AI plugins for code development

Introduction

Recently, I experimented with integrating AI into my IntelliJ IDEA setup for JVM development, and I wanted to share the steps I followed. It turned out to be really helpful, so maybe this guide can assist someone else in getting started too!

IntelliJ is one of the preferred IDE for Java, Scala and Kotlin development. I have been using the IntelliJ IDEA with plugins for AI, which allows me to use Local LLMs to generate code suggestions, refactor my code and even write tests for me.

What I did

Step 1: Install Ollama

First, visit Ollama and download the version for your operating system. Follow the simple installation steps.

Open your terminal and run ollama pull llama3 to download the model. Start the model by running ollama serve llama3.

Tip	Choosing the right model is very important .

Step 2: IntelliJ Plugins

I tested a few plugins and found Continue.dev really useful:

Note	A list of plugins at the bottom of this article with links

Continue.dev Helps with code completion, converting comments into code, and debugging tips. Works locally (privacy-friendly), quick. Needs decent hardware resources.

Step 3: Setting Up Continue.dev with IntelliJ

Install the Plugin: Open IntelliJ IDEA, navigate to Settings → Plugins, search for "Continue.dev", and install it.

Connect to Ollama: Open the Continue.dev settings and add the local Ollama server URL (http://localhost:11434).

Step 4: Exploring AI Features

Code Suggestions: The plugin provided accurate code completions immediately, significantly speeding up my workflow.

Generating Code from Comments: I tried writing simple English comments, and Continue.dev translated them into functioning code snippets effortlessly.

Debugging: Even when intentionally making small errors, the plugin quickly suggested effective fixes.

Step 5: AI-Assisted Refactoring

I highlighted some messy code. Using the AI suggestions via right-click helped clean up and optimize the code efficiently.

Tips for Best Results:

Regularly update plugins and AI models for optimal performance.

If hardware resources are limited, experiment with smaller models initially.

IntelliJ IDEA Plugins Supporting Local LLM Integration

Plugin	Features	Pros	Cons
Continue.dev	Code completion Natural language to code generation Inline code explanations Supports multiple local LLM providers	- Open-source - Highly customizable - Supports various local LLMs like Ollama, LM Studio, GPT4All	- May require manual configuration for optimal performance
DevoxxGenie	Code review and explanation Unit test generation Retrieval-Augmented Generation (RAG) Integration with various local LLMs	- Fully Java-based - Rich feature set including RAG and Git Diff viewer - Supports multiple local LLMs	- Interface may be overwhelming for beginners
Proxy AI	Connects IntelliJ IDEA with locally running LLMs Provides AI assistance features	- Open-source - Simple setup for local LLM integration	- Limited feature set compared to other plugins
CodeGPT	AI-powered code suggestions Chat interface within IntelliJ IDEA Supports local LLMs via LM Studio	- User-friendly interface - Supports multiple programming languages	- May require additional setup for local LLM integration
JetBrains AI Assistant	AI-driven code suggestions Code explanations and documentation generation Integration with local LLMs	- Official JetBrains plugin - Seamless integration with IntelliJ IDEA	- May have limited customization compared to open-source alternatives

Plugin

Features

Pros

Cons

Continue.dev