Readme Ai
README file generator, powered by AI.
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What is Readme Ai?
Readme Ai is an AI-powered documentation assistant that automatically generates comprehensive README files for software projects. Simply provide a GitHub repository URL or local codebase path, and the tool analyzes your code, extracts metadata, and generates a well-structured README with project introduction, features table, project structure, getting started guides, installation instructions, usage guides, testing information, contribution guides, and community support sections.
The tool works by cloning the codebase into a temporary directory, parsing each file to extract metadata, injecting this metadata into prompt templates, sending them to an AI API, and writing the generated content into markdown code blocks for the README file. It supports multiple AI providers including OpenAI, Anthropic, Google Gemini, and Ollama, and even has an offline mode that doesn't require any API service.
Readme Ai is highly customizable with dozens of styling options including header styles (classic, modern, compact, console, banner), badge colors and styles (flat-square, for-the-badge, plastic), navigation styles (bullet, roman, number, accordion, fold), emoji themes (solar, water, rainbow), and logo options. It is language-agnostic and works with any programming language or framework, supporting repositories from GitHub, GitLab, Bitbucket, and local file systems.
This tool is designed for developers of all experience levels who want to streamline their project documentation process. It's particularly useful for open-source maintainers who need to create professional READMEs quickly, developers who struggle with documentation formatting, teams wanting consistent documentation structure across projects, and anyone looking to enhance their project's quality and discoverability on GitHub.
Readme Ai pricing
Pricing model: Freemium
ReadmeAI itself is completely free and open source under the MIT license. The Python package 'readmeai' is available on PyPI at no cost. However, using third-party AI API services requires paying those providers: OpenAI (gpt-3.5-turbo default is low-cost, gpt-4 series costs more), Anthropic (Claude models have their own pricing), Google Gemini (Google's pricing applies). Ollama is free for local models with no API key needed. Offline mode is completely free with no API costs. The Streamlit web app is free to use in your browser.
Readme Ai pros
- Generates comprehensive README files with a single command
- Supports multiple AI providers (OpenAI, Anthropic, Gemini, Ollama)
- Works completely offline without any API key needed
- Language agnostic - supports any programming language or framework
- Highly customizable with dozens of styling options
- Multiple header styles (classic, modern, compact, console, banner)
- Configurable badge colors and styles for badges
- Multiple navigation styles (bullet, roman, number, accordion, fold)
- Emoji theme packs (solar, water, rainbow) for section titles
- Custom logo options including custom images
- Supports GitHub, GitLab, Bitbucket, and local file systems
- Generates project directory tree visualization
- Extracts dependencies and system requirements automatically
- Supports .readmeaiignore for intelligent file filtering
- Available via pip, pipx, uv, Docker, and from source
- Default model gpt-3.5-turbo offers best cost-performance balance
- Streamlit web app available for browser use without installation
- MIT license - completely open source
- Active development with regular releases
- Comprehensive example gallery showcasing diverse projects
Readme Ai cons
- Requires API key for OpenAI, Anthropic, and Google Gemini services
- Using gpt-4 or higher models may incur unexpected charges
- Streamlit web app may not always have latest features
- Requires Python 3.9 or higher prerequisite
- Extra dependencies needed for Anthropic and Google Gemini clients
- Offline mode may have limited capabilities compared to AI modes
- First-time setup requires environment variable configuration
- Custom logo requires providing image URL or path
- Temperature and model settings need manual configuration for optimal results
- Docker requires mounting volumes and setting environment variables
Frequently asked questions about Readme Ai
What is ReadmeAI?
ReadmeAI is a developer tool that automatically generates README files using a robust repository processing engine and advanced language models. Simply provide a URL or path to your codebase, and a well-structured and detailed README will be generated with project introduction, features, installation instructions, usage guides, and more.
How do I install ReadmeAI?
ReadmeAI can be installed via pip (recommended): pip install -U readmeai. Alternative installation methods include pipx for isolated environments, uv for high-performance installation, Docker by pulling zeroxeli/readme-ai:latest, or from source by cloning the repository and installing dependencies.
What AI providers does ReadmeAI support?
ReadmeAI supports OpenAI (industry-leading models, default gpt-3.5-turbo), Anthropic (Claude language models for advanced tasks), Google Gemini (multimodal AI with latest Google technology), and Ollama (open source local models with no API key needed). You can switch between providers anytime.
Do I need an API key to use ReadmeAI?
An API key is required when using third-party services like OpenAI, Anthropic, or Google Gemini. Set it via environment variables (e.g., export OPENAI_API_KEY=<your_key>). However, you can use Ollama with local models without any API key, or use offline mode which requires no internet or API service at all.
What is offline mode?
Offline mode allows you to generate README files without using any LLM API service. Run with the command: readmeai --api offline -o readmeai-offline.md -r https://github.com/eli64s/readme-ai. This is completely free with no API costs and no internet required.
What repositories does ReadmeAI support?
ReadmeAI supports repositories from GitHub (industry-standard hosting), GitLab (full DevOps integration), Bitbucket (Atlassian ecosystem), and local file systems. You can provide a repository URL or the full path to a local project directory.
How do I customize the README style?
Use CLI options like --header-style (classic, modern, compact, console, banner), --badge-style (flat-square, for-the-badge, plastic), --badge-color (hex code or color name), --navigation-style (bullet, roman, number, accordion, fold), --emojis (solar, water, rainbow), --logo (custom image or preset), and --align (left, center).
What sections are included in generated READMEs?
Generated READMEs include: Project Introduction (essence and value proposition), Features Table (detailed breakdown), Project Structure (directory tree), Project Index (key modules), Getting Started Guides (dependencies and requirements), Installation/Usage/Testing instructions, Community & Support (roadmap, contributions, license), and Contribution Guides with contributor graphs for open-source projects.
Can I use ReadmeAI with local models?
Yes, use Ollama for local open-source models. First pull a model: ollama pull llama3.2:latest, then start the server: export OLLAMA_HOST=127.0.0.1 && ollama serve. Run with: readmeai --api ollama --model llama3.2 -r https://github.com/eli64s/readme-ai. No API key is needed.
What programming languages does ReadmeAI support?
ReadmeAI is completely language agnostic and works with any programming language or framework. The example gallery showcases READMEs generated for Python, Go, Docker, FastAPI, Java, PostgreSQL, Kotlin, Streamlit, Vercel, NPM, Apache Flink, and more. It extracts information from source code regardless of the language used.