from fastapi import APIRouter, HTTPException, BackgroundTasks
from app.schemas.request import TrainingRequest
from app.schemas.response import TrainingResponse
from app.utils.model_loader import model_loader
from mlpipeline.pipeline.training_pipeline import TrainingPipeline

router = APIRouter(prefix="/train", tags=["training"])


def run_training_task():
    try:
        pipeline = TrainingPipeline()
        artifact = pipeline.run_pipeline()
        model_loader.reload_model()
        return artifact
    except Exception as e:
        raise e


@router.post("/", response_model=TrainingResponse)
async def trigger_training(request: TrainingRequest, background_tasks: BackgroundTasks):
    try:
        if request.force_retrain:
            background_tasks.add_task(run_training_task)
            return TrainingResponse(
                status="training_started",
                message="Training pipeline started in background"
            )
        else:
            artifact = run_training_task()
            return TrainingResponse(
                status="completed",
                message="Training completed successfully",
                model_path=artifact.pushed_model_path
            )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


@router.post("/reload", response_model=TrainingResponse)
async def reload_model():
    try:
        model_loader.reload_model()
        return TrainingResponse(
            status="success",
            message="Model reloaded successfully"
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))