mirror of
https://github.com/temporal-community/temporal-ai-agent.git
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eb06cf5c8d
* Format codebase to satisfy linters * fixing pylance and ruff-checked files * contributing md, and type and formatting fixes * setup file capitalization * test fix
112 lines
3.5 KiB
Python
112 lines
3.5 KiB
Python
import asyncio
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import multiprocessing
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import sys
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from typing import AsyncGenerator
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import pytest
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import pytest_asyncio
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from temporalio.client import Client
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from temporalio.testing import WorkflowEnvironment
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# Due to https://github.com/python/cpython/issues/77906, multiprocessing on
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# macOS starting with Python 3.8 has changed from "fork" to "spawn". For
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# pre-3.8, we are changing it for them.
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if sys.version_info < (3, 8) and sys.platform.startswith("darwin"):
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multiprocessing.set_start_method("spawn", True)
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def pytest_addoption(parser):
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parser.addoption(
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"--workflow-environment",
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default="local",
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help="Which workflow environment to use ('local', 'time-skipping', or target to existing server)",
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)
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@pytest.fixture(scope="session")
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def event_loop():
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# See https://github.com/pytest-dev/pytest-asyncio/issues/68
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# See https://github.com/pytest-dev/pytest-asyncio/issues/257
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# Also need ProactorEventLoop on older versions of Python with Windows so
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# that asyncio subprocess works properly
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if sys.version_info < (3, 8) and sys.platform == "win32":
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loop = asyncio.ProactorEventLoop()
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else:
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loop = asyncio.get_event_loop_policy().new_event_loop()
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yield loop
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loop.close()
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@pytest_asyncio.fixture(scope="session")
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async def env(request) -> AsyncGenerator[WorkflowEnvironment, None]:
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env_type = request.config.getoption("--workflow-environment")
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if env_type == "local":
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env = await WorkflowEnvironment.start_local(
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dev_server_extra_args=[
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"--dynamic-config-value",
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"frontend.enableExecuteMultiOperation=true",
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]
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)
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elif env_type == "time-skipping":
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env = await WorkflowEnvironment.start_time_skipping()
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else:
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env = WorkflowEnvironment.from_client(await Client.connect(env_type))
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yield env
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await env.shutdown()
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@pytest_asyncio.fixture
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async def client(env: WorkflowEnvironment) -> Client:
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return env.client
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@pytest.fixture
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def sample_agent_goal():
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"""Sample agent goal for testing."""
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from models.tool_definitions import AgentGoal, ToolArgument, ToolDefinition
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return AgentGoal(
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id="test_goal",
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category_tag="test",
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agent_name="TestAgent",
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agent_friendly_description="A test agent for testing purposes",
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description="Test goal for agent testing",
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tools=[
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ToolDefinition(
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name="TestTool",
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description="A test tool for testing purposes",
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arguments=[
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ToolArgument(
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name="test_arg", type="string", description="A test argument"
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)
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],
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)
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],
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)
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@pytest.fixture
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def sample_conversation_history():
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"""Sample conversation history for testing."""
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return {
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"messages": [
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{"actor": "user", "response": "Hello, I need help with testing"},
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{"actor": "agent", "response": "I can help you with that"},
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]
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}
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@pytest.fixture
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def sample_combined_input(sample_agent_goal):
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"""Sample combined input for workflow testing."""
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from collections import deque
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from models.data_types import AgentGoalWorkflowParams, CombinedInput
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tool_params = AgentGoalWorkflowParams(
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conversation_summary="Test conversation summary",
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prompt_queue=deque(), # Start with empty queue for most tests
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)
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return CombinedInput(agent_goal=sample_agent_goal, tool_params=tool_params)
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