We'll take a look at advanced prompt engineering, explore the different types of OpenAI models, and then create our own application by using Node.js and JavaScript.
Before we dive in, a quick shoutout to Live Learning for providing mentoring on building design businesses and furthering your career. Be sure to join their monthly NoCode Design Challenges, offering valuable prizes and expanding your network within their community.
Beyond the basics, advanced prompt engineering is all about making ChatGPT work for your specific needs, instead of settling for the more mundane examples where people just chat with it. Mastering this skill means getting the outputs you want and making the most of this incredible AI tool.
1. Advanced Prompt Engineering: In this section, we'll learn advanced techniques to make ChatGPT give us the results we want.
2. Exploring the OpenAI Playground: This part goes deeper into the different types of models that OpenAI provides, discussing their differences and why it's essential to understand them.
3. Building an Application: We'll create an API using Node.js and JavaScript, allowing us to query the OpenAI API and generate the desired prompts and outputs.
Note: If you're interested in building a project or creating an idea to sell as a SaaS, check out the template we've created for projects using OpenAI. It's a ready-to-go React and Node.js app, complete with authentication, token usage calculations, and more to save you time and effort.
When working with OpenAI, it’s crucial to understand the difference between available models. Each one has its unique characteristics, strengths, and weaknesses. Recognizing these distinctions will empower you to use the correct model for your application and get the best results possible.
Now that we've covered advanced prompt engineering and explored OpenAI models, it's time to create our own application. We'll use Node.js and JavaScript to build an API, allowing us to interact with the OpenAI API layer, generate our prompts, and extract the outputs we want.
Setting up the Application
To set up your application, you need to have Node.js installed on your system. Here's how you can proceed:
1. Create a new folder for your project
2. Run `npm init` to set up your package.json file
3. Install the necessary packages, such as Express, Axios, or OpenAI
Once you've got everything set up, it's time to start writing the code.
Creating the API Endpoint
To create the API endpoint, you can follow these steps:
1. Create a new file named 'app.js' in your project folder
2. Import the required packages (Express, OpenAI) and set up the Express app
3. Create a new route for your API, such as '/generate-response'
4. In the route, define your function to interact with the OpenAI API
5. Parse the received data and extract the desired outputs
6. Send the outputs as a response from your API
Interacting with the OpenAI API
Here's a simple example in JavaScript to interact with the OpenAI API:
```javascript
const { OpenAIClient } = require('openai')
const openai = new OpenAIClient('')
async function generateResponse(prompt) {
const response = await openai.Completion.create({
engine: 'text-davinci-002',
prompt: prompt,
max_tokens: 100,
n: 1,
stop: null,
temperature: 1.0,})
return response.choices[0].text
This code demonstrates how to interact with the OpenAI API and generate a response based on a given prompt. Remember to replace `` with your actual API key from OpenAI.
With all of these steps in place, you now have an API that interacts with the ChatGPT models, receives user input, and generates outputs based on the input received. With advanced prompt engineering techniques and a better understanding of the OpenAI models, you'll be able to develop a more powerful and effective application.
Keep experimenting and learning with AI, and don't forget to join the Live Learning community, where you get mentoring for building design businesses and can participate in Monthly NoCode Design Challenges to win awesome prizes. Happy building!
