Source code for pyrit.models.data_type_serializer

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

from __future__ import annotations

import abc
import base64
import hashlib
import os
import time
from mimetypes import guess_type
from pathlib import Path
from typing import TYPE_CHECKING, Optional, Union
from urllib.parse import urlparse

from pyrit.models.literals import PromptDataType
from pyrit.models.storage_io import DiskStorageIO

if TYPE_CHECKING:
    from pyrit.memory import MemoryInterface




def data_serializer_factory(
    *,
    data_type: PromptDataType,
    value: Optional[str] = None,
    extension: Optional[str] = None,
):
    if value is not None:
        if data_type == "text":
            return TextDataTypeSerializer(prompt_text=value)
        elif data_type == "image_path":
            return ImagePathDataTypeSerializer(prompt_text=value, extension=extension)
        elif data_type == "audio_path":
            return AudioPathDataTypeSerializer(prompt_text=value, extension=extension)
        elif data_type == "error":
            return ErrorDataTypeSerializer(prompt_text=value)
        elif data_type == "url":
            return URLDataTypeSerializer(prompt_text=value, extension=extension)
        else:
            raise ValueError(f"Data type {data_type} not supported")
    else:
        if data_type == "image_path":
            return ImagePathDataTypeSerializer(extension=extension)
        elif data_type == "audio_path":
            return AudioPathDataTypeSerializer(extension=extension)
        elif data_type == "error":
            return ErrorDataTypeSerializer(prompt_text="")
        else:
            raise ValueError(f"Data type {data_type} without prompt text not supported")





class DataTypeSerializer(abc.ABC):
    """
    Abstract base class for data type normalizers.

    Responsible for reading and saving multi-modal data types to local disk or Azure Storage Account.
    """

    data_type: PromptDataType
    value: str
    data_sub_directory: str
    file_extension: str

    _file_path: Union[Path, str] = None

    @property
    def _memory(self) -> MemoryInterface:
        from pyrit.memory import CentralMemory

        return CentralMemory.get_memory_instance()

    def _get_storage_io(self):
        """
        Retrieve the input datasets storage handle.

        Returns:
        StorageIO: An instance of DiskStorageIO or AzureBlobStorageIO based on the storage configuration.

        Raises:
            ValueError: If the Azure Storage URL is detected but the datasets storage handle is not set.
        """
        if self._is_azure_storage_url(self.value):
            return self._memory.results_storage_io
        return DiskStorageIO()



    @abc.abstractmethod
    def data_on_disk(self) -> bool:
        """
        Returns True if the data is stored on disk.
        """




    async def save_data(self, data: bytes) -> None:
        """
        Saves the data to storage.
        """
        file_path = await self.get_data_filename()
        await self._memory.results_storage_io.write_file(file_path, data)
        self.value = str(file_path)




    async def save_b64_image(self, data: str, output_filename: str = None) -> None:
        """
        Saves the base64 encoded image to storage.
        Arguments:
            data: string with base64 data
            output_filename (optional, str): filename to store image as. Defaults to UUID if not provided
        """
        file_path = output_filename or await self.get_data_filename()
        image_bytes = base64.b64decode(data)
        await self._memory.results_storage_io.write_file(file_path, image_bytes)
        self.value = str(file_path)




    async def read_data(self) -> bytes:
        """
        Reads the data from the storage.

        Returns:
            bytes: The data read from storage.
        """
        if not self.data_on_disk():
            raise TypeError(f"Data for data Type {self.data_type} is not stored on disk")

        if not self.value:
            raise RuntimeError("Prompt text not set")

        storage_io = self._get_storage_io()
        # Check if path exists
        file_exists = await storage_io.path_exists(path=self.value)
        if not file_exists:
            raise FileNotFoundError(f"File not found: {self.value}")
        # Read the contents from the path
        return await storage_io.read_file(self.value)




    async def read_data_base64(self) -> str:
        """
        Reads the data from the storage.
        """
        byte_array = await self.read_data()
        return base64.b64encode(byte_array).decode("utf-8")




    async def get_sha256(self) -> str:
        input_bytes: bytes = None

        if self.data_on_disk():
            storage_io = self._get_storage_io()
            file_exists = await storage_io.path_exists(self.value)
            if not file_exists:
                raise FileNotFoundError(f"File not found: {self.value}")

