pyrit.prompt_target.OpenAITarget

class OpenAITarget(*, model_name: str | None = None, endpoint: str | None = None, api_key: str | Callable[[], str | Awaitable[str]] | None = None, headers: str | None = None, max_requests_per_minute: int | None = None, httpx_client_kwargs: dict | None = None, underlying_model: str | None = None)

Bases: PromptChatTarget

Abstract base class for OpenAI-based prompt targets.

This class provides common functionality for interacting with OpenAI API endpoints, handling authentication, rate limiting, and request/response processing.

Read more about the various models here: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models.

__init__(*, model_name: str | None = None, endpoint: str | None = None, api_key: str | Callable[[], str | Awaitable[str]] | None = None, headers: str | None = None, max_requests_per_minute: int | None = None, httpx_client_kwargs: dict | None = None, underlying_model: str | None = None) → None

Initialize an instance of OpenAITarget.

Parameters:

• model_name (str, Optional) – The name of the model (or name of deployment in Azure). If no value is provided, the environment variable will be used (set by subclass).

• endpoint (str, Optional) – The target URL for the OpenAI service.

• api_key (str | Callable[[], str], Optional) – The API key for accessing the OpenAI service, or a callable that returns an access token. For Azure endpoints with Entra authentication, pass a token provider from pyrit.auth (e.g., get_azure_openai_auth(endpoint)). Defaults to the target-specific API key environment variable.

• headers (str, Optional) – Extra headers of the endpoint (JSON).

• max_requests_per_minute (int, Optional) – Number of requests the target can handle per minute before hitting a rate limit. The number of requests sent to the target will be capped at the value provided.

• httpx_client_kwargs (dict, Optional) – Additional kwargs to be passed to the httpx.AsyncClient() constructor.

• underlying_model (str, Optional) – The underlying model name (e.g., “gpt-4o”) used solely for target identifier purposes. This is useful when the deployment name in Azure differs from the actual model. If not provided, will attempt to fetch from environment variable. If it is not there either, the identifier “model_name” attribute will use the model_name. Defaults to None.

Methods

__init__(*[, model_name, endpoint, api_key, ...])	Initialize an instance of OpenAITarget.
dispose_db_engine()	Dispose database engine to release database connections and resources.
get_identifier()	Get an identifier dictionary for this prompt target.
is_json_response_supported()	Abstract method to determine if JSON response format is supported by the target.
is_response_format_json(message_piece)	Check if the response format is JSON and ensure the target supports it.
send_prompt_async(*, message)	Send a normalized prompt async to the prompt target.
set_model_name(*, model_name)	Set the model name for this target.
set_system_prompt(*, system_prompt, ...[, ...])	Set the system prompt for the prompt target.

Attributes

ADDITIONAL_REQUEST_HEADERS
model_name_environment_variable
endpoint_environment_variable
api_key_environment_variable
underlying_model_environment_variable
supported_converters	A list of PromptConverters that are supported by the prompt target.

ADDITIONAL_REQUEST_HEADERS: str = 'OPENAI_ADDITIONAL_REQUEST_HEADERS'

api_key_environment_variable: str

endpoint_environment_variable: str

abstract is_json_response_supported() → bool

Abstract method to determine if JSON response format is supported by the target.

Returns:

True if JSON response is supported, False otherwise.

Return type:

bool

model_name_environment_variable: str

underlying_model_environment_variable: str