temporalio · jssmith · Jul 26, 2025 · cretz · Jul 28, 2025 · jssmith
@@ -4,6 +4,8 @@ Simple examples to get started with OpenAI Agents SDK integrated with Temporal w
 
 *Adapted from [OpenAI Agents SDK basic examples](https://github.com/openai/openai-agents-python/tree/main/examples/basic)*
 
+Before running these examples, be sure to review the [prerequisites and background on the integration](../README.md).
+
 ## Running the Examples
 
 First, start the worker (supports all basic examples):
@@ -14,12 +16,64 @@ uv run openai_agents/basic/run_worker.py
 Then run individual examples in separate terminals:
 
 ### Hello World Agent
+Basic agent that only responds in haikus:
 ```bash
 uv run openai_agents/basic/run_hello_world_workflow.py
 ```
 
 ### Tools Agent
-Agent with access to external tools (weather API):
+Agent with access to external tools (simulated weather API):
 ```bash
 uv run openai_agents/basic/run_tools_workflow.py
-```
+```
+
+### Agent Lifecycle with Hooks
+Demonstrates agent lifecycle events and handoffs between agents:
+```bash
+uv run openai_agents/basic/run_agent_lifecycle_workflow.py
+```
+
+### Lifecycle with Usage Tracking
+Shows detailed usage tracking with RunHooks (requests, tokens, etc.):
+```bash
+uv run openai_agents/basic/run_lifecycle_workflow.py
+```
+
+### Dynamic System Prompts
+Agent with dynamic instruction generation based on context (haiku/pirate/robot):
+```bash
+uv run openai_agents/basic/run_dynamic_system_prompt_workflow.py
+```
+
+### Non-Strict Output Types
+Demonstrates different JSON schema validation approaches:
+```bash
+uv run openai_agents/basic/run_non_strict_output_workflow.py
+```
+
+Note: `CustomOutputSchema` is not supported by the Temporal OpenAI Agents SDK integration and is omitted in this example.
+
+### Image Processing - Local
+Process local image files with AI vision:
+```bash
+uv run openai_agents/basic/run_local_image_workflow.py
+```
+
+### Image Processing - Remote
+Process remote image URLs with AI vision:
+```bash
+uv run openai_agents/basic/run_remote_image_workflow.py
+```
+
+### Previous Response ID
+Demonstrates conversation continuity using response IDs:
+```bash
+uv run openai_agents/basic/run_previous_response_id_workflow.py
+```
+
+## Omitted Examples
+
+The following examples from the [reference repository](https://github.com/openai/openai-agents-python/tree/main/examples/basic) are not included in this Temporal adaptation:
+
+- **Session** - Stores state in local SQLite database, not appropriate for distributed workflows
+- **Stream Items/Stream Text** - Streaming is not supported in Temporal OpenAI Agents SDK integration
@@ -0,0 +1,19 @@
+import base64
+
+from temporalio import activity
+
+
+@activity.defn
+async def read_image_as_base64(image_path: str) -> str:
+    """
+    Read an image file and convert it to base64 string.
+
+    Args:
+        image_path: Path to the image file
+
+    Returns:
+        Base64 encoded string of the image
+    """
+    with open(image_path, "rb") as image_file:
+        encoded_string = base64.b64encode(image_file.read()).decode("utf-8")
+    return encoded_string
@@ -0,0 +1,15 @@
+import random
+
+from temporalio import activity
+
+
+@activity.defn
+async def random_number(max_value: int) -> int:
+    """Generate a random number up to the provided maximum."""
+    return random.randint(0, max_value)
+
+
+@activity.defn
+async def multiply_by_two(x: int) -> int:
+    """Simple multiplication by two."""
+    return x * 2
@@ -0,0 +1,28 @@
+import asyncio
+
+from temporalio.client import Client
+
+from openai_agents.basic.workflows.agent_lifecycle_workflow import (
+    AgentLifecycleWorkflow,
+)
+
+
+async def main() -> None:
+    client = await Client.connect("localhost:7233")
+
+    user_input = input("Enter a max number: ")
+    max_number = int(user_input)
+
+    result = await client.execute_workflow(
+        AgentLifecycleWorkflow.run,
+        max_number,
+        id="agent-lifecycle-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print(f"Final result: {result}")
+    print("Done!")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,41 @@
+import asyncio
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.dynamic_system_prompt_workflow import (
+    DynamicSystemPromptWorkflow,
+)
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    user_message = "Tell me a joke."
+
