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🎉 Welcome to Managing Gen()AI!

See the website

Our Mission: Simplify and demystify Gen()AI to make it accessible and understandable and increase our ability to manage it.

Our open-source project on Managing Generative AI 🤖 will help people to stay on top of understanding and effectively working with the increasingly complex world of Generative AI.

"Why is it called Gen() AI?"

Generative AI creates. So does will General AI. Depending on their definitions, there may be notable differences, but the overlap ensures that shared characteristics warrant writing this ambiguously, such as GenAI or Gen()AI.

📘 What's Inside?

  • Understanding GenAI: Delve deep into the mechanics, models, and methodologies for building GenAI.
  • Building GenAI: Learn how to build and deploy models.
  • Using GenAI: Where we describe use cases and applications, commercial tools and applications, and the ethics and regulations surrounding GenAI.
  • Managing GenAI: This is the heart of our project, where we describe the tools that we are building to enable quality and responsible development of this and other AI projects.

🚀 GenAI Explaining Itself?

One of our ambitious goals is to have this documentation written and updated by GenAI itself. We aim to:

  • 📝 Set up a base documentation repository that aids in generating self-descriptive content.
  • 🔄 Implement an automated merge and build system for a seamless automation and viewing experience.
  • 🔁 Create a self-referential models using tools like Langchain to enable its supervised self-improvement via pull requests and reviews.
  • 🕸️ Catch the greatest new insights and integrate it into a 'living' document that evolves with time.

We believe in Gen()AI's potential to effectively explain itself even as the technology grows with extreme complexity.

If you're as excited as we are and wish to contribute, join us!

Overview

The goal is to create an AI that can self-improve its documentation and code using tools like Langchain, AutoPR, etc.

It will automatically expand markdown documentation using generative models. The AI will also suggest code improvements to streamline documentation generation. This creates a self-referential system that enhances both docs and code.

We want to keep a human in the loop to oversee changes and provide feedback for further improvements.

Getting Started

  • Clone the repo:
git clone https://github.com/ianderrington/genai.git
  • Install dependencies:
pip install -r requirements.txt
  • Build documentation:
mkdocs serve

If you want to continually edit and see how the changes impact the outcome

mkdocs build; mkdocs serve --livereload

Contributing

We welcome contributions! Please check out the contributing guidelines to get started.

License

This project is licensed under the MIT License - see the LICENSE file for details.