Function test_session_memory_demo

tests/test_integration.py:123–241

Test session memory functionality across multiple agent instances. This is the integration test for session note tool, converted from example_memory.py.

()

@pytest.mark.asyncio
async def test_session_memory_demo():
    """Test session memory functionality across multiple agent instances.

    This is the integration test for session note tool,
    converted from example_memory.py.
    """
    print("\n" + "=" * 80)
    print("Integration Test: Session Memory Demo")
    print("=" * 80)

    # Load config
    config_path = Path("mini_agent/config/config.yaml")
    if not config_path.exists():
        pytest.skip("config.yaml not found")

    config = Config.from_yaml(config_path)

    # Check API key
    if not config.llm.api_key or config.llm.api_key == "YOUR_MINIMAX_API_KEY_HERE":
        pytest.skip("API key not configured")

    # Use temporary workspace
    with tempfile.TemporaryDirectory() as workspace_dir:
        # Use simplified system prompt for faster testing
        system_prompt = """You are a helpful AI assistant.

You have record_note and recall_notes tools:
- record_note: Save important information (use category to organize)
- recall_notes: Retrieve saved information
"""

        # Initialize LLM
        llm_client = LLMClient(
            api_key=config.llm.api_key,
            api_base=config.llm.api_base,
            model=config.llm.model,
        )

        # Memory file path
        memory_file = Path(workspace_dir) / ".agent_memory.json"

        # Initialize tools (only Session Note Tools for this test)
        tools = [
            SessionNoteTool(memory_file=str(memory_file)),
            RecallNoteTool(memory_file=str(memory_file)),
        ]

        print("\n📝 Creating Agent with Session Note tools...")
        agent = Agent(
            llm_client=llm_client,
            system_prompt=system_prompt,
            tools=tools,
            max_steps=8,  # Reduced from 15
            workspace_dir=workspace_dir,
        )

        # Task 1: First conversation - agent should save memories
        task1 = """