GPT-3.5 Turbo Instruct with Node.js, Python, and MERN Stack for Advanced Web Applications

gpt-3.5 turbo instruct nodejs python mern

OpenAI’s GPT-3.5 Turbo Instruct is the newest iteration in language model technology, designed to execute instructions with high precision. This article delves into the integration of GPT-3.5 Turbo Instruct across Node.js, Python, and React in a MERN stack.

What is GPT-3.5 Turbo Instruct?

As previously discussed in this article, GPT-3.5 Turbo Instruct, an advanced model, is engineered to provide coherent and contextually relevant responses, making it a versatile asset for various applications.

What’s new in GPT-3.5 Turbo Instruct?

GPT-3.5 Turbo Instruct is a refined version of GPT-3, aimed at performing natural language tasks with heightened accuracy and reduced toxicity.

How to use GPT-3.5 Turbo Instruct Node.js, Python and MERN?

GPT-3.5 Turbo Instruct brings a new level of interaction to applications. Whether you’re working with Node.js or Python on the backend, integrating this model is straightforward. Especially within a MERN stack, it harmonizes well with React on the frontend, making it easier to build intelligent, user-friendly applications. This setup allows developers to harness the model’s natural language processing ability, delivering a more engaging user experience. With GPT-3.5 Turbo Instruct, the transition between the backend logic, powered by Node.js or Python, and the interactive frontend, built with React, becomes smoother, paving the way for more advanced web applications.

Using GPT-3.5 Turbo Instruct with Node.js

Setting up GPT-3.5 Turbo Instruct in Node.js Environment

Setting up GPT-3.5 Turbo Instruct in a Node.js environment is a straightforward process. Here’s a simplified guide:

Create a New Node.js Application:
- Run npm init to create a new Node.js app. Follow the prompts to set up your project.
Install Necessary Packages:
- Install the OpenAI package using npm install --save openai or yarn add openai.
Setup OpenAI:
- Import the OpenAI library in your code with import OpenAI from 'openai';.
- Instantiate OpenAI with your API key:

npm install --save openai

Important: gpt-3.5-turbo-instruct is a completion model, hence you will need to use the completion function to get responses.

import OpenAI from 'openai';

const openai = new OpenAI({
        apiKey: 'my api key',
      });

async function main() {
  const response = await openai.completions.create({
        model: "gpt-3.5-turbo-instruct",
        prompt: `Tell me a story about node.js`,
        temperature: 1.00,
        max_tokens: 150,
        top_p: 1,
        frequency_penalty: 0,
        presence_penalty: 0,
        });

  console.log(response.data.choices);
}

main();

Usage with Python

Setting up GPT-3.5 Turbo Instruct in Python Environment

Setting up GPT-3.5 Turbo Instruct in a Python environment involves a few steps:

Create a Python Environment:

Create a new virtual environment by running:
python -m venv myenv.
Activate the environment:
Windows:

myenv\Scripts\activate

Linux/macOS:

source myenv/bin/activate

Install Necessary Packages:

Install the openai library using pip

pip install openai

Setup OpenAI:

Import the openai library in your code: import openai.
Set your API key: openai.api_key = 'your-api-key-here'.

Interact with GPT-3.5 Turbo Instruct:

Use the openai.Completion.create method to interact with the model, providing the necessary parameters.

Here is the code:

import openai

openai.api_key = "sk......."

response = openai.Completion.create(
    model="gpt-3.5-turbo-instruct",
    prompt="Write a poem about Python"
)

print(response.choices[0].message.content)

Usage with MERN Stack

In a MERN stack, create a backend service in Node.js or Python as outlined above. Build a React frontend to communicate with this service, sending requests to and receiving responses from GPT-3.5 Turbo Instruct.

Usage with React

Let’s walk through how to build a simple frontend in React to interact with the backend service.

Example:

import React, { useState } from 'react';
import axios from 'axios';

function GPTComponent() {
  const [prompt, setPrompt] = useState('');
  const [result, setResult] = useState('');

  const handleFetch = async () => {
    try {
      const response = await axios.post('/api/gpt-3.5-turbo', { prompt });
      setResult(response.data.choices[0].message.content);
    } catch (error) {
      console.error('Error fetching GPT-3.5 Turbo Instruct response:', error);
    }
  };

  return (
    <div>
      <input
        type="text"
        value={prompt}
        onChange={(e) => setPrompt(e.target.value)}
        placeholder="Enter your prompt here"
      />
      <button onClick={handleFetch}>Fetch GPT Response</button>
      <textarea value={result} readOnly />
    </div>
  );
}

export default GPTComponent;

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