Build Your AI Coding Assistant

Build Your AI Coding Assistant

Overview

This project provides a comprehensive guide on how to create an end-to-end AI coding assistant, similar to GitHub Copilot, JetBrains AI Assistant, and AutoDev. It covers everything from IDE plugin development, model selection, dataset construction, to model fine-tuning.

Key Features

• IDE Plugin Development: Learn how to build plugins for popular IDEs like JetBrains and VSCode.
• Model Selection and Fine-tuning: Understand how to choose the right AI models and fine-tune them for your specific needs.
• Dataset Construction: Get insights into building high-quality datasets for training your AI assistant.
• Contextual Code Completion: Implement features for inline, in-block, and after-block code completions.
• Code Explanation and Review: Enable your assistant to explain code snippets and conduct code reviews.
• Customizable Scenarios: Allow developers to customize the AI capabilities based on their specific requirements.

Benefits

• Enhanced Developer Productivity: By automating repetitive coding tasks, developers can focus on more complex problems.
• Improved Code Quality: AI-assisted code reviews can help maintain high standards in code quality.
• Flexibility and Customization: Tailor the AI assistant to fit the unique workflows of your development team.

Highlights

• Open-source project with contributions from the Thoughtworks community.
• Utilizes advanced AI models like DeepSeek Coder based on Llama architecture.
• Comprehensive documentation and resources for developers to get started quickly.