langchain/chains/pal/base.py/PALChain/_call
class PALChain:    def _call(
        self,
        inputs: Dict[str, Any],
        run_manager: Optional[CallbackManagerForChainRun] = None,
    ) -> Dict[str, str]:
        _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
        code = self.llm_chain.predict(
            stop=[self.stop], callbacks=_run_manager.get_child(), **inputs
        )
        _run_manager.on_text(code, color="green", end="\n", verbose=self.verbose)
        repl = PythonREPL(_globals=self.python_globals, _locals=self.python_locals)
        res = repl.run(code + f"\n{self.get_answer_expr}")
        output = {self.output_key: res.strip()}
        if self.return_intermediate_steps:
            output["intermediate_steps"] = code
        return output