Omnipilot

29 Best Copilot Alternatives to Accelerate Your Coding Workflow

Are you constantly navigating complex work environments or struggling to juggle multiple tasks simultaneously? AI Copilots may be just what you need to streamline your workflow and boost your productivity. Picture this: With the help of an AI Copilot, you can use AI anywhere on MacOS as an AI copilot assistant. If this sounds appealing, keep reading. In this blog, we'll discuss leveraging Copilot alternatives, such as Omnipilot's AI copilot, to enhance your MacOS experience and optimize your tasks efficiently.


Looking for an efficient way to Use AI anywhere on MacOS as an AI copilot assistant? With Omnipilot's AI copilot, you can revolutionize your workflow and achieve your objectives seamlessly. Enhance your MacOS experience with this innovative tool and refine your productivity in no time.

What Is Github Copilot & Its Key Capabilities

GitHub Copilot is an AI-powered coding assistant that helps developers write code faster and with less effort, allowing them to focus more energy on problem-solving and collaboration. Copilot offers coding suggestions as you type: sometimes the completion of the current line, sometimes a whole new block of code. 


You can accept all, or part, of a suggestion, or you can ignore the suggestion and keep typing. Using the chat feature, you can ask Copilot how best to solve a problem or explain someone else's code. If your code has a bug, you can ask Copilot how to fix it. Copilot has been proven to increase developer productivity and accelerate the pace of software development.


How GitHub Copilot Can Help Developers

GitHub Copilot assists developers in several ways, such as suggesting code completions, generating entire functions, and providing real-time assistance while coding. Copilot offers coding suggestions as you type, making it easier to complete lines of code or generate new blocks of code. 


The suggestions can be accepted in whole or part, or ignored if unnecessary. This feature can significantly enhance a developer's coding speed and efficiency. Developers can ask Copilot for help solving problems, explanations of code, or guidance on fixing bugs. These real-time assistance capabilities can streamline the coding process and help developers overcome obstacles quickly.


GitHub Copilot's Programming Language Support and IDE Integration

GitHub Copilot supports various programming languages, making it a versatile tool for different coding projects. Some supported languages include JavaScript, Python, Ruby, Go, TypeScript, and many others. This programming language diversity allows developers to leverage Copilot's features across various development tasks and projects. 


Copilot can be integrated with popular Integrated Development Environments (IDEs) and code editors, providing seamless coding assistance within the developer's preferred environment. This integration enhances the developer experience by allowing them to access Copilot's features without leaving their familiar coding setup.


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6 Reasons to Consider Github Copilot Alternatives

1. No free subscription

Free licenses are still available, but they’re now limited to OSS maintainers and students only


2. No midline code completion

As noted previously, Copilot requires much context to produce any code. The more context you provide, the more accurate the results will be. Copilot will only offer you the following line, function, or whole block of code based on context and cursor location.


3. AI models can’t run locally

Do you like to code offline or need to keep your code local for compliance? Then Copilot is not for you. The AI models cannot run locally.


4. Limitations in open-source functionality and support

GitHub Copilot is not open-source, meaning it doesn’t give you access to its code. While you can train the tool using a custom code base, it can’t beat the flexibility of open-source technology.


5. Compatibility

GitHub Copilot is not a one-size-fits-all product—you may need an alternative that fits your unique workflows and programming languages.


6. Data Privacy

Github Copilot can collect user information, including the suggestions you accept or dismiss. Sometimes, this information can include personal data and identifiers.


Revolutionizing macOS Productivity with Omnipilot's AI Copilot

Imagine an AI that can type anywhere on macOS, with full context of what's on your screen. Imagine if, your email wrote itself, your terminal was fluent in Bash, your team updates became effortless. You don’t have to imagine any of this anymore. You can download Omnipilot’s MacOS AI Copilot for free right now and use AI anywhere on MacOS! 


Try our free AI copilot today — just head to omnipilot.ai and enter your email, and you’ll be able to download our MacOS app in seconds! Let Omnipilot make your life easier.


29 Notable GitHub Copilot Alternatives 

1. Omnipilot

Imagine an AI that can type anywhere on macOS, with full context of what's on your screen. Imagine if, your email wrote itself, your terminal was fluent in Bash, your team updates became effortless. You don’t have to imagine any of this anymore. You can download Omnipilot’s MacOS AI Copilot for free and use AI anywhere on MacOS! 


