merge

smoreinis · smoreinis · commit dc6b98896037 · 2025-11-10T16:19:01.000-08:00
diff --git a/examples/tutorials/10_async/10_temporal/060_open_ai_agents_sdk_hello_world/060_open_ai_agents_sdk_hello_world/project/run_worker.py b/examples/tutorials/10_async/10_temporal/060_open_ai_agents_sdk_hello_world/060_open_ai_agents_sdk_hello_world/project/run_worker.py
@@ -0,0 +1,39 @@
+import asyncio
+
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
+
+from project.workflow import ExampleTutorialWorkflow
+from agentex.lib.utils.debug import setup_debug_if_enabled
+from agentex.lib.utils.logging import make_logger
+from agentex.lib.environment_variables import EnvironmentVariables
+from agentex.lib.core.temporal.activities import get_all_activities
+from agentex.lib.core.temporal.workers.worker import AgentexWorker
+
+environment_variables = EnvironmentVariables.refresh()
+
+logger = make_logger(__name__)
+
+
+async def main():
+    # Setup debug mode if enabled
+    setup_debug_if_enabled()
+
+    task_queue_name = environment_variables.WORKFLOW_TASK_QUEUE
+    if task_queue_name is None:
+        raise ValueError("WORKFLOW_TASK_QUEUE is not set")
+
+    # Add activities to the worker
+    all_activities = get_all_activities() + []  # add your own activities here
+
+    # Create a worker with automatic tracing
+    # We are also adding the Open AI Agents SDK plugin to the worker.
+    worker = AgentexWorker(task_queue=task_queue_name, plugins=[OpenAIAgentsPlugin()])
+
+    await worker.run(
+        activities=all_activities,
+        workflow=ExampleTutorialWorkflow,
+    )
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/examples/tutorials/10_async/10_temporal/060_open_ai_agents_sdk_hello_world/060_open_ai_agents_sdk_hello_world/tests/test_agent.py b/examples/tutorials/10_async/10_temporal/060_open_ai_agents_sdk_hello_world/060_open_ai_agents_sdk_hello_world/tests/test_agent.py
@@ -0,0 +1,40 @@
+"""
+Tests for example-tutorial (OpenAI Agents SDK Hello World)
+
+Prerequisites:
+    - AgentEx services running (make dev)
+    - Temporal server running
+    - Agent running: agentex agents run --manifest manifest.yaml
+
+Run: pytest tests/test_agent.py -v
+"""
+
+import pytest
+
+from agentex.lib.testing import test_agentic_agent, assert_valid_agent_response
+
+AGENT_NAME = "example-tutorial"
+
+
+@pytest.mark.asyncio
+async def test_agent_basic():
+    """Test basic agent functionality."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        response = await test.send_event("Test message", timeout_seconds=60.0)
+        assert_valid_agent_response(response)
+
+
+@pytest.mark.asyncio
+async def test_agent_streaming():
+    """Test streaming responses."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        events = []
+        async for event in test.send_event_and_stream("Stream test", timeout_seconds=60.0):
+            events.append(event)
+            if event.get("type") == "done":
+                break
+        assert len(events) > 0
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
diff --git a/examples/tutorials/10_async/10_temporal/070_open_ai_agents_sdk_tools/070_open_ai_agents_sdk_tools/project/run_worker.py b/examples/tutorials/10_async/10_temporal/070_open_ai_agents_sdk_tools/070_open_ai_agents_sdk_tools/project/run_worker.py
@@ -0,0 +1,44 @@
+import asyncio
+from datetime import timedelta
+
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin, ModelActivityParameters
+
+from project.workflow import ExampleTutorialWorkflow
+from project.activities import get_weather, deposit_money, withdraw_money
+from agentex.lib.utils.debug import setup_debug_if_enabled
+from agentex.lib.utils.logging import make_logger
+from agentex.lib.environment_variables import EnvironmentVariables
+from agentex.lib.core.temporal.activities import get_all_activities
+from agentex.lib.core.temporal.workers.worker import AgentexWorker
+
+environment_variables = EnvironmentVariables.refresh()
+
+logger = make_logger(__name__)
+
+
+async def main():
+    # Setup debug mode if enabled
+    setup_debug_if_enabled()
+
+    task_queue_name = environment_variables.WORKFLOW_TASK_QUEUE
+    if task_queue_name is None:
+        raise ValueError("WORKFLOW_TASK_QUEUE is not set")
+
+    # Add activities to the worker
+    all_activities = get_all_activities() + [withdraw_money, deposit_money, get_weather]  # add your own activities here
+
+    # Create a worker with automatic tracing
+    # We are also adding the Open AI Agents SDK plugin to the worker.
