How Setup Gemini AI for REST API using NodeJs

#ai #javascript #cloud

Project Prerequisites:

Node.js v18+
npm

Setting up Gemini AI for a REST API using Node.js involves a few steps. Gemini AI is a machine learning platform that offers various features for building and deploying machine learning models. Here's a basic guide on how to set up Gemini AI with Node.js for a REST API:

Sign up for Gemini AI: If you haven't already, sign up for an account on the Gemini AI website (https://deepmind.google/technologies/gemini/#introduction) and Build with Gemini (https://ai.google.dev/).

Create your API Key: Train or upload a machine learning model using the Gemini AI platform. Follow the instructions provided by Gemini AI to create and train your model based on your specific requirements.

For Documentation:
(https://ai.google.dev/tutorials/node_quickstart)

Create your project & Install Dependencies: In your Node.js project directory, initialize a new project if you haven't already, and install necessary dependencies:

mkdir gemini_nodes_api
npm init -y
npm install express axios body-parser

Set Up Your Node.js Server: Create a new file, index.js and .env, and set up a basic Express server:

const express = require('express');
const bodyParser = require('body-parser');

const { GoogleGenerativeAI } = require("@google/generative-ai");

// Access your API key as an environment variable (see "Set up your API key" above)
const genAI = new GoogleGenerativeAI(process.env.API_KEY);

console.log(genAI);

const app = express();
const port = process.env.PORT || 3001;

// Middleware to parse JSON bodies
app.use(bodyParser.json());

// Route to handle form submissions
app.post('/submit-form', (req, res) => {
    const formData = req.body;

    res.json(formData);
});

app.post('/text', async (req, res) => {
  const prompt = req.body.prompt;

  try {
    const model = genAI.getGenerativeModel({ model: "gemini-pro"});
    const result = await model.generateContent(prompt);
    const response = await result.response;
    const text = response.text();

    res.json({ text });
  } catch (error) {
    console.error(error);
    res.status(500).json({ error: 'Failed to generate text' });
  }
});


// Start the server
app.listen(port, () => {
    console.log(`Server is running on port ${port}`);
});

Replace 'API_KEY' with the actual URL provided by Gemini AI for making predictions.

Test Your API: Start your Node.js server by running node server.js in your terminal. You can then send POST requests to http://localhost:3000/text with the input data you want to make predictions on.

 node index.js

Remember to handle authentication, error handling, and any other necessary features according to your project requirements and Gemini AI's API documentation.

Enjoy your reading