3 alternatives to GitHub Copilot to keep an eye out for

Microsoft started to work with OpenAI and launched the GitHub Copilot, an AI programmer. This project drew on OpenAI Codex, and it is an AI programmer trained in open-source code. Github Copilot uses the OpenAI Codex to suggest you code while working with your favorite IDE tools. As we all know, it works well with JavaScript, Typescript, Python, Ruby, and Go. When the GitHub Copilot was launched, it kicked out a storm in social media. The initial response has been overwhelmingly positive, with many calling the coding assistant a big game changer. Later, people started to get afraid to use Github due to various factors like Copyright issues.

We know that Github Copilot is a tool built into an editor, i.e., it lets you write code based on the code you have already written for your projects. GitHub Copilot was launched by GitHub (AKA Microsoft) on 29 June 2021. This tool is powered by OpenAI GPT-3, a language prediction tool that generates human-like text. This article will explore the three top alternatives you can work with.

So, let’s get started!

Limitations of Github Copilot

GitHub Copilot is far too good for a beta product. But there are so many biased articles online, and I just wanted to show the other side.

• It Doesn’t Follow Best Practices The generated code does not always adhere to best practices or is not optimized for backend development. It generates var and == rather than const and ===, as in Javascript, which can lead to various bugs and shadowing. Sometimes GitHub Copilot generates autosuggestion codes from the public repository, which doesn’t follow proper structure code.

• Versions Issues Some Code Generated may not work for the version of your codebase you are using, resulting in conflicts. Also, AI can generate a lot of unnecessary code at times. Developers with experience can undoubtedly handle this, but if a newbie begins with the assistance of AI, he will spend more time on stack overflow than writing actual code.

• Copyright Infringement According to the GitHub Terms of Service, regardless of the license you use, you grant GitHub the right to host your code and use it to improve their products and features,” Downing says. “With regard to existing code on GitHub, I believe the answer to the question of copyright infringement is fairly straightforward.”

• No free Subscription There’s a free Subscription you can use, but it has certain limitations on OSS maintainers and Students. After getting the trial expired you need to buy the subscription to take those advantages while working.

• AI couldn’t run locally Do you prefer to code offline, or must you keep your code local for legal reasons? If this is the case, Copilot is not for you. AI models cannot be run locally. Copilot used Codex, an AI model trained on billions of lines of public code, to recommend additional lines of code and functions based on the context of existing code.

• No proper code completion Copilot requires a certain context to produce the source code. The more context you provide, the more results you will get. Therefore, Copilot will provide those source codes through context and cursor location.

Top 3 Alternatives for the Github Copilot

Here are the top three alternatives I would recommend.

1 Tabnine

Tabnine (once known as Codota) was one of the first code completion tools to hit the market. In your favorite IDEs, the Tabnine code completion plugin supports all of the most popular languages, libraries, and frameworks. Tabnine AI models are only trained on permissive open-source licensed code, ensuring your code remains yours.

The heart of Tabnine is the machine learning algorithm that works in real-time to provide suggestions while working with your favorite IDE tools.

The Tabnine Pro subscription allows you to train your own private AI model based on your code and receive personalized code completions that match your style and patterns. You won’t have to rely on code written by anyone other than yourself in your repositories.

Tabnine works with popular programming languages like Typescript, Python, Rust, and Go. In Tabnine, every model is optimized to work with specific languages, enabling auto-completion accuracy.

When it comes to privacy and compliance then, Tabnine always keeps your code private. It also integrates the IDE tools like VSCode, IntelliJ, Pycharm, Sublime, Rider, WebStorm, and AppCode.

As per Tabnine features, it predicts and suggests your next line of code based on your context and syntax.

• Whole line code completions
• Full function code completions
• Natural Language to code

You can run Tab Nine locally or through the cloud. It’s up to you.

Today Tabnine has successfully automated 30% of the code created by more than 1,000,000 developers. Over 500k active monthly users are using Tabnine.

Tabnine users who buy the Pro Plan can access the new, advanced code completion features for 14 days.

Features include:

• Natural language to code completions
• Context-sensitive
• Ability to work in local mode

2 Captain Stack

Human resource managers and Stackoverflow are analogous to developers and Stackoverflow. We require platforms and tools. Captain Stack is an open-source VSCode plugin that combines the two. Inspired by Copilot, it is a code suggestion tool that uses Google instead of AI. It submits your search query to Google, retrieves answers from StackOverflow and Github Gist, and auto-completes them.

If you want to use the CaptainStack, check out these CaptainStack details on Visual Studio Marketplace, where you will get the details of how to install and also how to use.

CaptainStack is created by Hieu Nguyen, and this product is free to use.

Limits:

• Extensions use fetch-node to get the page content.
• It also uses querySelector to extract code and other information.

Captain Stack allows enabling or disabling a source site. By default, only Stackoverflow is enabled.

You can also check the GitHub repository of CaptainStack. Where it has more than 12k likes for the extension.

3 GPT-Code-Clippy (GPT-CC)

GPT-Code-Clippy is a group effort to develop GPT-Codex, an open-source variant of GitHub Copilot, an AI pair programmer built on GPT-3. Our GPT Code Clippy dataset, which we obtained from publicly accessible code on GitHub, is used to fine-tune GPT-CC. It was developed to make it simple for researchers to examine substantial deep-learning models trained on code to comprehend their strengths and weaknesses. The underlying language model for GPT-CC is the GPT-Neo model, which has been pretrained on the Pile dataset. The model is trained using the Causal Language Modeling aim.

They have added the feature to take a screenshot of the code generated via Carbon which can be shared through social media.

It uses the Hugging Faces Transformers library and their Flax API to fine-tune our model on various code datasets, including one of our own, which can be scrapped from Github.

You can visit the model’s page to see the trained models and the results of fine-tuning.

Conclusion

Machines will not take over your job. They’re after the tedious parts that make your wrists ache. Artificial intelligence code prediction and completion tools and services are here to stay. It’s simply a matter of selecting the best platform for your needs, allowing you to code faster and better.

A TIP FROM THE EDITOR: For a different take on Github Copilot, look at our Is GitHub Copilot A Threat To Developers? article.

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