readmeai 0.4.975

🚀 Generate beautiful README.md files from the terminal using GPT LLM APIs 💫

README-AI

Auto-generate informative README.md files using GPT language model APIs 👾

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🔗 Quick Links

• README-AI
  • 🔗 Quick Links
  • 📍 Overview
  • 🤖 Demo
  • 🔮 Features
    • Customizable Header
  • 🚀 Getting Started
    • ⚙️ Installation
    • 👩‍💻 Running README-AI
    • 🧪 Tests
    • 🧩 Configuration
      • CLI Options
      • Custom Settings
  • 🛠 Project Roadmap
  • 📒 Changelog
  • 🤝 Contributing
  • 📄 License
  • 👏 Acknowledgments

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📍 Overview

Objective

Developer tool that automatically generates detailed README.md files using GPT language model APIs. Simply provide a repository URL or local directory path to your code, and readme-ai handles the rest!

Motivation

Streamlines documentation creation and maintenance, enhancing developer productivity. README-AI aims to enable all skill levels, across all domains, to better understand, use, and contribute to open-source projects.

[!IMPORTANT]

README-AI is currently under development with an opinionated configuration and setup. It is vital to review all text generated by the LLM APIs to ensure it accurately represents your project.

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🤖 Demo

Standard CLI usage from the terminal with an OpenAI API key.

readmeai-cli-demo

You can also run the readme-ai without an API key, passing the --offline flag to the CLI.

readmeai-cli-offline-demo

[!TIP]

Offline mode is useful for quickly generating a boilerplate README without incurring API costs. See an example README file generated in offline mode here.

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🔮 Features

README-AI is built with flexibility in mind, allowing users to customize various aspects of the README file using CLI options and configuration settings. Currently, 4 pieces of information used in the output file are generated using GPT language model APIs.

• Project slogan displayed in the README header.
• Codebase file summaries display in markdown tables.
• Overview section that highlights your project's value proposition.
• Features section that overviews technical components of your codebase

The rest of the content is extracted using from analyzing repository metadata, configuration settings, and templates.

Customizable Header

The header section is built using repository metadata and including the following information.

• Badges: Svg icons are built using codebase metadata. Current options are provided by shields.io and skill-icons!
• Project Logo: Select from a handful of default images or provide your own to the CLI.
• Project Slogan: A catch phrase is created by prompting OpenAI's LLM API.
• Table of Contents/Quick Links: Help users navigate the README file.

Examples of different header configurations generated by readme-ai are shown below.

--badges flat --image blue	--badges for-the-badge --image black --offline
--align left --badges flat-square --image black	--badges plastic --image blue
--badges skills-light --image blue	--badges flat-square --image gradient

📑 Codebase Documentation

Repository Structure A directory tree structure is generated using pure Python (readmeai.markdown.tree.py) and visualized in your README.

Codebase Summaries File summaries are generated using OpenAI's API, grouped by directory, and inserted into markdown tables.

🧩 Overview & Features Table

The overview and features table sections are generated using OpenAI's API and markdown templates. Prompts are embedded with your repository's metadata to generate content that is relevant to your project.

Overview High-level introduction of the repository, focused on the project's value proposition and use-case, rather than technical aspects.

Features Table Detailed overview of the technical components of the codebase, including the architecture, dependencies, testing, and more.

🚀 Dynamic Getting Started Instructions

Getting Started This tool generates instructions for installing, running, and testing your project. These steps are created by identifying the dependencies and languages used in the codebase, and referring to our language_setup.toml configuration file.

🤝 Contributing Guidelines, License, & More

Common README Sections The remaining sections of the README is generated from a template, including common sections such as project roadmap, contributing guidelines, license, and acknowledgements.

🧪 Templates

This feature is currently under development. The template system will allow users to generate README files in different flavors, such as AI/ML, data science, web development, etc.

AI/ML README Template Overview: Summary of the projects' objectives, scope, and expected outcomes. Project Structure: Overview of the organization of the projects and their main components. Data Preprocessing: Data sources, collection methods, and types of data Feature Engineering: Importance of feature engineering and its impact on model performance. Model Architecture and Development: Model selection, dev strategies, and implemented algorithms. Training and Validation: Info on model training procedures, hyperparameter tuning, and validation strategies. Testing and Evaluation: Model testing results, performance analysis, and comparison with benchmarks. Deployment and Integration: Integration with other systems, APIs, and user interfaces Usage and Maintenance: User guide on how to use the deployed models and interfaces. Results and Discussion: Implications, limitations, and future work. Ethical Considerations: Ethical aspects, data privacy, and fairness in model predictions. Contributing: Procedures for submitting contributions, reporting issues, and proposing enhancements. Acknowledgements: References to resources, libraries, and frameworks used. License: Explanation of usage rights, restrictions, and attribution requirements.

