Method lookup

libs/core/langchain_core/caches.py:51–70

Look up based on prompt and llm_string. A cache implementation is expected to generate a key from the 2-tuple of prompt and llm_string (e.g., by concatenating them with a delimiter). Args: prompt: a string representation of the prompt. In the

(self, prompt: str, llm_string: str)

    @abstractmethod
    def lookup(self, prompt: str, llm_string: str) -> Optional[RETURN_VAL_TYPE]:
        """Look up based on prompt and llm_string.

        A cache implementation is expected to generate a key from the 2-tuple
        of prompt and llm_string (e.g., by concatenating them with a delimiter).

        Args:
            prompt: a string representation of the prompt.
                    In the case of a Chat model, the prompt is a non-trivial
                    serialization of the prompt into the language model.
            llm_string: A string representation of the LLM configuration.
                This is used to capture the invocation parameters of the LLM
                (e.g., model name, temperature, stop tokens, max tokens, etc.).
                These invocation parameters are serialized into a string
                representation.

        Returns:
            On a cache miss, return None. On a cache hit, return the cached value.
            The cached value is a list of Generations (or subclasses).
        """

    @abstractmethod
    def update(self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE) -> None: