Merge remote-tracking branch 'origin/main' into update-readme-oai-agents

Author: jssmith

.github/workflows/build-binaries.yml

@@ -74,8 +74,3 @@ jobs:
         with:
           name: packages-${{ matrix.package-suffix }}
           path: dist
-
-      - name: Deliberately fail to prevent releasing nexus-rpc w/ GitHub link in pyproject.toml
-        run: |
-          echo "This is a deliberate failure to prevent releasing nexus-rpc with a GitHub link in pyproject.toml"
-          exit 1

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "temporalio"
-version = "1.14.1"
+version = "1.15.0"
 description = "Temporal.io Python SDK"
 authors = [{ name = "Temporal Technologies Inc", email = "[email protected]" }]
 requires-python = ">=3.9"
@@ -11,7 +11,7 @@ keywords = [
     "workflow",
 ]
 dependencies = [
-    "nexus-rpc>=1.1.0",
+    "nexus-rpc==1.1.0",
     "protobuf>=3.20,<6",
     "python-dateutil>=2.8.2,<3 ; python_version < '3.11'",
     "types-protobuf>=3.20",
@@ -57,6 +57,7 @@ dev = [
     "pytest-cov>=6.1.1",
     "httpx>=0.28.1",
     "pytest-pretty>=1.3.0",
+    "openai-agents[litellm] >= 0.2.3,<0.3"
 ]
 
 [tool.poe.tasks]
@@ -230,6 +231,3 @@ exclude = [
 [tool.uv]
 # Prevent uv commands from building the package by default
 package = false
-
-[tool.uv.sources]
-nexus-rpc = { git = "https://github.com/nexus-rpc/sdk-python.git", rev = "35f574c711193a6e2560d3e6665732a5bb7ae92c" }

temporalio/client.py

@@ -528,11 +528,12 @@ async def start_workflow(
                 retries and continue as new.
             run_timeout: Timeout of a single workflow run.
             task_timeout: Timeout of a single workflow task.
-            id_reuse_policy: How already-existing IDs are treated.
-            id_conflict_policy: How already-running workflows of the same ID are
-                treated. Default is unspecified which effectively means fail the
-                start attempt. This cannot be set if ``id_reuse_policy`` is set
-                to terminate if running.
+            id_conflict_policy: Behavior when a workflow is currently running with the same ID.
+                Default is UNSPECIFIED, which effectively means fail the start attempt.
+                Set to USE_EXISTING for idempotent deduplication on workflow ID.
+                Cannot be set if ``id_reuse_policy`` is set to TERMINATE_IF_RUNNING.
+            id_reuse_policy: Behavior when a closed workflow with the same ID exists.
+                Default is ALLOW_DUPLICATE.
             retry_policy: Retry policy for the workflow.
             cron_schedule: See https://docs.temporal.io/docs/content/what-is-a-temporal-cron-job/
             memo: Memo for the workflow.
@@ -2487,9 +2488,6 @@ class WithStartWorkflowOperation(Generic[SelfType, ReturnType]):
 
     Update-With-Start allows you to send an update to a workflow, while starting the
     workflow if necessary.
-
-    .. warning::
-        This API is experimental
     """
 
     # Overload for no-param workflow, with_start
@@ -2657,9 +2655,6 @@ def __init__(
     ) -> None:
         """Create a WithStartWorkflowOperation.
 
-        .. warning::
-           This API is experimental
-
         See :py:meth:`temporalio.client.Client.start_workflow` for documentation of the
         arguments.
         """
@@ -2700,11 +2695,7 @@ def __init__(
         self._used = False
 
     async def workflow_handle(self) -> WorkflowHandle[SelfType, ReturnType]:
-        """Wait until workflow is running and return a WorkflowHandle.
-
-        .. warning::
-           This API is experimental
-        """
+        """Wait until workflow is running and return a WorkflowHandle."""
         return await self._workflow_handle
 
 

temporalio/contrib/openai_agents/_invoke_model_activity.py

@@ -7,13 +7,16 @@
 import json
 from dataclasses import dataclass
 from datetime import timedelta
-from typing import Any, Optional, Union, cast
+from typing import Any, Optional, Union
 
 from agents import (
     AgentOutputSchemaBase,
+    CodeInterpreterTool,
     FileSearchTool,
     FunctionTool,
     Handoff,
+    HostedMCPTool,
+    ImageGenerationTool,
     ModelProvider,
     ModelResponse,
     ModelSettings,
@@ -25,13 +28,12 @@
     UserError,
     WebSearchTool,
 )
-from agents.models.multi_provider import MultiProvider
 from openai import (
     APIStatusError,
     AsyncOpenAI,
-    AuthenticationError,
-    PermissionDeniedError,
 )
+from openai.types.responses.tool_param import Mcp
+from pydantic_core import to_json
 from typing_extensions import Required, TypedDict
 
 from temporalio import activity
@@ -41,7 +43,9 @@
 
 @dataclass
 class HandoffInput:
-    """Data conversion friendly representation of a Handoff."""
+    """Data conversion friendly representation of a Handoff. Contains only the fields which are needed by the model
+    execution to determine what to handoff to, not the actual handoff invocation, which remains in the workflow context.
+    """
 
     tool_name: str
     tool_description: str
@@ -52,15 +56,33 @@ class HandoffInput:
 
