work on tests

.gitignore

@@ -32,3 +32,4 @@ coverage.xml
 .idea/
 
 .env
+./tests/*.env

README.md

@@ -47,3 +47,14 @@ See [the guide to adding goals and tools](./adding-goals-and-tools.md) for more
 
 ## For Temporal SAs
 Check out the [slides](https://docs.google.com/presentation/d/1wUFY4v17vrtv8llreKEBDPLRtZte3FixxBUn0uWy5NU/edit#slide=id.g3333e5deaa9_0_0) here and the enablement guide here (TODO).
+
+## Tests
+
+Running the tests requires `poe` and `pytest_asyncio` to be installed.
+
+    python -m pip install poethepoet
+    python -m pip install pytest_asyncio
+
+Once you have `poe` and `pytest_asyncio` installed you can run:
+
+    poe test

pyproject.toml

@@ -15,6 +15,12 @@ packages = [
 [tool.poetry.urls]
 "Bug Tracker" = "https://github.com/temporalio/samples-python/issues"
 
+[tool.poe.tasks]
+format = [{cmd = "black ."}, {cmd = "isort ."}]
+lint = [{cmd = "black --check ."}, {cmd = "isort --check-only ."}, {ref = "lint-types" }]
+lint-types = "mypy --check-untyped-defs --namespace-packages ."
+test = "pytest"
+
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 temporalio = "^1.8.0"

scripts/find_events_test.py

@@ -1,8 +1,8 @@
-from tools.search_events import find_events
+from tools.search_flights import search_flights
 import json
 
 # Example usage
 if __name__ == "__main__":
     search_args = {"city": "Sydney", "month": "July"}
-    results = find_events(search_args)
+    results = search_flights(search_args)
     print(json.dumps(results, indent=2))

tests/agent_goal_workflow_test.py

@@ -1,53 +0,0 @@
-import asyncio
-
-from temporalio.client import Client, WorkflowExecutionStatus
-from temporalio.worker import Worker
-from temporalio.testing import TestWorkflowEnvironment
-from api.main import get_initial_agent_goal
-from models.data_types import AgentGoalWorkflowParams, CombinedInput
-from workflows.agent_goal_workflow import AgentGoalWorkflow
-from activities.tool_activities import ToolActivities, dynamic_tool_activity
-
-
-async def asyncSetUp(self):
-    # Set up the test environment
-    self.env = await TestWorkflowEnvironment.create_local()
-
-async def asyncTearDown(self):
-    # Clean up after tests
-    await self.env.shutdown()
-
-async def test_flight_booking(client: Client):
-
-    task_queue_name = "agent-ai-workflow"
-    workflow_id = "agent-workflow"
-    
-    initial_agent_goal = get_initial_agent_goal()
-
-    # Create combined input
-    combined_input = CombinedInput(
-        tool_params=AgentGoalWorkflowParams(None, None),
-        agent_goal=initial_agent_goal,
-    )
-
-    workflow_id = "agent-workflow"
-    async with Worker(client, task_queue=task_queue_name, workflows=[AgentGoalWorkflow], activities=[ToolActivities.agent_validatePrompt, ToolActivities.agent_toolPlanner, dynamic_tool_activity]):
-
-        # todo set goal categories for scenarios
-        handle = await client.start_workflow(
-            AgentGoalWorkflow.run, id=workflow_id, task_queue=task_queue_name
-        )
-        # todo send signals based on 
-        await handle.signal(AgentGoalWorkflow.user_prompt, "book flights")
-        await handle.signal(AgentGoalWorkflow.user_prompt, "sydney in september")
-        assert WorkflowExecutionStatus.RUNNING == (await handle.describe()).status
-
-        
-        #assert ["Hello, user1", "Hello, user2"] == await handle.result()
-        await handle.signal(AgentGoalWorkflow.user_prompt, "I'm all set, end conversation")
-        assert WorkflowExecutionStatus.COMPLETED == (await handle.describe()).status
-
-   
-
-
-    

