Developers can deeply utilize the following core features to achieve leaps in efficiency:
- Intelligent Code Assist::
Input code snippets or error reporting information directly in the dialog interface, AI will perform syntax checking, suggest performance optimization (e.g., change Python loops to list derivatives), and automatically highlight the modified code, supporting 30+ programming languages. - Interactive debugging::
Locate the problem through multiple rounds of dialog, e.g., type "This Go code is panic, how can I fix it?" The AI will step by step analyze the stack information and propose a solution. - API Documentation::
Upload technical documentation (e.g., official Python library instructions), ask questions in natural language (e.g., "What are the common formatting characters for datetime.strftime?"), and the AI will pinpoint the content of the document. - Workflow integration::
With the "Quick Notes" feature, you can record code snippets and AI suggestions in Markdown, and support one-click export to .md file, which is convenient for importing into IDEs such as VS Code.
advanced techniqueThe "prompt templates" are pre-stored with frequently used commands (e.g., "Rewrite the following Python code in Rust") for quick reuse, and the model manager switches between models that specialize in code (e.g., CodeLlama) to get more professional advice.
This answer comes from the articleKunAvatar (kun-lab): a native lightweight AI dialog client based on OllamaThe
May not be reproduced without permission:AI productivity tools " As a developer, how can I utilize kun-lab's code-related features to improve my productivity?
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