gistfile1.txt

========================================================================================= FAILURES =========================================================================================
__________________________________________________________________________________ test_yes_no_classifier __________________________________________________________________________________

yes_no_classifier = <src.query_helpers.yes_no_classifier.YesNoClassifier object at 0x7faa85532d90>, monkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7faa860917d0>

    def test_yes_no_classifier(yes_no_classifier, monkeypatch):
    
        monkeypatch.setattr(
            langchain.chains, "LLMChain", MockLLMChain(desired_response="9")
        )
    
        import utils.model_context
    
        class MockChainInterface:
            """
            Unfortunately, LangChainInterface is a callable class, which makes
            testing extra ugly
            """
    
            def __init__(self, *args, **kwargs):
                pass
    
            def __call__(self, *args, **kwargs):
                return "test response"
    
        monkeypatch.setattr(utils.model_context, "LangChainInterface", MockChainInterface)
    
>       response = yes_no_classifier.classify(
            conversation="1234", statement="The sky is blue."
        )

tests/unit/query_helpers/test_yes_no_classifier.py:56: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
src/query_helpers/yes_no_classifier.py:55: in classify
    llm_chain = LLMChain(llm=bare_llm, prompt=prompt_instructions, verbose=verbose)
../../../../.pyenv/versions/fastapi-ols-311/lib/python3.11/site-packages/langchain_core/load/serializable.py:97: in __init__
    super().__init__(**kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

__pydantic_self__ = LLMChain()
data = {'llm': <test_yes_no_classifier.test_yes_no_classifier.<locals>.MockChainInterface object at 0x7faa85e9d610>, 'prompt'...se.\nResponse: 0\n\nStatement: Apples are red.\nResponse: 9\n\nStatement: {statement}\nResponse:\n"), 'verbose': False}
values = {'callback_manager': None, 'callbacks': None, 'llm_kwargs': {}, 'memory': None, ...}, fields_set = {'llm', 'prompt', 'verbose'}
validation_error = ValidationError(model='LLMChain', errors=[{'loc': ('llm',), 'msg': 'instance of Runnable expected', 'type': 'type_erro...'instance of Runnable expected', 'type': 'type_error.arbitrary_type', 'ctx': {'expected_arbitrary_type': 'Runnable'}}])

    def __init__(__pydantic_self__, **data: Any) -> None:
        """
        Create a new model by parsing and validating input data from keyword arguments.
    
        Raises ValidationError if the input data cannot be parsed to form a valid model.
        """
        # Uses something other than `self` the first arg to allow "self" as a settable attribute
        values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
        if validation_error:
>           raise validation_error
E           pydantic.v1.error_wrappers.ValidationError: 2 validation errors for LLMChain
E           llm
E             instance of Runnable expected (type=type_error.arbitrary_type; expected_arbitrary_type=Runnable)
E           llm
E             instance of Runnable expected (type=type_error.arbitrary_type; expected_arbitrary_type=Runnable)

../../../../.pyenv/versions/fastapi-ols-311/lib/python3.11/site-packages/pydantic/v1/main.py:341: ValidationError