Try our free AI copilot today — just head to omnipilot.ai and enter your email, and you can download our MacOS app in seconds! Let Omnipilot make your life easier.


2. Tabnine

Tabnine is an AI-powered code completion tool that enhances the efficiency of software development. It integrates with various Integrated Development Environments (IDEs) such as Visual Studio Code, IntelliJ IDEA, and more. Tabnine’s primary feature is its code completion capabilities, powered by machine learning algorithms. It analyzes the code you’re working on and provides relevant, context-aware suggestions, including predictions for the next line or chunk of code. 


3. Replit Ghostwriter

Replit Ghostwriter is a feature within the Replit online development environment that enhances the coding process through AI-powered code suggestions. Ghostwriter leverages LLMs to provide real-time, context-aware code completions, and bug fixes. One of its notable features is the ability to write code in response to natural language comments, making it more accessible to beginners or those learning a new programming language. Ghostwriter supports various programming languages and frameworks and is integrated within Replit’s online IDE, making it a useful tool for quick prototyping, educational purposes, and collaborative coding projects.


4. Amazon CodeWhisperer

Amazon CodeWhisperer, developed by AWS, is an AI-driven coding assistant designed to help developers write more efficiently. It too is based on LLMs and was trained based on Amazon’s proprietary code and open source libraries. CodeWhisperer provides code recommendations based on the context of the code and the comments written by the developer. It supports multiple programming languages and is integrated with popular IDEs like AWS Cloud9, IntelliJ IDEA, and Visual Studio Code. 


5. Visual Studio IntelliCode

Visual Studio IntelliCode is an extension for Visual Studio and Visual Studio Code that provides AI-assisted code completions and recommendations. IntelliCode is based on the previous generation of machine learning techniques, so it provides a more basic level of code completion compared to other tools. One of its key features is the ability to learn patterns from the codebase it’s working on, providing tailored recommendations that adapt to the coding practices of the development team. 


6. SourceGraph Cody

SourceGraph Cody is a development tool that enhances code search and intelligence within your codebase. It uses two LLMs: OpenAI’s GPT and Anthropic Claud. It’s designed to help developers navigate large codebases more effectively and gain insights into how their code connects and functions. Cody provides a powerful search engine for code, enabling developers to quickly find specific functions, definitions, and references across their entire codebase. 


7. Codeium

Codeium is another LLM-driven coding assistant designed to enhance productivity and code quality for developers. It provides smart code completions and refactorings. Codeium supports a variety of programming languages and integrates with popular IDEs. Codeium also helps maintain code quality by suggesting refactorings and improvements, ensuring the code is functional, clean, and efficient. This tool is suitable for experienced developers looking to speed up their workflow and beginners who can learn from the AI-generated code patterns.


8. Tabby

Tabby is an open-source self-hosted AI coding assistant recognized for providing a low-barrier code-completion solution. This platform suggests multi-line code snippets or entire functions as you type.  


9. Captain Stack

Captain Stack, a VSCode extension that mimics Copilot’s code suggestion feature, is one of the best open-source alternatives to GitHub Copilot. This tool sends your search query to Google, retrieves GitHub Gist and Stack OverFlow answers, and autocompletes them. 


10. Blackbox AI

Blackbox AI is well-known for solving coding problems and empowering developers to innovate and create with newfound confidence. This tool is packaged with code autocompletion, repo search, and code search. 


11. CodeGeeX

CodeGeeX is a robust AI assistant designed to help developers by taking their coding experience to the next level. It packages a large-scale multilingual code generation model and is trained on a vast corpus encompassing 20+ languages. 


12. AskCodi

Do you want to get precise and instant answers to your coding questions? Look no further than AskCodi. This tool is ideal for beginners and intermediate programmers and connects you with seasoned coders who can provide outstanding solutions to your problems in real-time. 


13. JetBrains AI

JetBrains AI develops IDEs like Android Studio and IntelliJ IDEA that let users create applications. Integration of AI tools in these IDEs enhances functionality, so users can access coding assistance features directly in their development environment without additional installations. JetBrains’ AI features are tightly integrated into its IDEs, so users can access them directly out of the box. While GitHub Copilot and JetBrains AI support contextual awareness, JetBrains’ abilities are more refined due to their tight integration in IDEs.