+    result = await client.execute_workflow(
+        DynamicSystemPromptWorkflow.run,
+        user_message,
+        id="dynamic-prompt-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+    print(result)
+    print()
+
+    # Run with specific style
+    result = await client.execute_workflow(
+        DynamicSystemPromptWorkflow.run,
+        args=[user_message, "pirate"],
+        id="dynamic-prompt-pirate-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+    print(result)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -20,7 +20,7 @@ async def main():
         HelloWorldAgent.run,
         "Tell me about recursion in programming.",
         id="my-workflow-id",
-        task_queue="openai-agents-task-queue",
+        task_queue="openai-agents-basic-task-queue",
     )
     print(f"Result: {result}")
 

@@ -0,0 +1,31 @@
+import asyncio
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.lifecycle_workflow import LifecycleWorkflow
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    user_input = input("Enter a max number: ")
+    max_number = int(user_input)
+
+    result = await client.execute_workflow(
+        LifecycleWorkflow.run,
+        max_number,
+        id="lifecycle-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print(f"Final result: {result}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,32 @@
+import asyncio
+import os
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.local_image_workflow import LocalImageWorkflow
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    # Use the media file from the original example
+    image_path = os.path.join(os.path.dirname(__file__), "media/image_bison.jpg")
+
+    result = await client.execute_workflow(
+        LocalImageWorkflow.run,
+        args=[image_path, "What do you see in this image?"],
+        id="local-image-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print(f"Agent response: {result}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,35 @@
+import asyncio
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.non_strict_output_workflow import (
+    NonStrictOutputWorkflow,
+)
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    input_message = "Tell me 3 short jokes."
+
+    result = await client.execute_workflow(
+        NonStrictOutputWorkflow.run,
+        input_message,
+        id="non-strict-output-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print("=== Non-Strict Output Type Results ===")
+    for key, value in result.items():
+        print(f"{key}: {value}")
+        print()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,35 @@
+import asyncio
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.previous_response_id_workflow import (
+    PreviousResponseIdWorkflow,
+)
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    first_question = "What is the largest country in South America?"
+    follow_up_question = "What is the capital of that country?"
+
+    result = await client.execute_workflow(
+        PreviousResponseIdWorkflow.run,
+        args=[first_question, follow_up_question],
+        id="previous-response-id-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print("\nFinal results:")
+    print(f"1. {result[0]}")
+    print(f"2. {result[1]}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,33 @@
+import asyncio
+
+from temporalio.client import Client
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from openai_agents.basic.workflows.remote_image_workflow import RemoteImageWorkflow
+
+
+async def main():
+    client = await Client.connect(
+        "localhost:7233",
+        plugins=[
+            OpenAIAgentsPlugin(),
+        ],
+    )
+
+    # Use the URL from the original example
+    image_url = (
+        "https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
+    )
+
+    result = await client.execute_workflow(
+        RemoteImageWorkflow.run,
+        args=[image_url, "What do you see in this image?"],
+        id="remote-image-workflow",
+        task_queue="openai-agents-basic-task-queue",
+    )
+
+    print(f"Agent response: {result}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -20,7 +20,7 @@ async def main():
         ToolsWorkflow.run,
         "What is the weather in Tokio?",
         id="tools-workflow",
-        task_queue="openai-agents-task-queue",
+        task_queue="openai-agents-basic-task-queue",
     )
 
     print(f"Result: {result}")