            # Read the data from storage
            input_bytes = await storage_io.read_file(self.value)
        else:
            if isinstance(self.value, str):
                input_bytes = self.value.encode("utf-8")
            else:
                raise ValueError(f"Invalid data type {self.value}, expected str data type.")

        hash_object = hashlib.sha256(input_bytes)
        return hash_object.hexdigest()




    async def get_data_filename(self) -> Union[Path, str]:
        """
        Generates or retrieves a unique filename for the data file.
        """
        if self._file_path:
            return self._file_path

        if not self.data_on_disk():
            raise TypeError("Data is not stored on disk")

        if not self.data_sub_directory:
            raise RuntimeError("Data sub directory not set")
        ticks = int(time.time() * 1_000_000)

        results_path = self._memory.results_path

        if self._is_azure_storage_url(results_path):
            full_data_directory_path = results_path + self.data_sub_directory
            self._file_path = full_data_directory_path + f"/{ticks}.{self.file_extension}"
        else:
            full_data_directory_path = results_path + self.data_sub_directory
            await self._memory.results_storage_io.create_directory_if_not_exists(Path(full_data_directory_path))
            self._file_path = Path(full_data_directory_path, f"{ticks}.{self.file_extension}")

        return self._file_path




    @staticmethod
    def get_extension(file_path: str) -> str | None:
        """
        Get the file extension from the file path.
        """
        _, ext = os.path.splitext(file_path)
        return ext if ext else None




    @staticmethod
    def get_mime_type(file_path: str) -> str | None:
        """
        Get the MIME type of the file path.
        """
        mime_type, _ = guess_type(file_path)
        return mime_type


    def _is_azure_storage_url(self, path: str) -> bool:
        """
        Validates if the given path is an Azure Storage URL.

        Args:
            path (str): Path or URL to check.

        Returns:
            bool: True if the path is an Azure Blob Storage URL.
        """
        parsed = urlparse(path)
        return parsed.scheme in ("http", "https") and "blob.core.windows.net" in parsed.netloc





class TextDataTypeSerializer(DataTypeSerializer):


    def __init__(self, *, prompt_text: str):
        self.data_type = "text"
        self.value = prompt_text




    def data_on_disk(self) -> bool:
        return False






class ErrorDataTypeSerializer(DataTypeSerializer):


    def __init__(self, *, prompt_text: str):
        self.data_type = "error"
        self.value = prompt_text




    def data_on_disk(self) -> bool:
        return False




class URLDataTypeSerializer(DataTypeSerializer):
    def __init__(self, *, prompt_text: str, extension: Optional[str] = None):
        self.data_type = "url"
        self.value = prompt_text
        self.data_sub_directory = "/dbdata/urls"
        self.file_extension = extension if extension else "txt"

    def data_on_disk(self) -> bool:
        return True




class ImagePathDataTypeSerializer(DataTypeSerializer):


    def __init__(self, *, prompt_text: Optional[str] = None, extension: Optional[str] = None):
        self.data_type = "image_path"
        self.data_sub_directory = "/dbdata/images"
        self.file_extension = extension if extension else "png"

        if prompt_text:
            self.value = prompt_text




    def data_on_disk(self) -> bool:
        return True






class AudioPathDataTypeSerializer(DataTypeSerializer):


    def __init__(
        self,
        *,
        prompt_text: Optional[str] = None,
        extension: Optional[str] = None,
    ):
        self.data_type = "audio_path"
        self.data_sub_directory = "/dbdata/audio"
        self.file_extension = extension if extension else "mp3"

        if prompt_text:
            self.value = prompt_text




    def data_on_disk(self) -> bool:
        return True