14. GPT-Code-Clippy (GPT-CC)

Another open-source alternative to Copilot is GPT-Code-Clippy. According to the description, GPT-Code-Clippy (GPT-CC) is an open-source version of GitHub Copilot, a language model (based on GPT-3, called GPT-Codex) that is fine-tuned on publicly available code from GitHub. Similar to Captain Stack, GPT-CC is only available as a plugin for VS Code.


15. Second Mate

Second Mate is another open-source imitation of GitHub Copilot. It uses EleutherAI GPT-Neo-2.7B (via Huggingface Model Hub) for Emacs. It’s a much smaller model, so it will likely be less effective than Copilot or other alternatives. On the other hand, you can run it on Emacs, and it’s free


16. K.Explorer

K.Explorer is an AI system that creates better software faster, cheaper, and more efficiently. A coding assistant that increases developer productivity. An AI pair programmer that suggests code completions and complete function bodies as you type. You can also search the engine for help. It is an AI-powered Code Assistant that has been trained on millions of lines of code from private corporations and billions of lines of open-source code for general purposes. Natural Language allows programmers to receive guidance and tell a text story about their code.


17. Code Llama

Code Llama, a large-language model (LLM), can generate code using text prompts. Code Llama, the most advanced publicly available LLM for code tasks, can potentially improve developers' workflows and reduce the barrier for those learning to code. Code Llama can improve productivity and educate programmers to create more robust, well-documented software. 


Code Llama, a state-of-the-art LLM, can generate both code and natural language about code based on both code and natural-language prompts. It can be used for free in research and commercial purposes. Code Llama is a new model built on Llama 2. It is available in three models: Code Llama is the foundational model of code; Codel Llama is a Python-specific language. Code Llama-Instruct is a finely tuned natural language instruction interpreter.


18. Code T5

Code for CodeT5, A new pre-trained encoder/decoder model that is code-aware. Identifier-aware pre-trained encoder/decoder models. This is the official PyTorch version of the EMNLP paper 2021 from Salesforce Research. CodeT5-large ntp-py was optimized for Python code generation and used as the foundation model in our CodeRL. This yielded new SOTA results for the APPS Python Competition-Level Program Synthesis benchmark. This repository contains the code to reproduce the experiments in CodeT5. 


CodeT5 is an encoder-decoder pre-trained model for programming language, which has been pre-trained with 8.35M functions from 8 programming languages: Python, Java, JavaScript PHP, Ruby Go, C#, C, and C#. It achieves the best results in a benchmark for code intelligence - CodeXGLUE. Generate code from the natural language description.


19. CodePal

CodePal will be your ultimate coding partner. It is a comprehensive platform with various tools and coding helpers to assist developers. It's great for students, newbies, experienced developers, or companies that want to improve their development process. The free plan gives you access to all tools and helpers but has some limitations. This is a great option for those who want to test out CodePal. 


AI Code Generators can perform various tasks, including programming, applying transformations, and manipulating the code. They can be very helpful for learning as they give a good understanding of how to write the task in code. Code generation is possible with many languages, such as Java, C, Python, and TypeScript. The choice of programming languages will often depend on specific project needs and available code-generation tools and frameworks.


20. Codey

Codey accelerates the software development process with real-time code generation and completion, customized to a client's codebase. This code generation model is compatible with 20+ coding languages, including Go, Google Standard SQL (GSS), Java, Javascript and Python. It allows developers to perform a wide range of coding tasks. 


This helps them work faster and close skill gaps by: 

  • Code completion: Codey suggests a few lines of code based on context. 
  • Code generation: Codey creates code using natural language prompts provided by a developer. 
  • Code chat: Codey allows developers to converse with a robot for help with debugging and documentation, learning new concepts and other code-related issues.

21. AlphaCode

Human intelligence can solve unexpected problems by applying critical thinking and experience. Although machine learning has made great strides in understanding and generating textual data, the machine learning community still faces challenges in problem-solving. These include simple maths and programming problems or retrieving and copying existing solutions. DeepMind's mission is to solve intelligence. We created AlphaCode, a computer program that can write computer programs at a competitive level. 


