import logging
from typing import Any

import boto3
from orchestration.sal_orchestrator import (
    SALOrchestrator,
)
from infrastructure.s3.csv_s3_client import CsvS3Client
from repositories.unstandardised_address.unstandardised_address_list_csv_s3_repository import (
    UnstandardisedAddressListCsvS3Repository,
)
from domain.addresses.unstandardised_address import AddressList
from domain.sal.column_classifier import ColumnClassifier
from domain.sal.property_type import PropertyType
from domain.sal.wall_type import WallType
from infrastructure.chatgpt.chatgpt import ChatGPT
from infrastructure.chatgpt.chatgpt_column_classifier import (
    ChatGptColumnClassifier,
)

logger = logging.getLogger(__name__)


def handler(
    body: dict[str, Any],
    context: Any,
) -> dict[str, list[str]]:

    s3_uri = "s3://retrofit-data-dev/bulk_onboarding_inputs/hyde2 (1).csv"
    bucket = "retrofit-data-dev"

    # boto3.client is overloaded per-service in the installed stubs; cast
    # to Any so the strict-mode checker treats it as opaque.
    boto3_client: Any = boto3.client  # noqa
    boto_s3: Any = boto3_client("s3")

    csv_client = CsvS3Client(boto_s3, bucket)
    unstandardised_address_repo = UnstandardisedAddressListCsvS3Repository(
        csv_client, bucket
    )

    # One ChatGPT-backed classifier per landlord-CSV column, keyed by column name.
    chat_gpt = ChatGPT()
    classifiers: dict[str, ColumnClassifier[Any]] = {
        "Property Type": ChatGptColumnClassifier(
            chat_gpt, PropertyType, PropertyType.UNKNOWN
        ),
        "Walls": ChatGptColumnClassifier(chat_gpt, WallType, WallType.UNKNOWN),
    }

    sal = SALOrchestrator(
        unstandardised_address_repo=unstandardised_address_repo,
        classifiers=classifiers,
    )

    addressList: AddressList = sal.get_unstandardised_addresses(input_s3_uri=s3_uri)

    # Cap the batch to the first 20 while the ChatGPT path is under test.
    addressList = AddressList(addressList[:20])

    classified = sal.classify_columns(addressList)
    for column, mapping in classified.items():
        logger.info(
            "Classified %d descriptions for column %r.", len(mapping), column
        )

    # TODO: persist `classified` to landlord overrides.

    return {"hello": ["200"]}