Updated openai agents samples to work with latest SDK. (#204)

* Stage changes for next update to openai integration

* Update temporalio to latest

* Formatting

* remove passthrough

* Run isort

Author: tconley1428

openai_agents/run_agents_as_tools_workflow.py

@@ -1,9 +1,7 @@
 import asyncio
 
 from temporalio.client import Client
-from temporalio.contrib.openai_agents.open_ai_data_converter import (
-    open_ai_data_converter,
-)
+from temporalio.contrib.pydantic import pydantic_data_converter
 
 from openai_agents.workflows.agents_as_tools_workflow import AgentsAsToolsWorkflow
 
@@ -12,7 +10,7 @@ async def main():
     # Create client connected to server at the given address
     client = await Client.connect(
         "localhost:7233",
-        data_converter=open_ai_data_converter,
+        data_converter=pydantic_data_converter,
     )
 
     # Execute a workflow

openai_agents/run_customer_service_client.py

@@ -7,9 +7,7 @@
     WorkflowUpdateFailedError,
 )
 from temporalio.common import QueryRejectCondition
-from temporalio.contrib.openai_agents.open_ai_data_converter import (
-    open_ai_data_converter,
-)
+from temporalio.contrib.pydantic import pydantic_data_converter
 from temporalio.service import RPCError, RPCStatusCode
 
 from openai_agents.workflows.customer_service_workflow import (
@@ -26,7 +24,7 @@ async def main():
     # Create client connected to server at the given address
     client = await Client.connect(
         "localhost:7233",
-        data_converter=open_ai_data_converter,
+        data_converter=pydantic_data_converter,
     )
 
     handle = client.get_workflow_handle(args.conversation_id)

openai_agents/run_hello_world_workflow.py

@@ -1,18 +1,17 @@
 import asyncio
 
 from temporalio.client import Client
-from temporalio.contrib.openai_agents.open_ai_data_converter import (
-    open_ai_data_converter,
-)
+from temporalio.contrib.pydantic import pydantic_data_converter
 
 from openai_agents.workflows.hello_world_workflow import HelloWorldAgent
+from openai_agents.workflows.research_bot_workflow import ResearchWorkflow
 
 
 async def main():
     # Create client connected to server at the given address
     client = await Client.connect(
         "localhost:7233",
-        data_converter=open_ai_data_converter,
+        data_converter=pydantic_data_converter,
     )
 
     # Execute a workflow

openai_agents/run_research_workflow.py

@@ -1,9 +1,7 @@
 import asyncio
 
 from temporalio.client import Client
-from temporalio.contrib.openai_agents.open_ai_data_converter import (
-    open_ai_data_converter,
-)
+from temporalio.contrib.pydantic import pydantic_data_converter
 
 from openai_agents.workflows.research_bot_workflow import ResearchWorkflow
 
@@ -12,7 +10,7 @@ async def main():
     # Create client connected to server at the given address
     client = await Client.connect(
         "localhost:7233",
-        data_converter=open_ai_data_converter,
+        data_converter=pydantic_data_converter,
     )
 
     # Execute a workflow

openai_agents/run_tools_workflow.py

@@ -1,9 +1,7 @@
 import asyncio
 
 from temporalio.client import Client
-from temporalio.contrib.openai_agents.open_ai_data_converter import (
-    open_ai_data_converter,
-)
+from temporalio.contrib.pydantic import pydantic_data_converter
 
 from openai_agents.workflows.tools_workflow import ToolsWorkflow
 
@@ -12,7 +10,7 @@ async def main():
     # Create client connected to server at the given address
     client = await Client.connect(
         "localhost:7233",
-        data_converter=open_ai_data_converter,
+        data_converter=pydantic_data_converter,
     )
 
