test_chat_ollama_ignores_strict_arg() — langchain Function Reference

Architecture documentation for the test_chat_ollama_ignores_strict_arg() function in test_chat_models.py from the langchain codebase.

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_chat_ollama_ignores_strict_arg() — langchain Function Reference

Dependency Diagram

graph TD
  3eb71e80_665e_e46e_4f39_c7cb7a581e35["test_chat_ollama_ignores_strict_arg()"]
  9c4a2438_9884_cbb0_3cf5_de8827531653["test_chat_models.py"]
  3eb71e80_665e_e46e_4f39_c7cb7a581e35 -->|defined in| 9c4a2438_9884_cbb0_3cf5_de8827531653
  style 3eb71e80_665e_e46e_4f39_c7cb7a581e35 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/ollama/tests/unit_tests/test_chat_models.py lines 452–475

def test_chat_ollama_ignores_strict_arg() -> None:
    """Test that ChatOllama ignores the 'strict' argument."""
    response = [
        {
            "model": "test-model",
            "created_at": "2025-01-01T00:00:00.000000000Z",
            "done": True,
            "done_reason": "stop",
            "message": {"role": "assistant", "content": "Hello!"},
        }
    ]

    with patch("langchain_ollama.chat_models.Client") as mock_client_class:
        mock_client = MagicMock()
        mock_client_class.return_value = mock_client
        mock_client.chat.return_value = response

        llm = ChatOllama(model="test-model")
        # Invoke with strict=True
        llm.invoke([HumanMessage("Hello")], strict=True)

        # Check that 'strict' was NOT passed to the client
        call_kwargs = mock_client.chat.call_args[1]
        assert "strict" not in call_kwargs