live Sandbox: AI Dev Tool: Owed a billion dollars

📝 Editable Code Sandbox

```python
# AI Dev Tool: TabPFN API Integration Wrapper
# Description: A production-ready API integration wrapper for TabPFN and TabICL models
# Author: Elite Software Architect and Micro-SaaS Developer

from pydantic import BaseModel
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
from fastapi.encoders import jsonable_encoder
from typing import Optional
import xgboost as xgb
import numpy as np

app = FastAPI()

# Define the request model for TabPFN and TabICL
class TabPFNRequest(BaseModel):
    """Request model for TabPFN and TabICL"""
    data: list
    model_type: str

# Define the response model for TabPFN and TabICL
class TabPFNResponse(BaseModel):
    """Response model for TabPFN and TabICL"""
    prediction: float
    error: Optional[str]

# Load the pre-trained XGBoost model
xgb_model = xgb.Booster()
xgb_model.load_model("xgb_model.json")

# Define the API endpoint for TabPFN and TabICL
@app.post("/tabpfm", response_model=TabPFNResponse)
async def tabpfm(request: TabPFNRequest

🖥️ Interactive Execution Terminal Console

⚡ Ready! Click ▶️ Run Code to execute code in browser terminal...