+    worker = AgentexWorker(
+        task_queue=task_queue_name,
+        plugins=[OpenAIAgentsPlugin(model_params=ModelActivityParameters(start_to_close_timeout=timedelta(days=1)))],
+    )
+
+    await worker.run(
+        activities=all_activities,
+        workflow=ExampleTutorialWorkflow,
+    )
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/examples/tutorials/10_async/10_temporal/070_open_ai_agents_sdk_tools/070_open_ai_agents_sdk_tools/tests/test_agent.py b/examples/tutorials/10_async/10_temporal/070_open_ai_agents_sdk_tools/070_open_ai_agents_sdk_tools/tests/test_agent.py
@@ -0,0 +1,40 @@
+"""
+Tests for example-tutorial (OpenAI Agents SDK Tools)
+
+Prerequisites:
+    - AgentEx services running (make dev)
+    - Temporal server running
+    - Agent running: agentex agents run --manifest manifest.yaml
+
+Run: pytest tests/test_agent.py -v
+"""
+
+import pytest
+
+from agentex.lib.testing import test_agentic_agent, assert_valid_agent_response
+
+AGENT_NAME = "example-tutorial"
+
+
+@pytest.mark.asyncio
+async def test_agent_basic():
+    """Test basic agent functionality."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        response = await test.send_event("Test message", timeout_seconds=60.0)
+        assert_valid_agent_response(response)
+
+
+@pytest.mark.asyncio
+async def test_agent_streaming():
+    """Test streaming responses."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        events = []
+        async for event in test.send_event_and_stream("Stream test", timeout_seconds=60.0):
+            events.append(event)
+            if event.get("type") == "done":
+                break
+        assert len(events) > 0
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
diff --git a/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/project/run_worker.py b/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/project/run_worker.py
@@ -0,0 +1,45 @@
+import asyncio
+from datetime import timedelta
+
+from temporalio.contrib.openai_agents import OpenAIAgentsPlugin, ModelActivityParameters
+
+from project.workflow import ChildWorkflow, ExampleTutorialWorkflow
+from project.activities import confirm_order, deposit_money, withdraw_money
+from agentex.lib.utils.debug import setup_debug_if_enabled
+from agentex.lib.utils.logging import make_logger
+from agentex.lib.environment_variables import EnvironmentVariables
+from agentex.lib.core.temporal.activities import get_all_activities
+from agentex.lib.core.temporal.workers.worker import AgentexWorker
+
+environment_variables = EnvironmentVariables.refresh()
+
+logger = make_logger(__name__)
+
+
+async def main():
+    # Setup debug mode if enabled
+    setup_debug_if_enabled()
+
+    task_queue_name = environment_variables.WORKFLOW_TASK_QUEUE
+    if task_queue_name is None:
+        raise ValueError("WORKFLOW_TASK_QUEUE is not set")
+
+    # Add activities to the worker
+    all_activities = get_all_activities() + [
+        withdraw_money,
+        deposit_money,
+        confirm_order,
+    ]  # add your own activities here
+
+    # Create a worker with automatic tracing
+    # We are also adding the Open AI Agents SDK plugin to the worker.
+    worker = AgentexWorker(
+        task_queue=task_queue_name,
+        plugins=[OpenAIAgentsPlugin(model_params=ModelActivityParameters(start_to_close_timeout=timedelta(days=1)))],
+    )
+
+    await worker.run(activities=all_activities, workflows=[ExampleTutorialWorkflow, ChildWorkflow])
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/project/workflow.py b/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/project/workflow.py
@@ -0,0 +1,137 @@
+"""
+OpenAI Agents SDK + Temporal Integration: Human-in-the-Loop Tutorial
+
+This tutorial demonstrates how to pause agent execution and wait for human approval
+using Temporal's child workflows and signals.
+
+KEY CONCEPTS:
+- Child workflows: Independent workflows spawned by parent for human interaction
+- Signals: External systems can send messages to running workflows
+- Durable waiting: Agents can wait indefinitely for human input without losing state
+
+WHY THIS MATTERS:
+Without Temporal, if your system crashes while waiting for human approval, you lose
+all context. With Temporal, the agent resumes exactly where it left off after
+system failures, making human-in-the-loop workflows production-ready.
+
+PATTERN:
+1. Agent calls wait_for_confirmation tool
+2. Tool spawns child workflow that waits for signal
+3. Human approves via CLI/web app
+4. Child workflow completes, agent continues
+
+Usage: `temporal workflow signal --workflow-id="child-workflow-id" --name="fulfill_order_signal" --input=true`
+"""
+
+import json
+import asyncio
+
+from agents import Agent, Runner
+from temporalio import workflow
+
+from agentex.lib import adk
+from project.tools import wait_for_confirmation
+from agentex.lib.types.acp import SendEventParams, CreateTaskParams
+from agentex.lib.utils.logging import make_logger
+from agentex.types.text_content import TextContent
+from agentex.lib.environment_variables import EnvironmentVariables
+from agentex.lib.core.temporal.types.workflow import SignalName
+from agentex.lib.core.temporal.workflows.workflow import BaseWorkflow
+
+environment_variables = EnvironmentVariables.refresh()
+
+if environment_variables.WORKFLOW_NAME is None:
+    raise ValueError("Environment variable WORKFLOW_NAME is not set")
+
+if environment_variables.AGENT_NAME is None:
+    raise ValueError("Environment variable AGENT_NAME is not set")
+
+logger = make_logger(__name__)
+
+
+@workflow.defn(name=environment_variables.WORKFLOW_NAME)
+class ExampleTutorialWorkflow(BaseWorkflow):
+    """
+    Human-in-the-Loop Temporal Workflow
+
+    Demonstrates agents that can pause execution and wait for human approval.
