Source URL: https://github.com/gr-b/repogather
Source: Hacker News
Title: Show HN: Repogather – copy relevant files to clipboard for LLM coding workflows
Feedly Summary: Comments
AI Summary and Description: Yes
Summary: Repogather is a command-line tool designed for code understanding and generation, leveraging language models (LLMs) like GPT-4o-mini for file relevance assessment. Its ability to filter code files and maintain project structure makes it relevant for professionals involved in software development, particularly in DevSecOps workflows where efficient code analysis is paramount.
Detailed Description:
Repogather stands out as a versatile command-line utility aimed at developers and data scientists who need to navigate and analyze large codebases efficiently. The tool employs advanced LLM capabilities for file relevance evaluation, streamlining workflows in applications such as code generation and understanding. Here are the major points of relevance:
– **Functionality Overview**:
– Copies relevant files from a repository to the clipboard along with their relative paths.
– Designed for integration into LLM-assisted workflows, enhancing code comprehension and generation tasks.
– **Filtering Capabilities**:
– Excludes test and configuration files by default but allows including them via command options.
– Filters out common irrelevant directories and files like `node_modules` and `venv`, and adheres to `.gitignore` rules.
– **LLM Utilization**:
– Uses OpenAI’s GPT models (e.g., gpt-4o-mini) to evaluate the relevance of files based on user queries.
– Ability to operate without LLM analysis to return all files, which may be useful in certain contexts.
– **Token Limit and Cost Management**:
– Provides estimates on token count and expected API usage costs prior to processing.
– Handles large repositories by splitting content into multiple requests, thereby managing API token limits effectively.
– **Installation and Usage**:
– Can be installed easily via pip, with straightforward configurations for setting up the OpenAI API key.
– Offers a variety of command-line options to customize file inclusions or exclusions, relevance thresholds, and model preferences.
– **Practical Applications**:
– Ideal for codebases where specific functionalities need to be gathered and examined quickly.
– Supports commands that tailor the search for particular file types, enhancing developer productivity.
– **Example Command Use**:
– A sample command can search for files related to user authentication while including configuration files, providing a relevance threshold, and utilizing a specific model.
– **User Confirmation and API Key**:
– When performing LLM analysis, users must confirm expected costs based on token input. If not using LLMs, the API key isn’t needed.
This tool is particularly significant in environments where security and compliance are indispensable, as it aids in quickly locating relevant code sections that may require scrutiny for vulnerabilities or compliance checks, thus enhancing overall security posture within software development workflows.