 @dataclass
 class FunctionToolInput:
-    """Data conversion friendly representation of a FunctionTool."""
+    """Data conversion friendly representation of a FunctionTool. Contains only the fields which are needed by the model
+    execution to determine what tool to call, not the actual tool invocation, which remains in the workflow context.
+    """
 
     name: str
     description: str
     params_json_schema: dict[str, Any]
     strict_json_schema: bool = True
 
 
-ToolInput = Union[FunctionToolInput, FileSearchTool, WebSearchTool]
+@dataclass
+class HostedMCPToolInput:
+    """Data conversion friendly representation of a HostedMCPTool. Contains only the fields which are needed by the model
+    execution to determine what tool to call, not the actual tool invocation, which remains in the workflow context.
+    """
+
+    tool_config: Mcp
+
+
+ToolInput = Union[
+    FunctionToolInput,
+    FileSearchTool,
+    WebSearchTool,
+    ImageGenerationTool,
+    CodeInterpreterTool,
+    HostedMCPToolInput,
+]
 
 
 @dataclass
@@ -152,22 +174,31 @@ async def empty_on_invoke_handoff(
 
         # workaround for https://github.com/pydantic/pydantic/issues/9541
         # ValidatorIterator returned
-        input_json = json.dumps(input["input"], default=str)
+        input_json = to_json(input["input"])
         input_input = json.loads(input_json)
 
         def make_tool(tool: ToolInput) -> Tool:
-            if isinstance(tool, FileSearchTool):
-                return cast(FileSearchTool, tool)
-            elif isinstance(tool, WebSearchTool):
-                return cast(WebSearchTool, tool)
+            if isinstance(
+                tool,
+                (
+                    FileSearchTool,
+                    WebSearchTool,
+                    ImageGenerationTool,
+                    CodeInterpreterTool,
+                ),
+            ):
+                return tool
+            elif isinstance(tool, HostedMCPToolInput):
+                return HostedMCPTool(
+                    tool_config=tool.tool_config,
+                )
             elif isinstance(tool, FunctionToolInput):
-                t = cast(FunctionToolInput, tool)
                 return FunctionTool(
-                    name=t.name,
-                    description=t.description,
-                    params_json_schema=t.params_json_schema,
+                    name=tool.name,
+                    description=tool.description,
+                    params_json_schema=tool.params_json_schema,
                     on_invoke_tool=empty_on_invoke_tool,
-                    strict_json_schema=t.strict_json_schema,
+                    strict_json_schema=tool.strict_json_schema,
                 )
             else:
                 raise UserError(f"Unknown tool type: {tool.name}")

temporalio/contrib/openai_agents/_openai_runner.py

@@ -1,3 +1,4 @@
+import json
 import typing
 from dataclasses import replace
 from typing import Any, Union
@@ -7,11 +8,13 @@
     RunConfig,
     RunResult,
     RunResultStreaming,
+    SQLiteSession,
     TContext,
     Tool,
     TResponseInputItem,
 )
 from agents.run import DEFAULT_AGENT_RUNNER, DEFAULT_MAX_TURNS, AgentRunner
+from pydantic_core import to_json
 
 from temporalio import workflow
 from temporalio.contrib.openai_agents._model_parameters import ModelActivityParameters
@@ -51,23 +54,38 @@ async def run(
                     "Provided tool is not a tool type. If using an activity, make sure to wrap it with openai_agents.workflow.activity_as_tool."
                 )
 
+        if starting_agent.mcp_servers:
+            raise ValueError(
+                "Temporal OpenAI agent does not support on demand MCP servers."
+            )
+
+        # workaround for https://github.com/pydantic/pydantic/issues/9541
+        # ValidatorIterator returned
+        input_json = to_json(input)
+        input = json.loads(input_json)
+
         context = kwargs.get("context")
         max_turns = kwargs.get("max_turns", DEFAULT_MAX_TURNS)
         hooks = kwargs.get("hooks")
         run_config = kwargs.get("run_config")
         previous_response_id = kwargs.get("previous_response_id")
+        session = kwargs.get("session")
+
+        if isinstance(session, SQLiteSession):
+            raise ValueError("Temporal workflows don't support SQLite sessions.")
 
         if run_config is None:
             run_config = RunConfig()
 
-        if run_config.model is not None and not isinstance(run_config.model, str):
+        model_name = run_config.model or starting_agent.model
+        if model_name is not None and not isinstance(model_name, str):
             raise ValueError(
-                "Temporal workflows require a model name to be a string in the run config."
+                "Temporal workflows require a model name to be a string in the run config and/or agent."
             )
         updated_run_config = replace(
             run_config,
             model=_TemporalModelStub(
-                run_config.model,
+                model_name=model_name,
                 model_params=self.model_params,
             ),
         )
@@ -80,6 +98,7 @@ async def run(
             hooks=hooks,
             run_config=updated_run_config,
             previous_response_id=previous_response_id,
+            session=session,
         )
 
     def run_sync(