Use get_class_names() to see what’s available, or get_all_registered_class_metadata() for detailed information.
from pyrit.registry import ScenarioRegistry
registry = ScenarioRegistry.get_registry_singleton()
# Get all registered names
names = registry.get_class_names()
print(f"Available scenarios: {names[:5]}...") # Show first 5
# Get detailed metadata
metadata = registry.get_all_registered_class_metadata()
for item in metadata[:2]: # Show first 2
print(f"\n{item.class_name}:")
print(f" Description: {item.class_description[:80]}...")Available scenarios: ['airt.cyber', 'airt.jailbreak', 'airt.leakage', 'airt.psychosocial', 'airt.rapid_response']...
Cyber:
Description: Cyber scenario implementation for PyRIT. This scenario tests how willing models ...
Jailbreak:
Description: Jailbreak scenario implementation for PyRIT. This scenario tests how vulnerable ...
Getting a Class¶
Use get_class() to retrieve a class by name. This returns the class itself, not an instance.
scenario_class = registry.get_class("garak.encoding")
print(f"Got class: {scenario_class}")
print(f"Class name: {scenario_class.__name__}")Got class: <class 'pyrit.scenario.scenarios.garak.encoding.Encoding'>
Class name: Encoding
Creating Instances¶
Once you have a class, instantiate it with your parameters. You can also use create_instance() as a shortcut.
from pyrit.prompt_target import OpenAIChatTarget
from pyrit.setup import IN_MEMORY, initialize_pyrit_async
from pyrit.setup.initializers import LoadDefaultDatasets
await initialize_pyrit_async(memory_db_type=IN_MEMORY, initializers=[LoadDefaultDatasets()]) # type: ignore
target = OpenAIChatTarget()
# Option 1: Get class then instantiate
encoding_class = registry.get_class("garak.encoding")
scenario = encoding_class() # type: ignore
# Set the objective target, then initialize
scenario.set_params_from_args(args={"objective_target": target}) # type: ignore
await scenario.initialize_async() # type: ignore
# Option 2: Use create_instance() shortcut
# scenario = registry.create_instance("garak.encoding", objective_target=my_target, ...)
print("Scenarios can be instantiated with your target and parameters")Found default environment files: ['./.pyrit/.env', './.pyrit/.env.local']
Loaded environment file: ./.pyrit/.env
Loaded environment file: ./.pyrit/.env.local
No new upgrade operations detected.
Scenarios can be instantiated with your target and parameters
Checking Registration¶
Registries support standard Python container operations.
# Check if a name is registered
print(f"'garak.encoding' registered: {'garak.encoding' in registry}")
print(f"'nonexistent' registered: {'nonexistent' in registry}")
# Get count of registered classes
print(f"Total scenarios: {len(registry)}")
# Iterate over names
for name in list(registry)[:3]:
print(f" - {name}")'garak.encoding' registered: True
'nonexistent' registered: False
Total scenarios: 9
- airt.cyber
- airt.jailbreak
- airt.leakage
Using different registries¶
There can be multiple registries. Below is doing a similar thing with the InitializerRegistry.
from pyrit.registry import InitializerRegistry
initializer_registry = InitializerRegistry.get_registry_singleton()
# Get all registered names
initializer_names = initializer_registry.get_class_names()
print(f"Available initializers: {initializer_names[:5]}...") # Show first 5
# Get detailed metadata
for init_item in initializer_registry.get_all_registered_class_metadata()[:2]: # Show first 2
print(f"\n{init_item.registry_name}:")
print(f" Class: {init_item.class_name}")
print(f" Description: {init_item.class_description[:80]}...")Available initializers: ['airt', 'load_default_datasets', 'scenario_objective_list', 'scenario_technique', 'scorer']...
airt:
Class: AIRTInitializer
Description: AIRT (AI Red Team) configuration initializer. This initializer provides a unifie...
load_default_datasets:
Class: LoadDefaultDatasets
Description: Load default datasets for all registered scenarios....