tests/conftest.py

@@ -0,0 +1,55 @@
+import asyncio
+import multiprocessing
+import sys
+from typing import AsyncGenerator
+
+import pytest
+import pytest_asyncio
+from temporalio.client import Client
+from temporalio.testing import WorkflowEnvironment
+
+# Due to https://github.com/python/cpython/issues/77906, multiprocessing on
+# macOS starting with Python 3.8 has changed from "fork" to "spawn". For
+# pre-3.8, we are changing it for them.
+if sys.version_info < (3, 8) and sys.platform.startswith("darwin"):
+    multiprocessing.set_start_method("spawn", True)
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--workflow-environment",
+        default="local",
+        help="Which workflow environment to use ('local', 'time-skipping', or target to existing server)",
+    )
+
+
+@pytest.fixture(scope="session")
+def event_loop():
+    # See https://github.com/pytest-dev/pytest-asyncio/issues/68
+    # See https://github.com/pytest-dev/pytest-asyncio/issues/257
+    # Also need ProactorEventLoop on older versions of Python with Windows so
+    # that asyncio subprocess works properly
+    if sys.version_info < (3, 8) and sys.platform == "win32":
+        loop = asyncio.ProactorEventLoop()
+    else:
+        loop = asyncio.get_event_loop_policy().new_event_loop()
+    yield loop
+    loop.close()
+
+
+@pytest_asyncio.fixture(scope="session")
+async def env(request) -> AsyncGenerator[WorkflowEnvironment, None]:
+    env_type = request.config.getoption("--workflow-environment")
+    if env_type == "local":
+        env = await WorkflowEnvironment.start_local()
+    elif env_type == "time-skipping":
+        env = await WorkflowEnvironment.start_time_skipping()
+    else:
+        env = WorkflowEnvironment.from_client(await Client.connect(env_type))
+    yield env
+    await env.shutdown()
+
+
+@pytest_asyncio.fixture
+async def client(env: WorkflowEnvironment) -> Client:
+    return env.client

tests/workflowtests/agent_goal_workflow_test.py

@@ -0,0 +1,80 @@
+from temporalio.client import Client, WorkflowExecutionStatus
+from temporalio.worker import Worker
+import concurrent.futures
+from temporalio.testing import WorkflowEnvironment
+from api.main import get_initial_agent_goal
+from models.data_types import AgentGoalWorkflowParams, CombinedInput
+from workflows.agent_goal_workflow import AgentGoalWorkflow
+from activities.tool_activities import ToolActivities, dynamic_tool_activity
+from unittest.mock import patch
+from dotenv import load_dotenv
+import os
+from contextlib import contextmanager
+
+
+@contextmanager
+def my_context():
+    print("Setup")
+    yield "some_value"  # Value assigned to 'as' variable
+    print("Cleanup")
+
+
+
+async def test_flight_booking(client: Client):
+
+    #load_dotenv("test_flights_single.env")
+    
+    with my_context() as value:
+        print(f"Working with {value}")
+    
+        
+        # Create the test environment
+        #env = await WorkflowEnvironment.start_local()
+        #client = env.client
+        task_queue_name = "agent-ai-workflow"
+        workflow_id = "agent-workflow"
+
+        with concurrent.futures.ThreadPoolExecutor(max_workers=100) as activity_executor:        
+            worker = Worker(
+                client, 
+                task_queue=task_queue_name,
+                workflows=[AgentGoalWorkflow],
+                activities=[ToolActivities.agent_validatePrompt, ToolActivities.agent_toolPlanner, ToolActivities.get_wf_env_vars, dynamic_tool_activity],
+                activity_executor=activity_executor,
+            )
+
+            async with worker:                 
+                initial_agent_goal = get_initial_agent_goal()
+                # Create combined input
+                combined_input = CombinedInput(
+                    tool_params=AgentGoalWorkflowParams(None, None),
+                    agent_goal=initial_agent_goal,
+                )
+
+                prompt="Hello!"
+
+                #async with Worker(client, task_queue=task_queue_name, workflows=[AgentGoalWorkflow], activities=[ToolActivities.agent_validatePrompt, ToolActivities.agent_toolPlanner, dynamic_tool_activity]):
+
+                # todo set goal categories for scenarios
+                handle = await client.start_workflow(
+                    AgentGoalWorkflow.run,
+                    combined_input,
+                    id=workflow_id, 
+                    task_queue=task_queue_name,
+                    start_signal="user_prompt",
+                    start_signal_args=[prompt],
+                )
+                # todo send signals to simulate user input
+                # await handle.signal(AgentGoalWorkflow.user_prompt, "book flights") # for multi-goal
+                await handle.signal(AgentGoalWorkflow.user_prompt, "sydney in september")
+                assert WorkflowExecutionStatus.RUNNING == (await handle.describe()).status
+
+                
+                #assert ["Hello, user1", "Hello, user2"] == await handle.result()
+                await handle.signal(AgentGoalWorkflow.user_prompt, "I'm all set, end conversation")
+                
+                #assert WorkflowExecutionStatus.COMPLETED == (await handle.describe()).status
+
+                result = await handle.result()
+                #todo dump workflow history for analysis optional
+                #todo assert result is good