# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

import logging
import pathlib
import textwrap

from pyrit.common.apply_defaults import REQUIRED_VALUE, apply_defaults
from pyrit.common.path import CONVERTER_SEED_PROMPT_PATH
from pyrit.converter.llm_generic_text_converter import LLMGenericTextConverter
from pyrit.models import ComponentIdentifier, SeedPrompt
from pyrit.prompt_target import PromptTarget

logger = logging.getLogger(__name__)


class NoiseConverter(LLMGenericTextConverter):
    """
    Injects noise errors into a conversation using an LLM.

    An existing ``PromptTarget`` is used to perform the conversion (like Azure OpenAI).
    """

    @apply_defaults
    def __init__(
        self,
        *,
        converter_target: PromptTarget = REQUIRED_VALUE,  # type: ignore[ty:invalid-parameter-default]
        noise: str | None = None,
        number_errors: int = 5,
        prompt_template: SeedPrompt | None = None,
    ) -> None:
        """
        Initialize the converter with the specified parameters.

        Args:
            converter_target (PromptTarget): The endpoint that converts the prompt.
                Can be omitted if a default has been configured via PyRIT initialization.
            noise (str): The noise to inject. Grammar error, delete random letter, insert random space, etc.
            number_errors (int): The number of errors to inject.
            prompt_template (SeedPrompt, Optional): The prompt template for the conversion.
        """
        # set to default strategy if not provided
        prompt_template = (
            prompt_template
            if prompt_template
            else SeedPrompt.from_yaml_file(pathlib.Path(CONVERTER_SEED_PROMPT_PATH) / "noise_converter.yaml")
        )

        if not noise:
            noise = textwrap.dedent(
                "Grammar error, Delete random letter, insert random symbol, missing white space, "
                "bad auto-correct, or similar"
            )

        super().__init__(
            converter_target=converter_target,
            system_prompt_template=prompt_template,
            noise=noise,
            number_errors=str(number_errors),
        )
        self._noise = noise
        self._number_errors = number_errors

    def _build_identifier(self) -> ComponentIdentifier:
        """
        Build the converter identifier with noise parameters.

        Returns:
            ComponentIdentifier: The identifier for this converter.
        """
        return self._create_identifier(
            params={
                "noise": self._noise,
                "number_errors": self._number_errors,
            },
            converter_target=self._converter_target.get_identifier(),
        )