Hello,

I'm unable to figure out how to get the values from the langchain calculator. I simply want to track API usage but the documentation is pretty limited.

Here is my API route's code. The onCompletion callback only returns a string, same thing for the onToken callback.

I've created a new Calculator() and I'm passing it to the tools field but from there I'm stuck. Should I pass something to the constructor or something?

Any help would be greatly appreciated.

import { kv } from "@vercel/kv";
import { LangChainStream, StreamingTextResponse, type Message } from "ai";
import { ChatOpenAI } from "langchain/chat_models/openai";
import { AIMessage, HumanMessage } from "langchain/schema";
import { Calculator } from "langchain/tools/calculator";
import { getCurrentSession } from "@/lib/session";
import { nanoid } from "@/lib/utils";

export const runtime = "edge";

export async function POST(req: Request) {
  const userId = (await getCurrentSession())?.user.id;

  if (!userId) {
    return new Response("Unauthorized", {
      status: 401,
    });
  }

  const { id, messages, previewToken } = await req.json();

  const { stream, handlers } = LangChainStream({
    async onCompletion(completion) {
      const title = messages[0].content.substring(0, 100);
      const chatId = id ?? nanoid();
      const createdAt = Date.now();
      const path = `/chat/${chatId}`;
      const payload = {
        id: chatId,
        title,
        userId,
        createdAt,
        path,
        messages: [
          ...messages,
          {
            content: completion,
            role: "assistant",
          },
        ],
      };
      await kv.hmset(`chat:${id}`, payload);
      await kv.zadd(`user:chat:${userId}`, {
        score: createdAt,
        member: `chat:${id}`,
      });
    },
    onToken(token) {
      console.log({ token });
    },
  });

  const llm = new ChatOpenAI({
    streaming: true,
    modelName: "gpt-3.5-turbo",
    temperature: 0,
    configuration: {
      apiKey: previewToken || process.env.OPENAI_API_KEY,
    },
  });

  llm
    .call(
      (messages as Message[]).map((m) =>
        m.role == "user"
          ? new HumanMessage(m.content)
          : new AIMessage(m.content)
      ),
      {
        tools: [new Calculator()],
      },
      [handlers]
    )
    .catch(console.error);

  return new StreamingTextResponse(stream);
}