aupdate() — langchain Function Reference

Architecture documentation for the aupdate() function in caches.py from the langchain codebase.

Function python LangChainCore ApiManagement calls 1 called by 1

Entity Profile

LangChainCore→ ApiManagement→ aupdate() — langchain Function Reference

Dependency Diagram

graph TD
  aa4561f7_6b0b_67c8_1afe_71223099cb3f["aupdate()"]
  374b7b0c_f4fd_ba00_b93d_1a3cbb3b05cb["BaseCache"]
  aa4561f7_6b0b_67c8_1afe_71223099cb3f -->|defined in| 374b7b0c_f4fd_ba00_b93d_1a3cbb3b05cb
  ea890aa7_5e0f_70ac_d2f0_6bc39ac36227["aupdate()"]
  ea890aa7_5e0f_70ac_d2f0_6bc39ac36227 -->|calls| aa4561f7_6b0b_67c8_1afe_71223099cb3f
  ea890aa7_5e0f_70ac_d2f0_6bc39ac36227["aupdate()"]
  aa4561f7_6b0b_67c8_1afe_71223099cb3f -->|calls| ea890aa7_5e0f_70ac_d2f0_6bc39ac36227
  style aa4561f7_6b0b_67c8_1afe_71223099cb3f fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/caches.py lines 125–148

    async def aupdate(
        self, prompt: str, llm_string: str, return_val: RETURN_VAL_TYPE
    ) -> None:
        """Async update cache based on `prompt` and `llm_string`.

        The prompt and llm_string are used to generate a key for the cache.
        The key should match that of the look up method.

        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.
            return_val: The value to be cached. The value is a list of `Generation`
                (or subclasses).
        """
        return await run_in_executor(None, self.update, prompt, llm_string, return_val)