import time
import logging
from fastapi import APIRouter, HTTPException
from app.salary_analytics.services.main import SalaryAnalyticsPipeline
from app.salary_analytics.helpers.data_checks import check_data_loaded
from app.salary_analytics.helpers.response_helpers import AnalysisResponse
from app.salary_analytics.core.state import state
from app.utils.logger import logger



router = APIRouter()


@router.post("/train/models", response_model=AnalysisResponse)
async def train_models():
    """Train salary prediction models."""
    start_time = time.time()
    try:
        check_data_loaded()
        logger.info("Starting model training...")
        state.pipeline.train_salary_prediction_models()
        logger.info("Models trained successfully")
        response = AnalysisResponse(
            message="Models trained successfully"
        )
        logger.info(f"Model training endpoint completed in {time.time() - start_time:.2f} seconds")
        return response
    except Exception as e:
        logger.error(f"Error in model training: {str(e)}")
        logger.info(f"Model training endpoint failed after {time.time() - start_time:.2f} seconds")
        raise HTTPException(status_code=500, detail=str(e))