Listing Available Classes - PyRIT Documentation

Use get_class_names() to see what’s available, or get_all_registered_class_metadata() for detailed information.

from pyrit.registry import ScenarioRegistry
from pyrit.setup import IN_MEMORY, initialize_pyrit_async
from pyrit.setup.initializers import LoadDefaultDatasets, TechniqueInitializer

dataset_initializer = LoadDefaultDatasets()
dataset_initializer.set_params_from_args(args={"dataset_names": ["garak_slur_terms_en", "garak_web_html_js"]})
await initialize_pyrit_async(
    memory_db_type=IN_MEMORY,
    initializers=[TechniqueInitializer(), dataset_initializer],
)  # type: ignore

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

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....