from abc import ABC, abstractmethod, abstractproperty
from typing import Dict, Any, List

from flask import current_app
from eveai_chat_workers.retrievers.retriever_typing import RetrieverResult, RetrieverArguments
from config.logging_config import TuningLogger


class BaseRetriever(ABC):
    """Base class for all retrievers"""

    def __init__(self, tenant_id: int, retriever_id: int):
        self.tenant_id = tenant_id
        self.retriever_id = retriever_id
        self.tuning = False
        self.tuning_logger = None
        self._setup_tuning_logger()

    @property
    @abstractmethod
    def type(self) -> str:
        """The type of the retriever"""
        pass

    def _setup_tuning_logger(self):
        try:
            self.tuning_logger = TuningLogger(
                'tuning',
                tenant_id=self.tenant_id,
                retriever_id=self.retriever_id,
            )
            # Verify logger is working with a test message
            if self.tuning:
                self.tuning_logger.log_tuning('retriever', "Tuning logger initialized")
        except Exception as e:
            current_app.logger.error(f"Failed to setup tuning logger: {str(e)}")
            raise

    def log_tuning(self, message: str, data: Dict[str, Any] = None) -> None:
        if self.tuning and self.tuning_logger:
            try:
                self.tuning_logger.log_tuning('retriever', message, data)
            except Exception as e:
                current_app.logger.error(f"Processor: Error in tuning logging: {e}")

    @abstractmethod
    def retrieve(self, arguments: RetrieverArguments) -> List[RetrieverResult]:
        """
        Retrieve relevant documents based on provided arguments

        Args:
            arguments: Dictionary of arguments for the retrieval operation

        Returns:
            List[Dict[str, Any]]: List of retrieved documents/content
        """
        pass