Tabnine Labs: Building a chrome extension with AI

Introduction

Introduction

In this article, I share my experience building a Chrome extension using Tabnine AI. The process involves setting up a password generator that combines various modern web technologies, including TypeScript, React, and Tailwind CSS, while leveraging the capabilities of AI to streamline the coding process.

Getting Started

The journey began by creating a new directory for the Chrome extension and setting up the necessary files. With Tabnine’s assistance, I generated a manifest file, which is crucial for defining the extension's properties.

Setting Up the Project

I opted to use Vite as the build tool for this project. The following steps were crucial for setting up the project:

1. Create a New Directory: I named it to reflect the password generator Chrome extension.
2. Initialize the Project: By using npm to create the project.
3. Install Dependencies: I included necessary libraries like TypeScript, React, and Tailwind CSS for styling.

Creating the Extension

Using Tabnine, I created the basic structure of the extension. This included:

• Setting up a manifest file describing the extension.
• Creating HTML and JavaScript files for the user interface.
• Building a background script to enable persistent functionality for the extension.

Developing the Password Generator

With the initial framework in place, I focused on developing the core functionality of the password generator. This involved:

• Password Generation: Implementing a function that generates a strong password with random characters.
• User Interaction: I added input fields to allow users to copy the generated password and set custom lengths and criteria (e.g., including special characters).
• Password Strength Indicator: An important feature to show users how strong their generated password is.

Refactoring the Code

As the project developed, I refactored the code to improve maintainability. I extracted functions into separate components and made use of utility files for better organization.

Enhancing User Experience

In pursuit of a better design, I integrated Tailwind CSS to style the component neatly. This resulted in a more appealing user interface that was also responsive.

Testing the Extension

Before completion, I set up testing using Vite’s testing capabilities to ensure the password generator functions as expected. Though challenges arose in setting up these tests, I relied on AI to help generate test cases based on the components created.

Conclusion

The experience of building this Chrome extension was both rewarding and educational. By utilizing Tabnine’s AI alongside modern web development practices, I managed to create a functional password generator while streamlining the coding process. I look forward to continuing this journey in future projects, exploring new features and technologies.

Keywords

Chrome extension, password generator, Tabnine, AI, TypeScript, React, Tailwind CSS, Vite, testing.

FAQ

What technologies were used to build the Chrome extension?

The Chrome extension was built using TypeScript for efficient coding, React for creating components, Tailwind CSS for styling, and Vite for the development server and build process.

What does the password generator do?

The password generator creates strong random passwords based on specified user criteria, such as length and inclusion of special characters. It also indicates the strength of the generated passwords.

How can I test the Chrome extension?

Testing was performed using Vite’s testing capabilities, allowing for the creation of various test cases to ensure that the password generator behaves as expected.

What role did Tabnine play in the development process?

Tabnine served as an AI coding assistant, helping to generate code snippets, assist with functions, and streamline the overall development process based on natural language prompts.

Will there be more articles like this?

Yes, there will be more articles and live coding sessions exploring similar projects and technologies, offering insights into the development process with the help of AI tools like Tabnine.