💥 Examples

	Output File	Repository	Languages
1️⃣	readme-python.md	readme-ai	Python
2️⃣	readme-typescript.md	chatgpt-app-react-typescript	TypeScript, React
3️⃣	readme-javascript.md	(repository deleted)	JavaScript, React
4️⃣	readme-kotlin.md	file.io-android-client	Kotlin, Java, Android
5️⃣	readme-rust-c.md	rust-c-app	C, Rust
6️⃣	readme-go.md	go-docker-app	Go
7️⃣	readme-java.md	java-minimal-todo	Java
8️⃣	readme-fastapi-redis.md	async-ml-inference	Python, FastAPI, Redis
9️⃣	readme-mlops.md	mlops-course	Python, Jupyter
🔟	readme-pyflink.md	flink-flow	PyFlink

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🚀 Getting Started

Prerequisites

Ensure that you have the following dependencies installed on your system.

• Python 3.9, 3.10, 3.11, or 3.12
• Package manager or container runtime (pip, docker, conda, etc.)
• OpenAI API account and API key (Additional API endpoints coming soon!)

Code Repository

A remote repository URL or local directory path to your project is required to generate a README file. The following repository sources are currently supported.

• GitHub
• GitLab
• Bitbucket
• File System

OpenAI API

An OpenAI API account and API key are needed to use readme-ai. The following steps outline the process.

🔐 OpenAI API Account Setup

1. Go to the OpenAI website.
2. Click the "Sign up for free" button.
3. Fill out the registration form with your information and agree to the terms of service.
4. Once logged in, click on the "API" tab.
5. Follow the instructions to create a new API key.
6. Copy the API key and keep it in a secure place.

Additionally, it is essential to understand the potential risks and costs associated with using LLM APIs.

[!WARNING]

Please review the following information before using readme-ai.

1. Review Sensitive Information: Before running readme-ai, ensure all content in your repository is free of sensitive information. This tool does not remove sensitive data from your codebase, nor from the output README.

2. API Usage Costs: The OpenAI API is not free and costs can accumulate quickly! You will be charged for each request made by readme-ai. Be sure to monitor API usage costs using the OpenAI API Usage Dashboard.

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⚙️ Installation

Using pip

pip install readmeai

Using docker

docker pull zeroxeli/readme-ai:latest

Using conda

conda install -c conda-forge readmeai

Alternatively, clone the readme-ai repository and build from source.

git clone https://github.com/eli64s/readme-ai && \
cd readme-ai

Then use one of the methods below to install the project's dependencies (Bash, Conda, Pipenv, or Poetry).

Using bash

bash setup/setup.sh

Using pipenv

pipenv install && \
pipenv shell

Using poetry

poetry install && \
poetry shell

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👩‍💻 Running README-AI

Before running the application, ensure that you have an OpenAI API key and that it is set as an environment variable.

On Linux or MacOS

export OPENAI_API_KEY=YOUR_API_KEY

On Windows

set OPENAI_API_KEY=YOUR_API_KEY

Use one of the methods below to run the application (Pip, Docker, Conda, Streamlit, etc).

Using pip

readmeai --repository https://github.com/eli64s/readme-ai

Using docker

docker run -it \
-e OPENAI_API_KEY=$OPENAI_API_KEY \
-v "$(pwd)":/app zeroxeli/readme-ai:latest \
-r https://github.com/eli64s/readme-ai

Using conda

readmeai -r https://github.com/eli64s/readme-ai

Using streamlit

[!NOTE]

The web app is hosted on Streamlit Community Cloud, a free service for sharing Streamlit apps. Thus, the app may be unstable or unavailable at times. See the readme-ai-streamlit repository for more details.

Alternatively, run the application locally from the cloned repository.

Using pipenv

pipenv shell && \
python3 -m readmeai.cli.commands -o readme-ai.md -r https://github.com/eli64s/readme-ai

Using poetry

poetry shell && \
poetry run python3 -m readmeai.cli.commands -o readme-ai.md -r https://github.com/eli64s/readme-ai

See the Configuration section below for the complete list of CLI options and settings.

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🧪 Tests

Use pytest to run the default test suite.

make test

Use nox to run the test suite against multiple Python versions including (3.9, 3.10, 3.11, 3.12).

nox -f noxfile.py

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🧩 Configuration

Run the readmeai command in your terminal with the following options to tailor your README file.

CLI Options

Flag (Long/Short)	Default	Description	Type	Status
--align/-a	center	Set header text alignment (left, center).	String	Optional
--api-key/-k	OPENAI_API_KEY env var	Your GPT model API key.	String	Optional
--badges/-b	flat	Badge style options for your README file.	String	Optional
--emojis/-e	False	Add emojis to section header tiles.	Boolean	Optional
--image/-i	blue	Project logo image displayed in README header.	String	Optional
--max-tokens	3999	Max number of tokens that can be generated.	Integer	Optional
--model/-m	gpt-3.5-turbo	Select GPT model for content generation.	String	Optional
--offline	False	Generate a README without an API key.	Boolean	Optional
--output/-o	readme-ai.md	README output file name.	Path/String	Optional
--repository/-r	None	Repository URL or local path.	URL/String	Required
--temperature/-t	1.0	LLM API creativity level.	Float	Optional
--template	None	Choose README template.	String	WIP
--language/-l	English (en)	Language for content.	String	WIP

_{WIP = work in progress, or feature currently under development.
For additional command-line information, run readmeai --help in your terminal for more details about each option.}

Badge Icons

Select your preferred badge icon style for your README file using the --badges flag. The following options are currently supported.

