In this tutorial, we will walk through the process of building a code editor using OpenAI Codex and Vue.js. OpenAI Codex is a powerful language model that can generate code based on a given prompt. Vue.js is a versatile JavaScript framework that simplifies the process of building user interfaces.
By combining these two technologies, we can create a code editor that provides real-time code suggestions and completion based on the user’s input. Let’s get started!
Prerequisites
Before we begin, make sure you have the following installed on your machine:
- Node.js and NPM (Node Package Manager)
- Vue CLI (Command Line Interface)
You can install Node.js and NPM by visiting the official website and following the installation instructions. After installing Node.js, you can install Vue CLI globally by running the following command:
npm install -g @vue/cli
With these prerequisites in place, we can start building our code editor.
Setting up the Vue.js project
First, we need to scaffold a new Vue.js project. Open your terminal or command prompt and navigate to the directory where you want to create the project. Run the following command to create a new Vue.js project:
vue create code-editor
You will be prompted to choose a preset. For simplicity, we’ll choose the default preset, which includes basic features such as Babel and ESLint. You can customize the preset based on your specific needs.
Once the project is created, navigate to the project directory:
cd code-editor
Now, let’s run the development server to ensure everything is set up correctly:
npm run serve
You should see a message indicating that the development server is running. Open your web browser and visit `http://localhost:8080` to verify that the Vue.js project is running successfully.
Creating the CodeEditor component
In Vue.js, components are reusable building blocks that make up a user interface. Let’s create a new component called CodeEditor that will serve as our code editor.
First, create a new file called CodeEditor.vue in the src/components directory. This file will contain the code for our CodeEditor component. Open the file and add the following code:
<template>
<div>
<textarea v-model="code" @input="handleInput"></textarea>
<ul v-if="suggestions.length">
<li v-for="(suggestion, index) in suggestions" :key="index">{{ suggestion }}</li>
</ul>
</div>
</template>
<script>
export default {
data() {
return {
code: '',
suggestions: [],
};
},
methods: {
async handleInput() {
// Call OpenAI Codex API to get code suggestions based on this.code
// Update this.suggestions with the response
},
},
};
</script>
<style scoped>
textarea {
width: 100%;
height: 400px;
}
</style>
In the above code, we have defined a textarea element that binds its value to the code data property using v-model. We have also defined an unordered list (ul) element that will display the code suggestions.
The handleInput method is called whenever the user types in the textarea. In this method, we will make an API call to OpenAI Codex to get code suggestions based on the user’s input. The suggestions received from the API will be stored in the suggestions data property.
Integrating with OpenAI Codex
Now that we have our component ready, let’s integrate it with OpenAI Codex to provide code suggestions in real-time.
First, make sure you have an OpenAI Codex API key. If you don’t have one, visit the OpenAI website to sign up for access. Once you have the key, create a .env file in the root directory of your project and add the following line:
VUE_APP_OPENAI_API_KEY=your-api-key
This will make the API key accessible in our Vue.js application.
Next, let’s install the axios library, which we will use to make HTTP requests to the OpenAI Codex API:
npm install axios
Once the installation is complete, open src/components/CodeEditor.vue and update the handleInput method as follows:
import axios from 'axios';
// ...
methods: {
async handleInput() {
try {
const response = await axios.post(
'https://api.openai.com/v1/engines/davinci-codex/completions',
{
prompt: this.code,
max_tokens: 100,
n: 5,
},
{
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${process.env.VUE_APP_OPENAI_API_KEY}`,
},
}
);
this.suggestions = response.data.choices.map(choice => choice.text);
} catch (error) {
console.error(error);
}
},
},
In the above code, we are making a POST request to the OpenAI Codex API endpoint with the user’s input as the prompt. We are requesting a maximum of 100 tokens for each completion and asking for 5 suggestions. The Authorization header includes the API key stored in the .env file.
When the API responds, we extract the text from each suggestion and store them in the suggestions data property.
Using the CodeEditor component
Now that we have our CodeEditor component ready, let’s use it in our main application component.
Open src/App.vue and update the template to use the CodeEditor component:
<template>
<div id="app">
<CodeEditor />
</div>
</template>
Make sure to import the CodeEditor component at the top of the file:
import CodeEditor from './components/CodeEditor.vue';
Testing the Code Editor
Finally, let’s test our code editor by running the development server:
npm run serve
Visit `http://localhost:8080` in your web browser, and you should see the code editor. As you type in the textarea, you will see code suggestions appearing below.
Congratulations! You have successfully built a code editor with real-time code suggestions using OpenAI Codex and Vue.js.
Conclusion
In this tutorial, we have explored how to build a code editor using OpenAI Codex and Vue.js. We started by setting up a new Vue.js project and creating a CodeEditor component. We then integrated with OpenAI Codex to receive real-time code suggestions based on user input.
By combining the power of OpenAI Codex and Vue.js, we can create even more advanced code editors with features like code completion, linting, and more. The possibilities are endless!
Feel free to experiment with different ideas and expand upon what we have built. Happy coding!