AlphaCode ranked among the top 54% of programmers in programming competitions. It solved new problems that required a combination logic, logic, algorithms and natural language understanding. AlphaCode uses transformer-based language modeling to generate code on an unprecedented scale. Then, it intelligently filters to a select few promising programs.


22. AiXCoder

Artificial Intelligence can be left to AIXcoder. Real Intelligence belongs to humans. The offline version has been released! Your code is protected on your local computer. AiXcoder works smoothly locally using state-of-the-art deep learning model compression techniques. The models are trained using a large amount of open-source code. They can be adapted to many areas. A search window seamlessly integrates into IDE and allows you to search open-source code at GitHub. 


Deep learning filters high-quality code in search results. Look for API usage and examples. Search for similar code to avoid duplicate code. 

  • Project Level Personalized Training: Train models on your personal project and computer. 
  • Enterprise-Level Customized Training: Train models on a code base or enterprise server. A standard model provides training. 


Personalized and customized training can be provided to help you learn the patterns and rules of your code.


23. Jedi

Jedi is a Python static analysis tool that can be used in IDEs and editor plugins. It focuses on auto-completion and goto functionality and has many other features, including code search, refactoring, and finding references. Jedi offers a simple API for use. A reference implementation is available as a VIM Plugin. It is possible to autocompletion your REPL. IPython uses it natively. You can also install it for the CPython REPL. Jedi is well-tested and should have a few bugs. 


A script is the foundation for Jedi completions, goto, or whatever else you need. The interpreter is the other part of this class. It works with an actual dictionary and can also work with a REPL. This class should be used when editing code in an editor. Most methods have both a line parameter and a column parameter. Jedi lines are always 1-based, while columns are always zero-based. They are not always documented to avoid repetition.


24. IBM Watsonx Code Assistant

AI-generated code recommendations allow hybrid cloud developers to write code at any experience level. Imagine translating plain text into code. IBM Watsonx code assistant will enable you to do that. IBM watsonx.ai Foundation Models (FM) power IBM watsonx.ai Code Assistant, making writing code easier through AI-generated suggestions. 


This brings the power of IT automation into your organization, making it a strategic and accessible asset for all users, not just subject matter experts. This means that code is automatically suggested to developers based on inputs in natural language. IBM Watsonx code assistant is infused Watsonx.aiFMs that were purpose-built and created with deployment efficiency and organization standards and best practices in mind.


25. Mutable.ai

AI allows you to build fast and produce high-quality code. Create high-quality code quickly. AI Autocomplete will enable you to prototype quickly. AI Autocomplete transforms your prototype into a production-quality code. Specialized neural networks reduce the time spent on boilerplate and on StackOverflow. Refactor, document, and add types. To modify code, give instructions directly to the AI. Automate the generation of unit tests using AI and metaprogramming. 


AI is the future of software development. The long-term goal is to allow programmers to think at the speed of thought. And believe that AI advances will open up new programming methods beyond the pre-AI-accelerated stack. These new programming methods won't look like an IDE or version control system.


26. Kodezi

Let Kodezi auto-summarize your code in seconds. Kodezi is Grammarly designed for programmers. KodeziChat allows you to ask, search, code, and generate anything in your codebase. Your AI coding assistant! Kodezi does more than fix your code. It also tells you why and how to prevent future problems. To ensure clean code and syntax, reduce unnecessary lines. Optimize your code to maximize efficiency. With detailed explanations, debug code. You can switch from one framework to another in seconds, without losing context. 


Commenting and explaining code is crucial for future maintenance. In seconds, you can generate code from text, answer a question about coding, or create a whole function. Generate your code documentation. Translate code into another language. Optimize your code to maximize efficiency. You can use our extension in your own IDE and never need to open new tabs again.


27. ExoCoding

ExoCoding, an online platform for code generation, empowers software developers by enabling them to create better software faster. It uses AI-powered assistants based on models to generate boilerplate codes and streamline repetitive tasks. Developers can create applications that contain modules for:

  • Database Management
  • Logic Building
  • Interface Design


More features, such as sharing prototypes, task planning, and a marketplace that offers pre-built templates, enhance the developer experience. After generating the code (backend or frontend), it's business as usual. The same IDE and other dev tools are used.