Badge	Preview
flat
flat-square
for-the-badge
plastic
skills
skills-light
social

Project Logo

Select an image to display in your README header section using the --image flag. The following options are currently supported.

Image	Preview
custom	Provide a custom image URL.
black
blue
gradient
purple
yellow

Custom Settings

The readme-ai tool is designed with flexibility in mind, allowing users to configure various aspects of its operation through a series of models and settings. The configuration file covers aspects such as language model settings, git host providers, repository details, markdown templates, and more.

🔠 Configuration Models

GitService Enum

• Purpose: Defines Git service details.
• Attributes:
  • LOCAL, GITHUB, GITLAB, BITBUCKET: Enumerations for different Git services.
  • host: Service host URL.
  • api_url: API base URL for the service.
  • file_url: URL format for accessing files in the repository.

BadgeOptions Enum

• Purpose: Provides options for README file badge icons.
• Options: FLAT, FLAT_SQUARE, FOR_THE_BADGE, PLASTIC, SKILLS, SKILLS_LIGHT, SOCIAL.

ImageOptions Enum

• Purpose: Lists CLI options for README file header images.
• Options: CUSTOM, BLACK, BLUE, GRADIENT, PURPLE, YELLOW.

CliSettings

• Purpose: Defines CLI options for the application.
• Fields:
  • emojis: Enables or disables emoji usage.
  • offline: Indicates offline mode operation.

FileSettings

• Purpose: Configuration for various file paths used in the application.
• Fields: dependency_files, identifiers, ignore_files, language_names, language_setup, output, shields_icons, skill_icons.

GitSettings

• Purpose: Manages repository settings and validations.
• Fields:
  • repository: The repository URL or path.
  • source: The source of the Git repository.
  • name: The name of the repository.

LlmApiSettings

• Purpose: Holds settings for OpenAI's LLM API.
• Fields: content, endpoint, encoding, model, rate_limit, temperature, tokens, tokens_max.

MarkdownSettings

• Purpose: Contains Markdown templates for different sections of a README.
• Fields: Templates for aligning text, badges, headers, images, features, getting started, overview, tables of contents, etc.

PromptSettings

• Purpose: Configures prompts for OpenAI's LLM API.
• Fields: features, overview, slogan, summaries.

AppConfig

• Purpose: Nested model encapsulating all application configurations.
• Fields: cli, files, git, llm, md, prompts.

AppConfigModel

• Purpose: Pydantic model for the entire application configuration.
• Sub-models: AppConfig.

ConfigHelper

• Purpose: Assists in loading additional configuration files.
• Methods: load_helper_files to load configuration from different files.

Functions

_get_config_dict

• Purpose: Retrieves configuration data from TOML files.
• Parameters:
  • handler: Instance of FileHandler.
  • file_path: Path to the configuration file.

load_config

• Purpose: Loads the main configuration file.
• Parameters:
  • path: Path to the configuration file.
• Returns: An instance of AppConfig.

load_config_helper

• Purpose: Loads multiple configuration helper files.
• Parameters:
  • conf: An instance of AppConfigModel.
• Returns: An instance of ConfigHelper.

Usage

The configurations are loaded using the load_config function, which parses a TOML file into the AppConfigModel. This model is then used throughout the application to access various settings. Additional helper files can be loaded using ConfigHelper, which further enriches the application's configuration context.

Return

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🛠 Project Roadmap

• Publish readme-ai CLI as a Python package on PyPI.
  • PyPI Package
• Containerize the readme-ai CLI as a Docker image via Docker Hub.
  • Docker Hub Image
• Serve the readme-ai CLI as a web app, deployed on Streamlit Community Cloud.
  • Streamlit Web Application
• Integrate singular interface for all LLM API providers (Anthropic, Cohere, Gemini, etc.)
• Design template system to give users a variety of README document flavors (ai, data, web, etc.)
• Develop robust documentation generation process that can extend to full project docs (i.e. Sphinx, MkDocs, etc.)
• Add support for generating README files in any language (i.e. CN, ES, FR, JA, KO, RU).
• Create GitHub Actions script to automatically update README file content on repository push.

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📒 Changelog

Changelog

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🤝 Contributing

• Discussions
• Open an Issue
• Contributing Guidelines

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📄 License

MIT

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👏 Acknowledgments

Badges

• Shields.io
• Aveek-Saha/GitHub-Profile-Badges
• Ileriayo/Markdown-Badges
• tandpfun/skill-icons

Return

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