ragvault/dist/helpers/fireworks.js

Securely manage and query your private data using a local vector database. Your private RAG.

import inquirer from "inquirer";
import { GetFireworksInstance } from "../utils/ai-providers.js";
import { getCollection } from "../utils/chroma-client.js";
import { PromptTemplate } from "@langchain/core/prompts";
export const answerQuestionFireworks = async (apiKey, username) => {
    const collection = await getCollection(username + "-ragvault");
    const { query } = await inquirer.prompt([
        {
            type: "input",
            name: "query",
            message: "Enter your query here",
        },
    ]);
    const chunks = await collection.query({
        queryTexts: [query],
        nResults: 2,
    });
    const fireworks = GetFireworksInstance(apiKey);
    const prompt = PromptTemplate.fromTemplate("You are a helpful assistant that can answer questions and help with tasks. You are given a question and a list of documents. You need to answer the question based on the given chunks of data. The chunks of data are: {context}. The question is: {question}.Do not recall that you are using chunks of data to answer the question. Talk like you are a human.");
    if (fireworks) {
        try {
            const chain = prompt.pipe(fireworks);
            const response = await chain.invoke({
                context: chunks.documents.join(","),
                question: query,
            });
            console.log("\n" + response.content + "\n");
        }
        catch (error) {
            console.log(error);
        }
    }
};