_prepare_input() — langchain Function Reference

Architecture documentation for the _prepare_input() function in string_run_evaluator.py from the langchain codebase.

Function python LangChainCore Runnables called by 2

Entity Profile

LangChainCore→ Runnables→ _prepare_input() — langchain Function Reference

Dependency Diagram

graph TD
  2ca03f02_b9e1_8677_eda6_1008a8b4b7d4["_prepare_input()"]
  96e174c1_4107_a88b_8d98_3f22e5d7fb20["StringRunEvaluatorChain"]
  2ca03f02_b9e1_8677_eda6_1008a8b4b7d4 -->|defined in| 96e174c1_4107_a88b_8d98_3f22e5d7fb20
  d3515eaf_6765_8d34_0615_40c3ff4f20d0["_call()"]
  d3515eaf_6765_8d34_0615_40c3ff4f20d0 -->|calls| 2ca03f02_b9e1_8677_eda6_1008a8b4b7d4
  45efc57d_2b9e_96a6_a608_68913f941b40["_acall()"]
  45efc57d_2b9e_96a6_a608_68913f941b40 -->|calls| 2ca03f02_b9e1_8677_eda6_1008a8b4b7d4
  style 2ca03f02_b9e1_8677_eda6_1008a8b4b7d4 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/smith/evaluation/string_run_evaluator.py lines 298–314

    def _prepare_input(self, inputs: dict[str, Any]) -> dict[str, str]:
        run: Run = inputs["run"]
        example: Example | None = inputs.get("example")
        evaluate_strings_inputs = self.run_mapper(run)
        if not self.string_evaluator.requires_input:
            # Hide warning about unused input
            evaluate_strings_inputs.pop("input", None)
        if example and self.example_mapper and self.string_evaluator.requires_reference:
            evaluate_strings_inputs.update(self.example_mapper(example))
        elif self.string_evaluator.requires_reference:
            msg = (
                f"Evaluator {self.name} requires an reference"
                " example from the dataset,"
                f" but none was provided for run {run.id}."
            )
            raise ValueError(msg)
        return evaluate_strings_inputs