+    When approval is needed, the agent spawns a child workflow that waits for
+    external signals (human input) before continuing.
+
+    Benefits: Durable waiting, survives system failures, scalable to millions of workflows.
+    """
+
+    def __init__(self):
+        super().__init__(display_name=environment_variables.AGENT_NAME)
+        self._complete_task = False
+        self._pending_confirmation: asyncio.Queue[str] = asyncio.Queue()
+
+    @workflow.signal(name=SignalName.RECEIVE_EVENT)
+    async def on_task_event_send(self, params: SendEventParams) -> None:
+        """
+        Handle user messages with human-in-the-loop approval capability.
+
+        When the agent needs human approval, it calls wait_for_confirmation which spawns
+        a child workflow that waits for external signals before continuing.
+        """
+        logger.info(f"Received task message instruction: {params}")
+
+        # Echo user message back to UI
+        await adk.messages.create(task_id=params.task.id, content=params.event.content)
+
+        # Create agent with human-in-the-loop capability
+        # The wait_for_confirmation tool spawns a child workflow that waits for external signals
+        confirm_order_agent = Agent(
+            name="Confirm Order",
+            instructions="You are a helpful confirm order agent. When a user asks you to confirm an order, use the wait_for_confirmation tool to wait for confirmation.",
+            tools=[
+                wait_for_confirmation,
+            ],
+        )
+
+        # Run agent - when human approval is needed, it will spawn child workflow and wait
+        result = await Runner.run(confirm_order_agent, params.event.content.content)
+
+        # Send response back to user (includes result of any human approval process)
+        await adk.messages.create(
+            task_id=params.task.id,
+            content=TextContent(
+                author="agent",
+                content=result.final_output,
+            ),
+        )
+
+    @workflow.run
+    async def on_task_create(self, params: CreateTaskParams) -> str:
+        """
+        Workflow entry point - starts the long-running human-in-the-loop agent.
+
+        Handles both automated decisions and human approval workflows durably.
+        To approve waiting actions: temporal workflow signal --workflow-id="child-workflow-id" --name="fulfill_order_signal" --input=true
+        """
+        logger.info(f"Received task create params: {params}")
+
+        # Send welcome message when task is created
+        await adk.messages.create(
+            task_id=params.task.id,
+            content=TextContent(
+                author="agent",
+                content=f"Hello! I've received your task. Normally you can do some state initialization here, or just pass and do nothing until you get your first event. For now I'm just acknowledging that I've received a task with the following params:\n\n{json.dumps(params.params, indent=2)}.\n\nYou should only see this message once, when the task is created. All subsequent events will be handled by the `on_task_event_send` handler.",
+            ),
+        )
+
+        # Keep workflow running indefinitely to handle user messages and human approvals
+        # This survives system failures and can resume exactly where it left off
+        await workflow.wait_condition(
+            lambda: self._complete_task,
+            timeout=None,  # No timeout for long-running human-in-the-loop workflows
+        )
+        return "Task completed"
+
+    # TEMPORAL UI (localhost:8080):
+    # - Main workflow shows agent activities + ChildWorkflow activity when approval needed
+    # - Child workflow appears as separate "child-workflow-id" that waits for signal
+    # - Timeline: invoke_model_activity → ChildWorkflow (waiting) → invoke_model_activity (after approval)
+    #
+    # To approve: temporal workflow signal --workflow-id="child-workflow-id" --name="fulfill_order_signal" --input=true
+    # Production: Replace CLI with web dashboards/APIs that send signals programmatically
diff --git a/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/tests/test_agent.py b/examples/tutorials/10_async/10_temporal/080_open_ai_agents_sdk_human_in_the_loop/080_open_ai_agents_sdk_human_in_the_loop/tests/test_agent.py
@@ -0,0 +1,40 @@
+"""
+Tests for example-tutorial (OpenAI Agents SDK Human in the Loop)
+
+Prerequisites:
+    - AgentEx services running (make dev)
+    - Temporal server running
+    - Agent running: agentex agents run --manifest manifest.yaml
+
+Run: pytest tests/test_agent.py -v
+"""
+
+import pytest
+
+from agentex.lib.testing import test_agentic_agent, assert_valid_agent_response
+
+AGENT_NAME = "example-tutorial"
+
+
+@pytest.mark.asyncio
+async def test_agent_basic():
+    """Test basic agent functionality."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        response = await test.send_event("Test message", timeout_seconds=60.0)
+        assert_valid_agent_response(response)
+
+
+@pytest.mark.asyncio
+async def test_agent_streaming():
+    """Test streaming responses."""
+    async with test_agentic_agent(agent_name=AGENT_NAME) as test:
+        events = []
+        async for event in test.send_event_and_stream("Stream test", timeout_seconds=60.0):
+            events.append(event)
+            if event.get("type") == "done":
+                break
+        assert len(events) > 0
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
