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Integration Tests for Agent Mark Complete (User Story 3)
Tests the end-to-end workflow of AI agent marking tasks complete via chat endpoint.
"""
import pytest
from tests.utils.agent_helpers import (
invoke_agent_with_message,
assert_tool_called,
extract_tool_calls
)
from tests.utils.task_helpers import create_test_task, get_task_by_id
@pytest.mark.integration
@pytest.mark.asyncio
async def test_agent_marks_task_complete_via_chat_endpoint(test_user, test_session):
"""
Test: Agent marks task complete via chat endpoint
Verifies that AI agent can mark a task complete through natural language.
"""
# Setup: Create a task
task = create_test_task(test_session, test_user.id, title="Buy groceries", completed=False)
# Execute
response = await invoke_agent_with_message(
user_id=test_user.id,
message=f"Mark task {task.id} as complete"
)
# Assert agent called mark_complete tool
assert_tool_called(response, "mark_complete")
# Verify task is marked complete
updated_task = get_task_by_id(test_session, task.id)
assert updated_task.completed is True
@pytest.mark.integration
@pytest.mark.asyncio
async def test_agent_marks_task_complete_with_natural_language_i_finished(test_user, test_session):
"""
Test: Agent marks task complete with natural language "I finished X"
Verifies that agent recognizes "I finished" intent and marks task complete.
"""
# Setup: Create a task
task = create_test_task(test_session, test_user.id, title="Buy groceries", completed=False)
# Execute - agent should list tasks first, then mark complete
response = await invoke_agent_with_message(
user_id=test_user.id,
message="I finished buying groceries"
)
# Agent should call list_tasks to find the task, then mark_complete
tool_calls = extract_tool_calls(response)
tool_names = [tc["tool"] for tc in tool_calls]
# Verify agent used appropriate tools
assert "list_tasks" in tool_names or "mark_complete" in tool_names
@pytest.mark.integration
@pytest.mark.asyncio
async def test_agent_lists_tasks_then_marks_specific_task_complete(test_user, test_session):
"""
Test: Agent lists tasks then marks specific task complete
Verifies multi-step workflow: list tasks, identify task, mark complete.
"""
# Setup: Create multiple tasks
task1 = create_test_task(test_session, test_user.id, title="Buy milk", completed=False)
task2 = create_test_task(test_session, test_user.id, title="Buy eggs", completed=False)
# Step 1: List tasks
response1 = await invoke_agent_with_message(
user_id=test_user.id,
message="Show my tasks"
)
assert_tool_called(response1, "list_tasks")
# Step 2: Mark specific task complete
response2 = await invoke_agent_with_message(
user_id=test_user.id,
message=f"Mark task {task1.id} as done"
)
assert_tool_called(response2, "mark_complete")
# Verify only task1 is completed
updated_task1 = get_task_by_id(test_session, task1.id)
updated_task2 = get_task_by_id(test_session, task2.id)
assert updated_task1.completed is True
assert updated_task2.completed is False
@pytest.mark.integration
@pytest.mark.asyncio
async def test_agent_marks_task_complete_by_title_reference(test_user, test_session):
"""
Test: Agent marks task complete by title reference
Verifies that agent can identify task by title and mark it complete.
"""
# Setup: Create a task
task = create_test_task(test_session, test_user.id, title="Call dentist", completed=False)
# Execute - reference task by title
response = await invoke_agent_with_message(
user_id=test_user.id,
message="I completed the dentist call"
)
# Agent should list tasks to find matching task, then mark complete
tool_calls = extract_tool_calls(response)
tool_names = [tc["tool"] for tc in tool_calls]
# Verify agent attempted to complete the task
assert "list_tasks" in tool_names or "mark_complete" in tool_names
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