Language Translator Utilizing OpenAI – Analytics Vidhya


On this article, you’ll discover ways to construct a easy language translator app utilizing OpenAI API and Django Internet Utility Framework. Django is likely one of the widespread open-source internet utility frameworks of Python. Alongside the best way, you’ll be taught the important thing ideas and methods to make use of the OpenAI API for any job. OpenAI gives us with numerous fashions that can be utilized to unravel any job that entails language processing similar to analyzing and understanding the language in addition to producing content material(similar to code, photographs, and so forth).

As you all know, in at this time’s world language translation performs a vital position in bridging communication gaps between individuals who converse completely different languages. Furthermore, there’s a excessive demand for language translation apps and companies on the web at this time. To get together with this tutorial, you have to be accustomed to Python language and a bit of little bit of Django internet utility framework.

This text was printed as part of the Data Science Blogathon.

Getting Began on Language Translator

Earlier than entering into the event course of, initially, we have to arrange the event atmosphere together with the required packages. To make use of the OpenAI API, you might want to register an account and generate an API key. Allow us to begin by producing an API Key.

Create an OpenAI API Key

Go to the hyperlink and create a brand new account. Login to your account and click on in your account within the prime proper nook after which choose “View API Keys” from the drop-down menu as proven beneath:

And now you can create a brand new secret key by clicking on the button as proven within the beneath screenshot.


After clicking on the button, you’ll get one other window as proven beneath:


Give it a reputation and click on on Create a secret key. Save this as you’ll be utilizing it sooner or later.

Putting in the Essential Libraries

Set up Django

Allow us to begin by making a digital atmosphere as it’s the finest apply to all the time construct your initiatives in a digital atmosphere. Create a digital atmosphere utilizing the next command for Home windows customers

virtualenv env1

Activate the digital atmosphere utilizing the next command


Now that we are in our surroundings, we have to set up Django as it’s an exterior bundle. Set up Django utilizing the pip command as follows:

pip set up django

Set up OpenAI Library

The Openai Python library gives entry to the OpenAI API for all of the functions written in Python language. Use the next command to put in the library

pip set up --upgrade openai

Set up Dotenv

We’re putting in dotenv to learn an API key from the .env file. Python dotenv reads key-value pairs from the .env file and set them to atmosphere variables. Set up it utilizing the pip command as follows:

pip set up python-dotenv

Create a New Django Challenge

Allow us to begin creating a brand new Django undertaking and provides it a reputation. I’m naming it as “mysite”.  Use the next command to create a brand new undertaking

django-admin startproject mysite

At this level, you’ll be able to crosscheck if all the pieces is working or not. To take action, navigate to the undertaking listing:

cd mysite

And run the server utilizing the next command:

python runserver

You’ll be directed to an online web page on the localhost and the next web page can be displayed

Language Translator | OpenAI

Create a New App

Create a brand new Django app within the undertaking folder utilizing the beneath command

django-admin startapp core

You can provide any title to your app and I’m naming it “core”. Each time, you create a brand new app you need to register it within the file by including the app to the INSTALLED_APPS.










Add URLs

Open the file that’s within the initiatives listing and add the URL path to the utility URLs. Add the beneath code:

from django.contrib import admin
from django.urls import path,embody

urlpatterns = [

The embody operate will embody all of the URL patterns of ‘’ to the undertaking. However since now we have no file named ‘’ in our app folder, we should go forward and
create an empty file named ‘’ within the utility listing. We can be including urls to our views later on this article.

Creating Templates

Create a brand new folder named templates within the utility listing and create two template information as proven within the screenshot beneath:

Creating templates | Language Translator | OpenAI

Add the next code within the “base.html” file

<html lang="en">

    <title>{% block title %}{% endblock %}</title>

    <!-- CSS solely -->
    <hyperlink rel="stylesheet" href=""
        integrity="sha384-9aIt2nRpC12Uk9gS9baDl411NQApFmC26EwAOH8WgZl5MYYxFfc+NcPb1dKGj7Sk" crossorigin="nameless">

    <!-- JS, Popper.js, and jQuery -->
    <script src=""
    <script src="https://cdn.jsdelivr.web/npm/[email protected]/dist/umd/popper.min.js"
    <script src=""

    {% block content material %}
    {% endblock %}


Subsequent, open the file “primary.html” and add the beneath code as of now.

