from fastapi import APIRouter, Request
from fastapi.responses import JSONResponse
import logging
from pydantic import BaseModel
import json
from typing import Dict, List
from datetime import datetime, timezone

from dependences.utils import (
    disclaim_bool_string,
    prepare_output_folder,
    create_folder,
    db_persistence_insert,
)
from dependences.image_extractor import ImageExtractor
from dependences.mllm_management import MLLMManager, parse_mllm_alt_text_response

invalid_json_input_msg = "Invalid JSON format"
unexpected_error_msg = "Unexpected Error: could not end the process"


class ExtractImages(BaseModel):
    page_url: str = "https://www.bbc.com"
    number_of_images: int = 10


class ExtractImagesRoutes:

    def __init__(self):

        self.router = APIRouter()

        self.router.add_api_route(
            "/extract_images",
            self.extract_images,
            methods=["POST"],
            tags=["Basic Elaboration"],
            description="extract images from a webpage",
            name="Extract images and context",
            dependencies=[],
        )

        logging.info("extract images routes correctly initialized.")

    async def extract_images(
        self, request: Request, data: ExtractImages
    ) -> JSONResponse:
        """Return the alt text validation  assessment based on WCAG guidelines"""
        print("Received extract images request.")
        try:
            json_content = json.loads(data.model_dump_json())

            # ---------------------

            # Create extractor
            image_extractor = ImageExtractor(
                json_content["page_url"],
                context_levels=0,
                pixel_distance_threshold=0,
                number_of_images=json_content["number_of_images"],
                save_images="False",
                save_images_path="",
            )
            # Extract images
            logging.info(f"Extracting images from: {json_content['page_url']}")
            images = await image_extractor.extract_images(extract_context=False)

            returned_object = {
                "images": images,
            }

            return JSONResponse(content=returned_object, status_code=200)

        except json.JSONDecodeError:
            logging.error(invalid_json_input_msg)
            return JSONResponse(
                content={"error": invalid_json_input_msg}, status_code=400
            )

        except Exception as e:
            logging.error(unexpected_error_msg + " %s", e)
            return JSONResponse(
                content={"error": unexpected_error_msg}, status_code=500
            )