28. Cosine

Cosine can understand and provide answers at a superhuman level, whether they are high-level or complex. We are not just an LLM-wrapper. We combine multiple heuristics, including static analysis and semantic search. Ask Cosine to generate a step-by-step guide on how to add new features or modify existing code. Cosine indexes your codebase and understands it on multiple levels. 


Cosine can answer any questions you may have about your codebase, from a graph relationship between functions and files to a deep understanding of the code. While Copilot excels at inline code generation, it only uses a few files (usually the most recently opened) to answer questions. This is a great way to quickly auto-complete, but it struggles to give higher-level answers about how your codebase works. Cosine is able to read every code snippet within your codebase and provides a superhuman level of contextual understanding.


29. StableCode

StableCode is a unique tool that helps developers become more efficient in their coding by using three models. The base model was trained first on a diverse collection of programming languages using the stack dataset from BigCode, and then further trained with popular languages such as Python, Go, Java, Javascript, C, markdown and C++. We trained our models using 560B tokens on our HPC Cluster. 


After establishing the base model, the instruction models were tuned for specific use cases to help solve complex programming problems. To achieve this result, 120,000 code instructions/response pairs in Alpaca format were trained on the base. StableCode is a great tool for anyone who wants to learn more about programming. The long-context model is a great assistant for ensuring that the user can make autocomplete suggestions for single- and multiple-line input. This model was designed to handle a large amount of code at once.


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How to Choose the Best Copilot Alternative

1. AI-powered code completion and suggestions

One of the key factors to consider when looking for a GitHub Copilot alternative is the presence of AI-powered code completion and suggestions. Having this ability directly in your integrated development environment (IDE) can significantly enhance your coding experience by providing helpful suggestions and code completions while you work.


2. Support for multiple programming languages

A GitHub Copilot alternative that supports a wide range of programming languages can benefit software developers working with different languages in their projects. Ensure that the alternative you choose has built-in support for the programming languages you commonly use, such as Python, Java, JavaScript, TypeScript, etc.


3. Compatibility with popular IDEs

Consider the compatibility of the GitHub Copilot alternative with popular integrated development environments (IDEs) like Visual Studio Code, JetBrains, and Vim. The ability to seamlessly integrate the alternative into your preferred IDE can significantly impact your workflow and productivity.


4. Real-time capabilities

Real-time feedback and help can be invaluable during software development. Look for GitHub Copilot alternatives that offer real-time code suggestions, autocompletion, and code generation capabilities to streamline your development process.


5. API access

Depending on your needs, you may opt for a GitHub Copilot alternative that provides API services for extended functionality. This feature can offer additional flexibility and customization options tailored to your specific requirements.


6. Hybrid processing capabilities

The availability of both cloud-based and local processing options can cater to different security and performance needs. Choose a GitHub Copilot alternative that can seamlessly switch between cloud and local processing, ensuring the tool continues functioning even without an internet connection for increased accessibility.


7. Evaluation criteria for choosing the ideal alternative

As you assess different GitHub Copilot alternatives, consider the following criteria:

  • Stack requirements and programming language support
  • Impact on workflow efficiency and development process
  • Pricing structure and availability of free plans
  • Community support and access to assistance and updates
  • Repository and plug-in support
  • User-friendliness and suitability for developers of all skill levels

By examining these factors, you can select the best GitHub Copilot alternative that aligns with your privacy and security requirements, customization, flexibility needs and integrates seamlessly with your existing tools and workflows.


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Try Our MacOS AI Copilot for Free Today

I recently came across a game-changing AI tool for MacOS called Omnipilot, and let me tell you, it has revolutionized how I work. This innovative AI copilot seamlessly integrates into your MacOS environment, allowing you to type anywhere on your screen with full context awareness. Imagine having an AI that can draft your emails, navigate your terminal like a pro, and make team updates a breeze. Well, with Omnipilot, you don't have to imagine anymore – it's all possible.


Omnipilot is not your average AI copilot; it goes above and beyond to make your life easier. With just a few clicks, you can download Omnipilot's MacOS AI Copilot for free and unlock a world of possibilities. Simply head to omnipilot.ai, enter your email, and you'll be able to download the MacOS app in seconds. Trust me, once you start using Omnipilot, you'll wonder how you ever lived without it. 


Try our free AI copilot today and let Omnipilot be your trusted sidekick in the world of MacOS.