Error in NextJS edge function: Attempted import error: './index.js' does not contain a default export (imported as 'cjs')

[gablabelle]

Hello there,

I'm trying to use gpt-tokenizer inside a NextJs edge function and get the following error

Attempted import error: './index.js' does not contain a default export (imported as 'cjs').

When using the require version of the import I get the following error:

{
  error: [TypeError: Cannot read properties of undefined (reading 'encodeChatGenerator')]
}

Here is the utility function that I'm using in the edge route:

import { type Message } from "ai";
import { encodeChat } from "gpt-tokenizer";

// const api = require("gpt-tokenizer/cjs/encoding/cl100k_base");
// const { encodeChat } = require("gpt-tokenizer");

// Their interface is missing the `function` role
interface ChatMessage extends Omit<Message, "role"> {
  role: "system" | "user" | "assistant" | undefined;
}

export function getTokenUsage(
  messages: Omit<Message, "id">[],
  model?:
    | "gpt-4"
    | "gpt-4-32k"
    | "gpt-4-0314"
    | "gpt-4-32k-0314"
    | "gpt-3.5-turbo"
    | "gpt-3.5-turbo-0301"
    | "text-davinci-003"
    | "text-davinci-002"
    | "text-davinci-001"
    | "text-curie-001"
    | "text-babbage-001"
    | "text-ada-001"
    | "davinci"
    | "curie"
    | "babbage"
    | "ada"
    | "code-davinci-002"
    | "code-davinci-001"
    | "code-cushman-002"
    | "code-cushman-001"
    | "davinci-codex"
    | "cushman-codex"
    | "text-davinci-edit-001"
    | "code-davinci-edit-001"
    | "text-embedding-ada-002"
    | "text-similarity-davinci-001"
    | "text-similarity-curie-001"
    | "text-similarity-babbage-001"
    | "text-similarity-ada-001"
    | "text-search-davinci-doc-001"
    | "text-search-curie-doc-001"
    | "text-search-babbage-doc-001"
    | "text-search-ada-doc-001"
    | "code-search-babbage-code-001"
    | "code-search-ada-code-001"
    | undefined,
  tokenLimit?: number
) {
  const chatTokens = encodeChat(messages as ChatMessage[], model);
  console.log({ chatTokens });
  console.log({ length: chatTokens.length });

  return chatTokens.length;
}