Bump temporalio to 1.16.0 (#2703)

Author: DouweM

pydantic_ai_slim/pydantic_ai/durable_exec/temporal/__init__.py

@@ -1,15 +1,24 @@
 from __future__ import annotations
 
 import warnings
-from collections.abc import Sequence
+from collections.abc import AsyncIterator, Sequence
+from contextlib import AbstractAsyncContextManager
 from dataclasses import replace
 from typing import Any, Callable
 
 from pydantic.errors import PydanticUserError
-from temporalio.client import ClientConfig, Plugin as ClientPlugin
+from temporalio.client import ClientConfig, Plugin as ClientPlugin, WorkflowHistory
 from temporalio.contrib.pydantic import PydanticPayloadConverter, pydantic_data_converter
-from temporalio.converter import DefaultPayloadConverter
-from temporalio.worker import Plugin as WorkerPlugin, WorkerConfig
+from temporalio.converter import DataConverter, DefaultPayloadConverter
+from temporalio.service import ConnectConfig, ServiceClient
+from temporalio.worker import (
+    Plugin as WorkerPlugin,
+    Replayer,
+    ReplayerConfig,
+    Worker,
+    WorkerConfig,
+    WorkflowReplayResult,
+)
 from temporalio.worker.workflow_sandbox import SandboxedWorkflowRunner
 
 from ...exceptions import UserError
@@ -31,17 +40,15 @@
 class PydanticAIPlugin(ClientPlugin, WorkerPlugin):
     """Temporal client and worker plugin for Pydantic AI."""
 
-    def configure_client(self, config: ClientConfig) -> ClientConfig:
-        if (data_converter := config.get('data_converter')) and data_converter.payload_converter_class not in (
-            DefaultPayloadConverter,
-            PydanticPayloadConverter,
-        ):
-            warnings.warn(  # pragma: no cover
-                'A non-default Temporal data converter was used which has been replaced with the Pydantic data converter.'
-            )
+    def init_client_plugin(self, next: ClientPlugin) -> None:
+        self.next_client_plugin = next
 
-        config['data_converter'] = pydantic_data_converter
-        return super().configure_client(config)
+    def init_worker_plugin(self, next: WorkerPlugin) -> None:
+        self.next_worker_plugin = next
+
+    def configure_client(self, config: ClientConfig) -> ClientConfig:
+        config['data_converter'] = self._get_new_data_converter(config.get('data_converter'))
+        return self.next_client_plugin.configure_client(config)
 
     def configure_worker(self, config: WorkerConfig) -> WorkerConfig:
         runner = config.get('workflow_runner')  # pyright: ignore[reportUnknownMemberType]
@@ -67,7 +74,35 @@ def configure_worker(self, config: WorkerConfig) -> WorkerConfig:
             PydanticUserError,
         ]
 
-        return super().configure_worker(config)
+        return self.next_worker_plugin.configure_worker(config)
+
+    async def connect_service_client(self, config: ConnectConfig) -> ServiceClient:
+        return await self.next_client_plugin.connect_service_client(config)
+
+    async def run_worker(self, worker: Worker) -> None:
+        await self.next_worker_plugin.run_worker(worker)
+
+    def configure_replayer(self, config: ReplayerConfig) -> ReplayerConfig:  # pragma: no cover
+        config['data_converter'] = self._get_new_data_converter(config.get('data_converter'))  # pyright: ignore[reportUnknownMemberType]
+        return self.next_worker_plugin.configure_replayer(config)
+
+    def run_replayer(
+        self,
+        replayer: Replayer,
+        histories: AsyncIterator[WorkflowHistory],
+    ) -> AbstractAsyncContextManager[AsyncIterator[WorkflowReplayResult]]:  # pragma: no cover
+        return self.next_worker_plugin.run_replayer(replayer, histories)
+
+    def _get_new_data_converter(self, converter: DataConverter | None) -> DataConverter:
+        if converter and converter.payload_converter_class not in (
+            DefaultPayloadConverter,
+            PydanticPayloadConverter,
+        ):
+            warnings.warn(  # pragma: no cover
+                'A non-default Temporal data converter was used which has been replaced with the Pydantic data converter.'
+            )
+
+        return pydantic_data_converter
 
 
 class AgentPlugin(WorkerPlugin):
@@ -76,8 +111,24 @@ class AgentPlugin(WorkerPlugin):
     def __init__(self, agent: TemporalAgent[Any, Any]):
         self.agent = agent
 
+    def init_worker_plugin(self, next: WorkerPlugin) -> None:
+        self.next_worker_plugin = next
+
     def configure_worker(self, config: WorkerConfig) -> WorkerConfig:
         activities: Sequence[Callable[..., Any]] = config.get('activities', [])  # pyright: ignore[reportUnknownMemberType]
         # Activities are checked for name conflicts by Temporal.
         config['activities'] = [*activities, *self.agent.temporal_activities]
-        return super().configure_worker(config)
+        return self.next_worker_plugin.configure_worker(config)
+
+    async def run_worker(self, worker: Worker) -> None:
+        await self.next_worker_plugin.run_worker(worker)
+
+    def configure_replayer(self, config: ReplayerConfig) -> ReplayerConfig:  # pragma: no cover
+        return self.next_worker_plugin.configure_replayer(config)
+
+    def run_replayer(
+        self,
+        replayer: Replayer,
+        histories: AsyncIterator[WorkflowHistory],
+    ) -> AbstractAsyncContextManager[AsyncIterator[WorkflowReplayResult]]:  # pragma: no cover
+        return self.next_worker_plugin.run_replayer(replayer, histories)

pydantic_ai_slim/pydantic_ai/durable_exec/temporal/_logfire.py

@@ -25,10 +25,13 @@ def __init__(self, setup_logfire: Callable[[], Logfire] = _default_setup_logfire
         self.setup_logfire = setup_logfire
         self.metrics = metrics
 
+    def init_client_plugin(self, next: ClientPlugin) -> None:
+        self.next_client_plugin = next
+
     def configure_client(self, config: ClientConfig) -> ClientConfig:
         interceptors = config.get('interceptors', [])
         config['interceptors'] = [*interceptors, TracingInterceptor(get_tracer('temporalio'))]
-        return super().configure_client(config)
+        return self.next_client_plugin.configure_client(config)
 
     async def connect_service_client(self, config: ConnectConfig) -> ServiceClient:
         logfire = self.setup_logfire()
@@ -45,4 +48,4 @@ async def connect_service_client(self, config: ConnectConfig) -> ServiceClient:
                     telemetry=TelemetryConfig(metrics=OpenTelemetryConfig(url=metrics_url, headers=headers))
                 )
 
-        return await super().connect_service_client(config)
+        return await self.next_client_plugin.connect_service_client(config)

pydantic_ai_slim/pyproject.toml

@@ -94,7 +94,7 @@ ag-ui = ["ag-ui-protocol>=0.1.8", "starlette>=0.45.3"]
 # Retries
 retries = ["tenacity>=8.2.3"]
 # Temporal
-temporal = ["temporalio==1.15.0"]
+temporal = ["temporalio==1.16.0"]
 
 [tool.hatch.metadata]
 allow-direct-references = true