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docs-gen-js-ts

v1.0.3

Published

A TypeScript-based documentation generator for local repositories.

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Links

Maintainers

shalwin04shalwin04

Keywords

documentationgeneratortypescriptdocs-gennpm package

Readme

Documentation Generator with LangChain and Google Generative AI

This project is a Documentation Generator for local repositories that leverages LangChain, Google Generative AI (Gemini-1.5-flash), and LangGraph to analyze code and generate detailed, high-quality API documentation. The tool processes JavaScript and TypeScript files, splits them into manageable chunks, and generates documentation with suggestions for improvement.

Table of Contents

  1. Features
  2. Installation
  3. Usage
  4. Configuration
  5. Technologies Used
  6. File Structure
  7. Future Improvements
  8. License: MIT

Features

  • Automatically loads and analyzes files from a specified directory.
  • Uses Google Generative AI to generate detailed documentation for:
    • API Endpoints
    • Functions and Methods
    • Data Models
    • Design Patterns
    • Security Considerations
  • Includes a reflection step for documentation critique and improvement.
  • Implements LangGraph for iterative workflows.
  • Provides customizable chunk size and overlap for text splitting.
  • Streams results to handle large outputs efficiently.

Usage

Installation

Prerequisites

Ensure the following are installed on your machine:

  • Node.js (v18+ recommended)
  • npm or yarn
  • Google API Key for Generative AI
  • Unstructured API Key (optional, for advanced text loading)

Steps

  1. Install the package

    npm install docs-gen-js-ts

  2. RUn the script

    docs-gen
    • The project will scan the specified directory (process.cwd() by default), split the documents, and generate API documentation based on the loaded code files.

Technologies Used

  • LangChain: Framework for building AI-driven workflows.
  • Google Generative AI (Gemini): Generates detailed and insightful documentation.
  • LangGraph: Manages iterative workflows with state graphs.
  • TypeScript: Ensures type safety and maintainability.
  • Node.js: Executes the backend logic.

Future Improvements

  • Add support for more programming languages.
  • Integrate with cloud storage for generated documentation.
  • Improve error handling for edge cases (e.g., large repositories).
  • Enhance the reflection process with additional critique points.

Developed by Shalwin. If you have questions or feedback, feel free to reach out!