{% extends 'core/base.html' %}

{% block content material %}

{% endblock %}

We can be including a kind after making a view.

Create .env File and Set Your API Key

create a .env file within the undertaking listing and add the next traces :

OPENAI_KEY='insert your key right here'

Create Views

Open your “” file. Right here, I’m utilizing easy function-based views. So, allow us to add all of the imports initially

from django.shortcuts import render
import openai,os
from dotenv import load_dotenv

Subsequent, we get our API key in a variable referred to as api_key utilizing the getenv() operate as follows:


Allow us to now create a function-based view as follows:

def chatbot(request):
    if api_key shouldn't be None and request.methodology=='POST':
        user_input = request.POST.get('user_input')
        immediate=f"translate this textual content to hindi: {user_input}"


    return render(request,'core/primary.html',{"response":chatbot_response})

To start with, we’re setting the variable chatbot_response to none. Subsequent, we’re checking if the request methodology is POST and likewise if the API key shouldn’t be None, then we attempt to generate a response from Openai. We collect the enter of the consumer in a variable named “user_input” through the use of the get methodology and passing the title of the enter area which we can be including in the principle.html file. We’re setting the immediate to translate the enter message to Hindi. You’ll be able to specify any language over right here.

We then create a response object and declare the engine as “text-DaVinci-003”. You’ll be able to undergo the documentation to know extra about this. Setting the immediate to immediate and max tokens is given as 350 which signifies that the response can be of max 350 characters.

Replace Template

Now that now we have performed with our view, allow us to create a kind within the “primary.html” file to take the enter message from the consumer. We then generate the response within the view by passing the enter message and at last print the response in our template. Add the beneath code to the “primary.html” file:

{% extends 'core/base.html' %}

{% block content material %}

<h3> Write an instruction </h3>

<kind methodology="publish">
    {% csrf_token %}
    <enter sort="textual content" class="form-control" title="user_input">
    <button sort="submit" class="btn btn-primary mt-3">Submit</button>
{% if response %}
    {secure }
{% endif %}
{% endblock %}

Now, It’s time to run the server and test our utility. Run the applying utilizing the command

python runserver

You’ll get the web page as proven beneath

Language Translator | OpenAI

Allow us to give any enter and test

Language Translator | OpenAI

Allow us to attempt to change the language within the immediate message

immediate=f"translate this textual content to telugu: {user_input}"

Save and reload the web page

Language Translator | OpenAI

If we give an enter message of greater than 350 chars, we’ll get a response of solely as much as 350 chars.


Enter: Information science is the examine of knowledge to extract significant insights for enterprise. It’s a multidisciplinary method that mixes rules and practices from the fields of arithmetic, statistics, synthetic intelligence, and pc engineering to investigate massive quantities of knowledge.

Language Translator

As you’ll be able to see, the response can be lower than 350 tokens.


This text demonstrates on utilizing the OpenAI API with Python for language translator and a fundamental information to creating attention-grabbing internet apps utilizing AI expertise. We’re designing a easy internet app utilizing the Django internet utility framework that takes enter within the type of a sentence and interprets it into a unique language.

Key takeaways:

  • The OpenAI API can be utilized to carry out any job that entails pure language processing.
  • You’ll be able to both generate context (textual content, or photographs) and even translate textual content from one language to a different as we did on this article
  • Designing your immediate is a vital step as you program the mannequin by giving a set of directions.
  • Lastly, you additionally discovered use the OpenAI API and entry it by way of the Django internet app.

The media proven on this article shouldn’t be owned by Analytics Vidhya and is used on the Writer’s discretion.

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