mindcraft/src/models/gemini.js

import { GoogleGenerativeAI } from '@google/generative-ai';
import { toSinglePrompt } from '../utils/text.js';
import configJson from "../../config.json" assert { type: "json" };

export class Gemini {
    constructor(model_name, url) {
        this.model_name = model_name;
        this.url = url;

        if (!configJson.GEMINI_API_KEY) {
            throw new Error('Gemini API key missing! Make sure you set your GEMINI_API_KEY in your config.json.');
        }
        this.genAI = new GoogleGenerativeAI(configJson.GEMINI_API_KEY);
    }

    async sendRequest(turns, systemMessage) {
        let model;
        if (this.url) {
            model = this.genAI.getGenerativeModel(
                {model: this.model_name || "gemini-pro"},
                {baseUrl: this.url}
            );
        } else {
            model = this.genAI.getGenerativeModel(
                {model: this.model_name || "gemini-pro"}
            );
        }

        const stop_seq = '***';
        const prompt = toSinglePrompt(turns, systemMessage, stop_seq, 'model');
        const result = await model.generateContent(prompt);
        const response = await result.response;
        const text = response.text();
        if (!text.includes(stop_seq)) return text;
        const idx = text.indexOf(stop_seq);
        return text.slice(0, idx);
    }

    async embed(text) {
        let model;
        if (this.url) {
            model = this.genAI.getGenerativeModel(
                {model: this.model_name || "embedding-001"},
                {baseUrl: this.url}
            );
        } else {
            model = this.genAI.getGenerativeModel(
                {model: this.model_name || "embedding-001"}
            );
        }

        const result = await model.embedContent(text);
        return result.embedding;
    }
}