Langchain

When we want something more personality and intelligence in our assistants, the first thing we think about is Openai, what if I tell you that there is a simple way to get the most out of your LLM?

Install

let's look at a simple but very valuable trick. to be able to know the user's intention, we have tried it before with DialogFlow but what a headache, let's go for something easier

pnpm i @langchain/openai @langchain/core zod

import { z } from "zod";
import { ChatOpenAI, ChatPromptTemplate } from "@langchain/openai";

export const openAI = new ChatOpenAI({
    modelName: 'gpt-4',
    openAIApiKey: 'YOUR_API_KEY_HERE',
});

const SYSTEM_STRUCT = `just only history based: 
{history}

Answer the users question as best as possible.`;

export const PROMPT_STRUCT = ChatPromptTemplate.fromMessages([
    ["system", SYSTEM_STRUCT],
    ["human", "{question}"]
]);

const catchIntention = z.object(
    {
        intention: z.enum(['UNKNOWN', 'SALES', 'GREETING', 'CLOSURE'])
            .describe('Categorize the following conversation and decide what the intention is')
    }
).describe('Given the following products, you should structure it in the best way, do not alter or edit anything');

const llmWithToolsCatchIntention = openAI.withStructuredOutput(catchIntention, {
    name: "CatchIntention",
});

export const getIntention = async (text: string): Promise<string> => {
    try {
        const { intention } = await PROMPT_STRUCT.pipe(llmWithToolsCatchIntention).invoke({
            question: text,
            history: await history.getHistory(state)
        });

        return Promise.resolve(String(intention).toLocaleLowerCase());
    } catch (errorIntention) {
        return Promise.resolve('unknown');
    }
};