def pair_tool_calls()

in src/dfcx_scrapi/tools/evaluations.py [0:0]

• 21 lines of code
• 9 McCabe index (conditional complexity)

    def pair_tool_calls(self, df: pd.DataFrame) -> pd.DataFrame:
        """Pairs user utterances with indices of relevant tool invocations."""

        df["tool_pair"] = pd.Series(dtype="string")
        grouped = df.groupby("eval_id")

        for _, group in grouped:
            tool_indices = []
            last_user_utterance_index = None

            for index, row in group.iterrows():
                if row["action_type"] == "User Utterance":
                    # Assign accumulated tool indices to
                    # the *previous* user utterance (if any)
                    if last_user_utterance_index is not None:
                        df.loc[last_user_utterance_index, "tool_pair"] = (
                            str(tool_indices)
                        )
                    # Reset for the current user utterance:
                    tool_indices = []
                    last_user_utterance_index = index

                elif row["action_type"] == "Tool Invocation":
                    tool_indices.append(index)

            # After processing the group, assign any remaining
            # tool indices to the last user utterance
            if last_user_utterance_index is not None and tool_indices:
                df.loc[last_user_utterance_index, "tool_pair"] = (
                    str(tool_indices)
                )

        return df