temporal-ai-agent/TESTING.md

Testing the Temporal AI Agent

This guide provides instructions for running the comprehensive test suite for the Temporal AI Agent project.

Quick Start

1. Install dependencies:

   poetry install --with dev
   

2. Run all tests:

   poetry run pytest
   

3. Run with time-skipping for faster execution:

   poetry run pytest --workflow-environment=time-skipping
   

Test Categories

Unit Tests

• Activity Tests: tests/test_tool_activities.py
  • LLM integration (mocked)
  • Environment configuration
  • JSON processing
  • Dynamic tool execution

Integration Tests

• Workflow Tests: tests/test_agent_goal_workflow.py
  • Full workflow execution
  • Signal and query handling
  • State management
  • Error scenarios

Running Specific Tests

# Run only activity tests
poetry run pytest tests/test_tool_activities.py -v

# Run only workflow tests  
poetry run pytest tests/test_agent_goal_workflow.py -v

# Run a specific test
poetry run pytest tests/test_tool_activities.py::TestToolActivities::test_sanitize_json_response -v

# Run tests matching a pattern
poetry run pytest -k "validation" -v

Test Environment Options

Local Environment (Default)

poetry run pytest --workflow-environment=local

Time-Skipping Environment (Recommended for CI)

poetry run pytest --workflow-environment=time-skipping

External Temporal Server

poetry run pytest --workflow-environment=localhost:7233

Environment Variables

Tests can be configured with these environment variables:

• LLM_MODEL: Model for LLM testing (default: "openai/gpt-4")
• LLM_KEY: API key for LLM service (mocked in tests)
• LLM_BASE_URL: Custom LLM endpoint (optional)

Test Coverage

The test suite covers:

✅ Workflows

• AgentGoalWorkflow initialization and execution
• Signal handling (user_prompt, confirm, end_chat)
• Query methods (conversation history, agent goal, tool data)
• State management and conversation flow
• Validation and error handling

✅ Activities

• ToolActivities class methods
• LLM integration (mocked)
• Environment variable handling
• JSON response processing
• Dynamic tool activity execution

✅ Integration

• End-to-end workflow execution
• Activity registration in workers
• Temporal client interactions

Test Output

Successful test run example:

============================== test session starts ==============================
platform darwin -- Python 3.11.3, pytest-8.3.5, pluggy-1.5.0
rootdir: /Users/steveandroulakis/Documents/Code/agentic/temporal-demo/temporal-ai-agent
configfile: pyproject.toml
plugins: anyio-4.5.2, asyncio-0.26.0
collected 21 items

tests/test_tool_activities.py::TestToolActivities::test_sanitize_json_response PASSED
tests/test_tool_activities.py::TestToolActivities::test_parse_json_response_success PASSED
tests/test_tool_activities.py::TestToolActivities::test_get_wf_env_vars_default_values PASSED
...

============================== 21 passed in 12.5s ==============================

Troubleshooting

Common Issues

1. Module not found errors: Run poetry install --with dev
2. Async warnings: These are expected with pytest-asyncio and can be ignored
3. Test timeouts: Use --workflow-environment=time-skipping for faster execution
4. Import errors: Check that you're running tests from the project root directory

Debugging Tests

Enable verbose logging:

poetry run pytest --log-cli-level=DEBUG -s

Run with coverage:

poetry run pytest --cov=workflows --cov=activities

Continuous Integration

For CI environments, use:

poetry run pytest --workflow-environment=time-skipping --tb=short

Additional Resources

• See tests/README.md for detailed testing documentation
• Review tests/conftest.py for available test fixtures
• Check individual test files for specific test scenarios

Test Architecture

The tests use:

• Temporal Testing Framework: For workflow and activity testing
• pytest-asyncio: For async test support
• unittest.mock: For mocking external dependencies
• Test Fixtures: For consistent test data and setup

All external dependencies (LLM calls, file I/O) are mocked to ensure fast, reliable tests.