Build your own code completion tool with openai using Nodejs

Are you tired of manually completing code while programming? Do you wish you had a tool that could suggest code snippets and solutions for your programming problems? Look no further! In this article, we will guide you through the process of building your own code completion tool using OpenAI and Node.js. By the end of this article, you'll have a powerful tool at your disposal that can assist you in writing code more efficiently.

Table of Contents

1. Introduction
2. Understanding Code Completion
3. Setting Up the Project
4. Configuring OpenAI API
5. Creating an Express Router
6. Handling API Requests
7. Generating Code Completions
8. Error Handling
9. Conclusion
10. FAQs

1. Introduction

Code completion is a feature commonly found in integrated development environments (IDEs) that suggests code snippets and completions as you type. It saves time and reduces errors by providing intelligent suggestions based on the context of your code. In this article, we'll leverage OpenAI's powerful language model to create our own code completion tool.

2. Understanding Code Completion

Code completion works by analyzing the code you've already written and providing suggestions based on patterns and common usage. It takes into account the programming language, the context of the code, and the desired outcome. With OpenAI, we can tap into its vast knowledge and generate code completions that align with our requirements.

3. Setting Up the Project

To begin, let's set up our Node.js project. Make sure you have Node.js and npm (Node Package Manager) installed on your system. Create a new directory for your project and initialize it with the following command:

mkdir code-completion-tool
cd code-completion-tool
npm init -y

This will create a new project with a package.json file.

4. Configuring OpenAI API

To access the OpenAI API (Click here) , we need to obtain an API key. Visit the OpenAI website and sign up for an account if you haven't already. Once you have an API key, create a .env file in the project root directory and add the following line:

OPENAI_API_KEY=your_api_key_here

Remember to replace your_api_key_here with your actual API key.

5. Creating an Express Router

We'll be using the Express framework to handle HTTP requests and create an API endpoint for our code completion tool. Install Express by running the following command:

npm install express

Next, create a new file called index.js and add the following code:

const router = require("express").Router();
const { Configuration, OpenAIApi } = require("openai");

require("dotenv").config();

const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
});

const openai = new OpenAIApi(configuration);

// API routes and code here

module.exports = router;

This sets up the basic structure of our Express router and initializes the OpenAI API client.

6. Handling API Requests

In our Express router, we'll create a route to handle code completion requests. Add the following code after the initialization of the openai object:

router.post("/api/textGeneration", async (req, res) => {
  if (!configuration.apiKey) {
    res.status(500).json({
      error:

 {
        message:
          "OpenAI API key not configured, please follow instructions in README.md",
      },
    });
    return;
  }

  const { query, programmingLanguage, info } = req.body;
  if (!query || query.trim().length === 0) {
    res.status(400).json({
      error: {
        message: "Please enter a valid input",
      },
    });
    return;
  }

  try {
    const completion = await openai.createCompletion({
      model: "text-davinci-003",
      prompt: generatePrompt(query, programmingLanguage, info),
      temperature: 0.6,
      max_tokens: 1000,
    });
    res.status(200).json({ result: completion.data.choices[0].text });
  } catch (error) {
    if (error.response) {
      console.error(error.response.status, error.response.data);
      res.status(error.response.status).json(error.response.data);
    } else {
      console.error(`Error with OpenAI API request: ${error.message}`);
      res.status(500).json({
        error: {
          message: "An error occurred during your request.",
        },
      });
    }
  }
});

This route listens for HTTP POST requests to the /api/textGeneration endpoint. It checks if the OpenAI API key is configured and validates the input data. Then, it calls the OpenAI API to generate the code completion and sends the result as a JSON response.

7. Generating Code Completions

To generate code completions, we need to define a prompt that includes the programming language and the problem or query. Add the following function after the API route:

function generatePrompt(query, programmingLanguage, info) {
  const question = `Write a ${programmingLanguage} solution for this problem \n`;
  let actualQuery = question + query;
  if (info) {
    actualQuery += `\n ${info}`;
  }
  return actualQuery;
}

The generatePrompt function takes the query, programming language, and additional information as parameters and constructs the prompt by appending them together.

8. Error Handling

Error handling is an important aspect of any API. We've already included basic error handling in our code. You can customize it further based on your specific requirements.

9. Conclusion

In this article, we have learned how to build our own code completion tool using OpenAI and Node.js. We started by setting up the project, configuring the OpenAI API, and creating an Express router to handle API requests. Then, we implemented the code completion functionality by calling the OpenAI API and generating completions based on the provided query. Finally, we added basic error handling to ensure a smooth user experience.

Now you have the power to enhance your coding productivity by utilizing your own code completion tool. Happy coding!

FAQs

1. Can I use any programming language with this code completion tool? Yes, you can use any programming language supported by the OpenAI API.

2. Is the code completion tool capable of handling complex problems? Yes, the tool can handle a wide range of programming problems, including complex ones.

3. How can I improve the accuracy of the code completions? You can experiment with different values for the temperature parameter to control the randomness of the generated completions.

4. Are there any limitations to the number of tokens in the generated completions? Yes, the OpenAI API has a maximum token limit for each API call. You can adjust the max_tokens parameter to control the length of the completions.

5. Can I deploy this code completion tool in a production environment? Yes, you

   can deploy the code completion tool to a server or a cloud platform to make it accessible to other developers.