3 VS Code Plugins for Local Coding Assistance

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readme - 3 VS Code Plugins for Local Coding Assistance

Are you a developer looking to take your Visual Studio Code (VS Code) experience to the next level? Look no further than Local Coding Copilot plugins. These extensions can help increase productivity, streamline workflows, and provide valuable insights and tools to make coding in VS Code even better. In this article, we’ll explore some of the best Local Coding Copilot plugins available for VS Code, including their features and how they can benefit your development process. Whether you’re a seasoned veteran or just starting out with VS Code, these plugins are sure to enhance your coding experience.


readme - 3 VS Code Plugins for Local Coding Assistance

Alright, let’s dive right in! The “Continue” plugin for Visual Studio Code is a nifty tool for devs who want to use local Large Language Models (LLMs) directly in their code editor. It’s designed to fit seamlessly into VS Code, providing an easy-to-use interface that connects your coding world with AI capabilities.

The best part? “Continue” lets you interact with local LLM interfaces like Lm Studio, Ollama, and Jan, using a locally hosted API. This means your coding work continues even without an internet connection, and your code stays safely on your PC. It’s all about keeping your stuff private and secure.

“Continue” is also super flexible. It works with both GPU and CPU environments. While a GPU gives you smoother and faster interactions, the plugin functions just fine with a CPU. This makes “Continue” accessible to a wide range of users, no matter their hardware setup. Just remember, using a CPU might slow down response times, but hey, it’s a small price to pay for added privacy and control, right?

      "title": "LocalAI",
      "provider": "openai",
      "model": "model_name",
      "apiKey": "EMPTY",
      "apiBase": "http://localhost:1337"

Code GPT

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Code GPT is a versatile and powerful coding companion for Visual Studio Code, designed to elevate your programming experience to new heights. As part of the “3 Best Local Coding Copilot Plugins For VS Code,” Code GPT stands out for its rich feature set and adaptability. This extension is not just another coding tool; it’s your AI pair-programming partner that assists in coding more efficiently by offering AI chat assistance, auto-completion, code explanation, error-checking, and much more. One of its remarkable attributes is its ability to work with various AI models from different providers, thus offering a wide range of coding assistance and insights.

A standout feature of Code GPT is its compatibility with local LLM interfaces like Lm studio, ollama, and Jan, allowing it to operate using a locally hosted API within your own PC. This means you can enjoy all the benefits of AI-powered coding assistance without the need for an internet connection, ensuring your code remains private and secure since it is not sent to external servers. While utilizing your GPU is recommended for optimal performance, the plugin is also capable of running on a CPU, albeit at a slower pace. This flexibility ensures that regardless of your hardware setup, Code GPT can provide you with the intelligent coding assistance you need, making it an essential tool for developers looking to enhance their productivity and coding skills in a secure and efficient manner.


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Twinny is presented as a straightforward and efficient AI code completion plugin for Visual Studio Code, designed with local hosting capabilities to ensure privacy and freedom from internet dependencies. This tool is remarkable for its ability to integrate seamlessly with local LLM interfaces such as LM Studio, Ollama, and Jan, utilizing locally hosted APIs to deliver its services. What sets Twinny apart is its compatibility with various local APIs, including those hosted on your own PC, as well as its ability to connect with other APIs like OpenAI, offering a versatile solution for code completion.

This plugin champions privacy and local processing, negating the need to send code over the internet, thus ensuring your work remains confidential and secure. It operates optimally on GPUs, though it’s also capable of running on CPUs, albeit at a slower pace. The benefit here is twofold: there is no reliance on internet connectivity for the plugin’s functionality, and it respects the user’s desire for privacy by processing code locally. Twinny emerges as a dependable option for developers seeking a private, efficient, and versatile coding assistant, making it a valuable addition to the toolkit of any VS Code user interested in leveraging AI for code completion without compromising on privacy or connectivity issues.

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