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GenAIScript - Comment Code with AI

  • Documenting code is a necessity, and AI LLM models simplify the task of commenting while coding.
  • GenAIScript is an open-source scripting environment that streamlines tasks for AI analysis by automating complex processes within a cohesive scripting framework. It facilitates ingestion of diverse document formats and supports the generation of structured outputs.
  • A batch processing approach is implemented using an AI-powered Command-Line Interface (CLI) that runs on the code-base and uses primarily local LLM models.
  • The author used the RAG approach with Abstract Syntax Tree (AST) as a way to reduce context on which LLM has to reason, provide hierarchical views of code's syntax and abstracting away irrelevant details, to divide a source code file into meaningful pieces.
  • Tree-Sitter, an AST tool with an incremental parsing library that can build a concrete syntax tree for a source file, was used by the author to implement the Commenter CLI that generates high-quality comments for existing code within a codebase.
  • The Commenter CLI is composed of the following steps – loading each source file, submitting its content to the AST parser, which extracts code chunks, invoking LLM model, which reviews implementation and produces a comment based on the chunk, Comment + Chunk is provided back to the AST parser to verify that LLM has produced is valid code for given language, and finally joining all chunks and related comments.
  • The Commenter CLI method saves time and improves the overall quality of documentation, making the codebase easier for developers to understand and work with.
  • The qwen2.5-coder:7b model worked well for code commenting tasks, which the author used for the first release of the tool available on the Github project.
  • Overall, the Commenter tool makes it easier for developers to improve the readability and understandability of their code.
  • Article originally published on https://bsorrentino.github.io on December 20, 2024.

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