from fastapi import FastAPI
from pydantic import BaseModel
from typing import Optional
import uvicorn

app = FastAPI(title="Enterprise AI API")

class PredictionRequest(BaseModel):
    features: list[float]
    model_version: Optional[str] = "v2.1"

class PredictionResponse(BaseModel):
    prediction: float
    confidence: float
    model_used: str
    processing_time_ms: float

@app.post("/api/v2/predict", response_model=PredictionResponse)
async def predict(request: PredictionRequest):
    """Enterprise-grade ML prediction endpoint"""

    import time
    start = time.time()

    # Load model based on version
    model = load_model(request.model_version)

    # Run prediction with monitoring
    prediction, confidence = await model.predict_async(
        request.features,
        return_confidence=True
    )

    processing_time = (time.time() - start) * 1000

    # Log prediction for monitoring
    log_prediction(
        features=request.features,
        result=prediction,
        model_version=request.model_version,
        processing_time=processing_time
    )

    return PredictionResponse(
        prediction=float(prediction),
        confidence=float(confidence),
        model_used=request.model_version,
        processing_time_ms=processing_time
    )