     # Execute a workflow

openai_agents/run_worker.py

@@ -4,9 +4,9 @@
 from datetime import timedelta
 
 from temporalio.client import Client
-from temporalio.contrib.openai_agents.invoke_model_activity import ModelActivity
-from temporalio.contrib.openai_agents.model_parameters import ModelActivityParameters
-from temporalio.contrib.openai_agents.temporal_openai_agents import (
+from temporalio.contrib.openai_agents import (
+    ModelActivity,
+    ModelActivityParameters,
     set_open_ai_agent_temporal_overrides,
 )
 from temporalio.contrib.pydantic import pydantic_data_converter
@@ -32,7 +32,6 @@ async def main():
             data_converter=pydantic_data_converter,
         )
 
-        model_activity = ModelActivity(model_provider=None)
         worker = Worker(
             client,
             task_queue="openai-agents-task-queue",
@@ -44,7 +43,7 @@ async def main():
                 AgentsAsToolsWorkflow,
             ],
             activities=[
-                model_activity.invoke_model_activity,
+                ModelActivity().invoke_model_activity,
                 get_weather,
             ],
         )

openai_agents/workflows/agents_as_tools_workflow.py

@@ -1,8 +1,6 @@
+from agents import Agent, ItemHelpers, MessageOutputItem, RunConfig, Runner, trace
 from temporalio import workflow
 
-with workflow.unsafe.imports_passed_through():
-    from agents import Agent, ItemHelpers, MessageOutputItem, RunConfig, Runner, trace
-
 """
 This example shows the agents-as-tools pattern. The frontline agent receives a user message and
 then picks which agents to call, as tools. In this case, it picks from a set of translation

openai_agents/workflows/customer_service_workflow.py

@@ -1,26 +1,24 @@
 from __future__ import annotations as _annotations
 
+from agents import (
+    Agent,
+    HandoffOutputItem,
+    ItemHelpers,
+    MessageOutputItem,
+    RunConfig,
+    Runner,
+    ToolCallItem,
+    ToolCallOutputItem,
+    TResponseInputItem,
+    trace,
+)
 from temporalio import workflow
 
-with workflow.unsafe.imports_passed_through():
-    from agents import (
-        Agent,
-        HandoffOutputItem,
-        ItemHelpers,
-        MessageOutputItem,
-        RunConfig,
-        Runner,
-        ToolCallItem,
-        ToolCallOutputItem,
-        TResponseInputItem,
-        trace,
-    )
-
-    from openai_agents.workflows.customer_service import (
-        AirlineAgentContext,
-        ProcessUserMessageInput,
-        init_agents,
-    )
+from openai_agents.workflows.customer_service import (
+    AirlineAgentContext,
+    ProcessUserMessageInput,
+    init_agents,
+)
 
 
 @workflow.defn

openai_agents/workflows/hello_world_workflow.py

@@ -1,9 +1,6 @@
+from agents import Agent, Runner
 from temporalio import workflow
 
-# Import agent Agent and Runner
-with workflow.unsafe.imports_passed_through():
-    from agents import Agent, Runner
-
 
 @workflow.defn
 class HelloWorldAgent:

openai_agents/workflows/tools_workflow.py

@@ -2,14 +2,11 @@
 
 from datetime import timedelta
 
+from agents import Agent, Runner
 from temporalio import workflow
-from temporalio.contrib.openai_agents.temporal_tools import activity_as_tool
+from temporalio.contrib import openai_agents as temporal_agents
 
-# Import our activity, passing it through the sandbox
-with workflow.unsafe.imports_passed_through():
-    from agents import Agent, Runner
-
-    from openai_agents.workflows.get_weather_activity import get_weather
+from openai_agents.workflows.get_weather_activity import get_weather
 
 
 @workflow.defn
@@ -20,7 +17,7 @@ async def run(self, question: str) -> str:
             name="Hello world",
             instructions="You are a helpful agent.",
             tools=[
-                activity_as_tool(
+                temporal_agents.workflow.activity_as_tool(
                     get_weather, start_to_close_timeout=timedelta(seconds=10)
                 )
             ],