Source code for pyrit.models.seeds.seed

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

"""
Base Seed class for representing seed data with various attributes and metadata.

This module is the foundation for all seed types in PyRIT.
"""

from __future__ import annotations

import abc
import logging
import re
import uuid
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, Iterator, Optional, Sequence, TypeVar, Union

from jinja2 import BaseLoader, Environment, StrictUndefined, Template, Undefined

from pyrit.common.yaml_loadable import YamlLoadable
from pyrit.models.literals import PromptDataType

logger = logging.getLogger(__name__)

# TypeVar for generic return type in class methods
T = TypeVar("T", bound="Seed")


class PartialUndefined(Undefined):
    # Return the original placeholder format
    def __str__(self) -> str:
        return f"{{{{ {self._undefined_name} }}}}" if self._undefined_name else ""

    def __repr__(self) -> str:
        return f"{{{{ {self._undefined_name} }}}}" if self._undefined_name else ""

    def __iter__(self) -> Iterator[object]:
        """Return an empty iterator to prevent Jinja from trying to loop over undefined variables."""
        return iter([])

    def __bool__(self) -> bool:
        return True  # Ensures it doesn't evaluate to False


[docs] @dataclass class Seed(YamlLoadable): """Represents seed data with various attributes and metadata.""" # The actual prompt value, which can be a string or a file path value: str # SHA256 hash of the value, used for deduplication value_sha256: Optional[str] = None # Unique identifier for the prompt id: Optional[uuid.UUID] = field(default_factory=lambda: uuid.uuid4()) # Name of the prompt name: Optional[str] = None # Name of the dataset this prompt belongs to dataset_name: Optional[str] = None # Categories of harm associated with this prompt harm_categories: Optional[Sequence[str]] = field(default_factory=lambda: []) # Description of the prompt description: Optional[str] = None # Authors of the prompt authors: Optional[Sequence[str]] = field(default_factory=lambda: []) # Groups affiliated with the prompt groups: Optional[Sequence[str]] = field(default_factory=lambda: []) # Source of the prompt source: Optional[str] = None # Date when the prompt was added to the dataset date_added: Optional[datetime] = field(default_factory=lambda: datetime.now()) # User who added the prompt to the dataset added_by: Optional[str] = None # Arbitrary metadata that can be attached to the prompt metadata: Optional[Dict[str, Union[str, int]]] = field(default_factory=lambda: {}) # Unique identifier for the prompt group prompt_group_id: Optional[uuid.UUID] = None # Alias for the prompt group prompt_group_alias: Optional[str] = None @property def data_type(self) -> PromptDataType: """ Return the data type for this seed. Base implementation returns 'text'. SeedPrompt overrides this to support multiple data types (image_path, audio_path, etc.). """ return "text"
[docs] def render_template_value(self, **kwargs: Any) -> str: """ Renders self.value as a template, applying provided parameters in kwargs. Args: kwargs:Key-value pairs to replace in the SeedPrompt value. Returns: A new prompt with the parameters applied. Raises: ValueError: If parameters are missing or invalid in the template. """ template_identifier = self.name or "<unnamed template>" try: jinja_template = Template(self.value, undefined=StrictUndefined) return jinja_template.render(**kwargs) except Exception as e: raise ValueError( f"Error rendering template '{template_identifier}': {str(e)}. " f"Template value preview: {self.value[:100]}..." ) from e
[docs] def render_template_value_silent(self, **kwargs: Any) -> str: """ Renders self.value as a template, applying provided parameters in kwargs. For parameters in the template that are not provided as kwargs here, this function will leave them as is instead of raising an error. Args: kwargs: Key-value pairs to replace in the SeedPrompt value. Returns: A new prompt with the parameters applied. Raises: ValueError: If parameters are missing or invalid in the template. """ # Check if the template contains Jinja2 control structures (for loops, if statements, etc.) # If it does, and we don't have all required parameters, don't render it to preserve the structure has_control_structures = bool(re.search(r"\{%[-\s]*(for|if|block|macro|call)", self.value)) if has_control_structures: # Check if all parameters in control structures are provided # Extract variable names from {% for var in collection %} patterns for_vars = re.findall(r"\{%[-\s]*for\s+\w+\s+in\s+(\w+)", self.value) if any(var not in kwargs for var in for_vars): # Don't render if we're missing loop collection variables - preserve the template as-is return self.value # Create a Jinja template with PartialUndefined placeholders env = Environment(loader=BaseLoader, undefined=PartialUndefined) # type: ignore jinja_template = env.from_string(self.value) try: # Render the template with the provided kwargs return jinja_template.render(**kwargs) except Exception as e: logging.error("Error rendering template: %s", e) return self.value
[docs] async def set_sha256_value_async(self) -> None: """ This method computes the SHA256 hash value asynchronously. It should be called after prompt `value` is serialized to text, as file paths used in the `value` may have changed from local to memory storage paths. Note, this method is async due to the blob retrieval. And because of that, we opted to take it out of main and setter functions. The disadvantage is that it must be explicitly called. """ from pyrit.models.data_type_serializer import data_serializer_factory original_serializer = data_serializer_factory( category="seed-prompt-entries", data_type=self.data_type, value=self.value ) self.value_sha256 = await original_serializer.get_sha256()
[docs] @classmethod @abc.abstractmethod def from_yaml_with_required_parameters( cls, template_path: Union[str, Path], required_parameters: list[str], error_message: Optional[str] = None, ) -> Seed: """ Load a Seed from a YAML file and validate that it contains specific parameters. Args: template_path: Path to the YAML file containing the template. required_parameters: List of parameter names that must exist in the template. error_message: Custom error message if validation fails. If None, a default message is used. Returns: Seed: The loaded and validated seed of the specific subclass type. """