temporalio.contrib.openai_agents.OpenAIAgentsPlugin

class documentation

class OpenAIAgentsPlugin(temporalio.client.Plugin, temporalio.worker.Plugin): (source)

Constructor: OpenAIAgentsPlugin(model_params, model_provider)

Temporal plugin for integrating OpenAI agents with Temporal workflows.

Warning

This class is experimental and may change in future versions. Use with caution in production environments.

This plugin provides seamless integration between the OpenAI Agents SDK and Temporal workflows. It automatically configures the necessary interceptors, activities, and data converters to enable OpenAI agents to run within Temporal workflows with proper tracing and model execution.

The plugin: 1. Configures the Pydantic data converter for type-safe serialization 2. Sets up tracing interceptors for OpenAI agent interactions 3. Registers model execution activities 4. Manages the OpenAI agent runtime overrides during worker execution

Example

>>> from temporalio.client import Client
>>> from temporalio.worker import Worker
>>> from temporalio.contrib.openai_agents import OpenAIAgentsPlugin, ModelActivityParameters
>>> from datetime import timedelta
>>>
>>> # Configure model parameters
>>> model_params = ModelActivityParameters(
...     start_to_close_timeout=timedelta(seconds=30),
...     retry_policy=RetryPolicy(maximum_attempts=3)
... )
>>>
>>> # Create plugin
>>> plugin = OpenAIAgentsPlugin(model_params=model_params)
>>>
>>> # Use with client and worker
>>> client = await Client.connect(
...     "localhost:7233",
...     plugins=[plugin]
... )
>>> worker = Worker(
...     client,
...     task_queue="my-task-queue",
...     workflows=[MyWorkflow],
... )

Parameters
model_params	Configuration parameters for Temporal activity execution of model calls. If None, default parameters will be used.
model_provider	Optional model provider for custom model implementations. Useful for testing or custom model integrations.

Method	`__init__`	Initialize the OpenAI agents plugin.
Method	`configure_client`	Configure the Temporal client for OpenAI agents integration.
Method	`configure_replayer`	Configure the replayer for OpenAI Agents.
Method	`configure_worker`	Configure the Temporal worker for OpenAI agents integration.
Async Method	`connect_service_client`	No modifications to service client
Method	`init_client_plugin`	Set the next client plugin
Method	`init_worker_plugin`	Set the next worker plugin
Async Method	`run_replayer`	Set the OpenAI Overrides during replay
Async Method	`run_worker`	Run the worker with OpenAI agents temporal overrides.
Instance Variable	`next_client_plugin`	Undocumented
Instance Variable	`next_worker_plugin`	Undocumented
Instance Variable	`_model_params`	Undocumented
Instance Variable	`_model_provider`	Undocumented

Inherited from Plugin:

Method name Get the name of this plugin. Can be overridden if desired to provide a more appropriate name.

def __init__(self, model_params: ModelActivityParameters | None = None, model_provider: ModelProvider | None = None): (source) ¶

Initialize the OpenAI agents plugin.

Parameters
model_params:`ModelActivityParameters \| None`	Configuration parameters for Temporal activity execution of model calls. If None, default parameters will be used.
model_provider:`ModelProvider \| None`	Optional model provider for custom model implementations. Useful for testing or custom model integrations.

def configure_client(self, config: ClientConfig) -> ClientConfig: (source) ¶

overrides temporalio.client.Plugin.configure_client

Configure the Temporal client for OpenAI agents integration.

This method sets up the Pydantic data converter to enable proper serialization of OpenAI agent objects and responses.

Parameters
config:`ClientConfig`	The client configuration to modify.
Returns
`ClientConfig`	The modified client configuration.

def configure_replayer(self, config: ReplayerConfig) -> ReplayerConfig: (source) ¶

overrides temporalio.worker.Plugin.configure_replayer

Configure the replayer for OpenAI Agents.

def configure_worker(self, config: WorkerConfig) -> WorkerConfig: (source) ¶

overrides temporalio.worker.Plugin.configure_worker

Configure the Temporal worker for OpenAI agents integration.

This method adds the necessary interceptors and activities for OpenAI agent execution: - Adds tracing interceptors for OpenAI agent interactions - Registers model execution activities

Parameters
config:`WorkerConfig`	The worker configuration to modify.
Returns
`WorkerConfig`	The modified worker configuration.

async def connect_service_client(self, config: temporalio.service.ConnectConfig) -> temporalio.service.ServiceClient: (source) ¶

overrides temporalio.client.Plugin.connect_service_client

No modifications to service client

def init_client_plugin(self, next: temporalio.client.Plugin): (source) ¶

overrides temporalio.client.Plugin.init_client_plugin

Set the next client plugin

def init_worker_plugin(self, next: temporalio.worker.Plugin): (source) ¶

overrides temporalio.worker.Plugin.init_worker_plugin

Set the next worker plugin

@asynccontextmanager
async def run_replayer(self, replayer: Replayer, histories: AsyncIterator[temporalio.client.WorkflowHistory]) -> AsyncIterator[AsyncIterator[WorkflowReplayResult]]: (source) ¶

overrides temporalio.worker.Plugin.run_replayer

Set the OpenAI Overrides during replay

async def run_worker(self, worker: Worker): (source) ¶

overrides temporalio.worker.Plugin.run_worker

Run the worker with OpenAI agents temporal overrides.

This method sets up the necessary runtime overrides for OpenAI agents to work within the Temporal worker context, including custom runners and trace providers.

Parameters
worker:`Worker`	The worker instance to run.

next_client_plugin = (source) ¶

Undocumented

next_worker_plugin = (source) ¶

Undocumented

_model_params = (source) ¶

Undocumented

_model_provider = (source) ¶

Undocumented