api.py

from fastapi import FastAPI
from pydantic import BaseModel
from typing import List
import uvicorn
import logging
from datetime import datetime
import pytz
import torch

from main import ImageProcessor

logging.basicConfig(filename="drinksLog.log", filemode='w')
logger = logging.getLogger("drinks")
logger.setLevel(logging.DEBUG)
file_handler = logging.FileHandler("drinksLog.log")
logger.addHandler(file_handler)

app = FastAPI()

class RequestBody(BaseModel):
    fdz: List[str]
    cItem: List[str]

class RequestData(BaseModel):
    body: RequestBody

@app.get("/status")
async def status():
    return {"status": "AI Server is running"}

@app.post("/drinks")
async def detect_items(request_data: RequestData):
    try:
        image_processor = ImageProcessor()  # Initialize the image processor
        fdz_urls = request_data.body.fdz
        citem_urls = request_data.body.cItem

        result = await image_processor.process_images(fdz_urls, citem_urls)

        return {"response": result}

    except Exception as e:
        logger.error(f"Error during detection: {str(e)}")
        return {"error": "An error occurred during detection"}

if __name__ == "__main__":
    try:
        uvicorn.run(app, host="127.0.0.1", port=4444)
    finally:
        torch.cuda.empty_cache()