How to Build an AI Translator App with React Native and GPT-3

Table of Contents

• Introduction
• Designing the App Interface
• Connecting to the GPT-3 API
• Crafting the Prompt for GPT-3
• Styling and Final Touches
• Conclusion and Next Steps

Introduction to the App's Capabilities

The app demonstrated in the video enables users to instantly translate angry rants into more polite statements. This is made possible by GPT-3, OpenAI's latest natural language processing model.

GPT-3 is the most advanced AI to date for understanding and generating human language. It was trained on virtually all text on the internet prior to 2021, giving it an incredibly broad knowledge base to draw from.

As illustrated through examples in the video, GPT-3 can take on different personas and properly respond based on the provided context. This ability is core to translating rude statements into polite ones - GPT-3 takes on the persona of a helpful chatbot aiming to rephrase issues constructively.

Overview of App Capabilities

The key functions of the app are:

• Allow users to enter a rant
• Leverage GPT-3 to rephrase the rant in a polite, constructive way
• Display the translated output to the user

Core Functions of the App

In addition to the translation capabilities, the app needs to:

• Connect to the GPT-3 API to leverage the AI model
• Have an interface for text input/output
• Offset costs by incorporating ads and tips

Designing a Simple Yet Effective App Interface

The video focuses on core app functionality over graphic design aesthetics. However, some basic design is required for an intuitive user experience.

Figma was used to mock up the app layout. It consists of a heading banner, text input and output fields, a 'Translate Rant' button, and some sample translations to demonstrate capabilities.

Connecting to the Powerful GPT-3 API

With the front-end interface designed, the next key step is integrating with the GPT-3 API to enable advanced text generation behind the scenes.

The OpenAI npm package provides easy access to GPT-3. After installation, API keys grant access to start calling the model with prompts.

Getting Access Keys

Users need to sign up on OpenAI's site to access API keys. Both a general key and secret organization key are provided, though only the main key is required here.

Installing the OpenAI Package

The OpenAI npm package is installed with:

npm install openai

This provides access to call GPT-3 from Node.js code.

Calling the API in React

With keys set up, the OpenAI package can be imported and leveraged in React:

import { Configuration, OpenAIApi } from 'openai';
const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY
});
const openai = new OpenAIApi(configuration);

Crafting the Prompt for GPT-3

With API access in place, properly structuring the text prompt for GPT-3 is crucial to generating the desired politic translations.

OpenAI provides an interactive Playground to experiment with prompts before integrating them.

Testing Prompts in the Playground

A variety of model sizes with different speeds, costs, and capabilities are available. After some experimentation, the Curie model balance performance and cost well for this use case. The following template prompt structure triggered accurate translations:

You are a chatbot trying to help a friend relate an issue to their boss in a polite way. Your job is to translate the issue in a way that will be received in a more positive light.
Friend: [User Rant Text]
Translation:

Integrating the Prompt into React Code

The refined Playground prompt can be inserted directly into the app's React code:

const response = await openai.createCompletion({
 prompt: `You are... [User Rant Text] Translation:`,
 model: "curie"
});

The user input text then fills in the rant portion dynamically at runtime.

Styling and Final Touches

With core functionality built out, some basic styling and polish was added:

• Centered text and standardized font styling

• Colored header section

• Properly spaced input/output fields

Formatting Text and Buttons

Standard CSS was used to style and align key text elements:

• font-family, text-align, padding properties
• Flexbox for positioning button between fields

Adding Colors and Backgrounds

Hex codes from the Figma mockups establish app color scheme:

• Blue header background
• Matching translate button color

Conclusion and Next Steps

This walkthrough video summarized the entire process of building an AI-powered app from ideation to functioning prototype.

With the core in place, future enhancements involve:

• Adding advertisements to offset API costs

• Allowing tips to boost revenue

• Deploying the web app for public access

FAQ

Q: What is GPT-3 and how can it be used to build apps?
A: GPT-3 is an AI system created by Anthropic that is trained on massive amounts of textual data. It can generate human-like text and be used through an API to power language applications like chatbots, content generators, and more.

Q: What coding skills are needed to build an app with GPT-3?
A: To build an app with GPT-3, you'll need skills in a web development framework like React Native, skills to connect an API, and ability to craft effective prompts to get desired outputs from GPT-3.

Q: What steps are involved in designing the app interface?
A: Key steps include wireframing the layout, planning core UI elements like text fields and buttons, choosing design elements like colors and fonts, and implementing in a UI framework like React.

Q: How do you connect React code to the GPT-3 API?
A: Install the OpenAI package, get API keys, import OpenAI in React, and call its text completion endpoint by passing the prompt, model, and other parameters.

Q: Why is crafting the right prompt for GPT-3 important?
A: The prompt encodes the instructions given to GPT-3, so it needs to be carefully designed to get the desired output. Testing in the Playground is key.

Q: What final touches help polish the app?
A: Styling choices like colors, backgrounds, spacing, and text formatting help refine the look and feel. Fixing bugs, adding edge case handling, etc finalize it.

Q: What are the next steps after completing the basic app?
A: Next steps may include adding monetization features, deploying the app for users to access, continuing to refine the UI/UX, and improving the backend.

Q: Where can I learn more about building AI apps?
A: There are many online courses, documentation resources, communities and tutorials focused on building AI apps, particularly using tools like GPT-3 and React Native.

Q: Does this app tutorial require expert coding skills?
A: No, this tutorial aims to show an end-to-end build process accessible even for those newer to coding. However, some development experience is assumed.

Q: What other AI models could be used for natural language apps?
A: Beyond GPT-3, models like Jurassic-1 J, Anthropic's Claude, Google's LaMDA, and Facebook's BlenderBot can power conversational and generative language apps.