test_configurable() — langchain Function Reference

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

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_configurable() — langchain Function Reference

Dependency Diagram

graph TD
  27f552a5_502a_d862_4baa_e7194c649e84["test_configurable()"]
  29aaa9ad_8f95_7e3c_f947_66f656fbb0e8["test_chat_models.py"]
  27f552a5_502a_d862_4baa_e7194c649e84 -->|defined in| 29aaa9ad_8f95_7e3c_f947_66f656fbb0e8
  style 27f552a5_502a_d862_4baa_e7194c649e84 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain_v1/tests/unit_tests/chat_models/test_chat_models.py lines 107–228

def test_configurable() -> None:
    """Test configurable chat model behavior without default parameters.

    Verifies that a configurable chat model initialized without default parameters:
    - Has access to all standard runnable methods (`invoke`, `stream`, etc.)
    - Blocks access to non-configurable methods until configuration is provided
    - Supports declarative operations (`bind_tools`) without mutating original model
    - Can chain declarative operations and configuration to access full functionality
    - Properly resolves to the configured model type when parameters are provided

    Example:
    ```python
    # This creates a configurable model without specifying which model
    model = init_chat_model()

    # This will FAIL - no model specified yet
    model.get_num_tokens("hello")  # AttributeError!

    # This works - provides model at runtime
    response = model.invoke("Hello", config={"configurable": {"model": "gpt-4o"}})
    ```
    """
    model = init_chat_model()

    for method in (
        "invoke",
        "ainvoke",
        "batch",
        "abatch",
        "stream",
        "astream",
        "batch_as_completed",
        "abatch_as_completed",
    ):
        assert hasattr(model, method)

    # Doesn't have access non-configurable, non-declarative methods until a config is
    # provided.
    for method in ("get_num_tokens", "get_num_tokens_from_messages"):
        with pytest.raises(AttributeError):
            getattr(model, method)

    # Can call declarative methods even without a default model.
    model_with_tools = model.bind_tools(
        [{"name": "foo", "description": "foo", "parameters": {}}],
    )

    # Check that original model wasn't mutated by declarative operation.
    assert model._queued_declarative_operations == []

    # Can iteratively call declarative methods.
    model_with_config = model_with_tools.with_config(
        RunnableConfig(tags=["foo"]),
        configurable={"model": "gpt-4o"},
    )
    assert model_with_config.model_name == "gpt-4o"  # type: ignore[attr-defined]

    for method in ("get_num_tokens", "get_num_tokens_from_messages"):
        assert hasattr(model_with_config, method)

    assert model_with_config.model_dump() == {  # type: ignore[attr-defined]
        "name": None,
        "bound": {
            "name": None,
            "disable_streaming": False,
            "disabled_params": None,
            "model_name": "gpt-4o",
            "temperature": None,
            "model_kwargs": {},
            "openai_api_key": SecretStr("foo"),
            "openai_api_base": None,
            "openai_organization": None,
            "openai_proxy": None,
            "output_version": None,
            "request_timeout": None,
            "max_retries": None,
            "presence_penalty": None,
            "reasoning": None,
            "reasoning_effort": None,
            "verbosity": None,
            "frequency_penalty": None,