Sean Tauber seantauber

🤖 GenAI, AI, and Data Science Resources

Welcome to my AI GENERATED list of interesting repositories in the fields of Generative AI, Artificial Intelligence, and Data Science. As an AI Engineer & Product Development Specialist in these areas, I've compiled this list to help developers, researchers, and enthusiasts stay up-to-date with the latest advancements and tools.

How This Landing Page Works

This GitHub landing page is automatically updated every day by AI to showcase my latest interests and discoveries in the fields of AI, Machine Learning, and Data Science.

Here's how it works:

Automated Updates: The repository list you see below is automatically updated daily using GitHub Actions that I've set up to run the AI pipeline.
Starred Repositories: The content is based on my GitHub starred repositories, reflecting my current interests and valuable finds in the tech world.
AI-Powered Organization: An AI model (GPT-4o) is used to categorize and organize the repositories, ensuring that the list remains well-structured and informative.
Minimal Manual Intervention: Once set up, this page requires little to no manual updating. All I need to do is star a new repo and it will automatically be categorized and added to this document. When I remove a repo from my starred list, the AI automatically removes it from this page.

Why use AI for this?: The key thing that the LLM-based solution is doing is dynamically deciding what categories should exist on this page and how to group my starred repos into those categories. It also reassesses and changes the categories and groupings over time as the starred repos change. It does all of this without the need for me to decide in advance what categories it should consider or to pre-train the model on categories. Implementing this algorithm is extremely simple compared to implementing a solution with a more traditional ML/AI approach that doesn't have the NLP reasoning capabilities of an LLM.

📚 Table of Contents

Generative AI

Large Language Models (LLMs)

VincentGranville/Large-Language-Models - Large language Models (LLM).
andrewyng/aisuite - Simple, unified interface to multiple Generative AI providers.
adobe-research/dynasaur - Official repository for "DynaSaur: Large Language Agents Beyond Predefined Actions".
microsoft/lida - Automatic Generation of Visualizations and Infographics using Large Language Models.

Artificial Intelligence

vercel/ai - The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents.
huggingface/smol-course - A course on aligning smol models.
run-llama/chat-ui - Chat UI components for LLM apps.
kennethreitz/simplemind - Python API client for AI providers that intends to replace LangChain and LangGraph for most common use cases.
prompt-security/ps-fuzz - Make your GenAI Apps Safe & Secure 🚀 Test & harden your system prompt.
yangchris11/samurai - Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory."

MLOps & AI Infrastructure

Portkey-AI/gateway - A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
anaisbetts/mcp-youtube - A Model-Context Protocol Server for YouTube.
modelcontextprotocol/python-sdk - The official Python SDK for Model Context Protocol servers and clients.
modelcontextprotocol/servers - Model Context Protocol Servers.

Productivity Tools

Kozea/Radicale - A simple CalDAV (calendar) and CardDAV (contact) server.
collective/icalendar - icalendar parser library for Python.
kanboard/kanboard - Kanban project management software.
microsoft/markitdown - Python tool for converting files and office documents to Markdown.

AI Agents

MineDojo/Voyager - An Open-Ended Embodied Agent with Large Language Models.
microsoft/ai-agents-for-beginners - 10 Lessons to Get Started Building AI Agents.
langchain-ai/agent-protocol
TransformerOptimus/SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
ComposioHQ/composio - Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling.
browser-use/browser-use - Make websites accessible for AI agents.

Other

cherysun/chatgpt-siri-shortcut - Talk to ChatGPT with Siri shortcuts on iOS, macOS, and watchOS devices. This open-source project is lightweight and highly customizable.
Ironclad/rivet - The open-source visual AI programming environment and TypeScript library.
caspianmoon/memoripy - An AI memory layer with short- and long-term storage, semantic clustering, and optional memory decay for context-aware applications.
anthropics/claude-code - Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.
lumina-ai-inc/chunkr - Vision infrastructure to turn complex documents into RAG/LLM-ready data.
Tameyer41/liftoff - Mock Interview Simulator with AI-Powered Feedback.

How to Implement This Landing Page On Your Own GitHub

This project automatically updates the README with your GitHub starred repositories using a Python script and GitHub Actions.

1. Clone the repository:

git clone https://github.com/your-username/github-genai-list.git
cd github-genai-list

2. Set up your environment:

Ensure you have Python 3.x installed. You can check your version with:

python --version

3. Install dependencies:

First, make sure pip is up-to-date:

python -m pip install --upgrade pip

Then install the required dependencies:

pip install -r requirements.txt

4. Set up GitHub secrets:

Go to your GitHub repository settings, and under Secrets and variables > Actions, create the following secrets:

GITHUB_TOKEN: Your personal access token for GitHub API.

OPENAI_API_KEY: Your API key for OpenAI (if applicable for LLM updates).

PAT: A GitHub Personal Access Token with appropriate permissions

5. Update the script:

In the update_readme.py script located in the scripts/ directory, replace "YourGitHubUsername" with your actual GitHub username.

6. Configure the GitHub Action:

The workflow is already set up in .github/workflows/update-readme.yml.

It runs daily at midnight (UTC) or can be triggered manually via the GitHub Actions tab.

7. Running locally (optional):

You can also run the script manually to test it locally:

python scripts/update_readme.py

8. Commit and push changes:

git add . git commit -m "Updated project structure" git push origin main

9. Customize the README:

You can modify the README.md template to fit your personal brand and interests.

The GitHub Action will automatically update it with your latest starred repositories daily.

Note: This landing page uses OpenAI's GPT-4o model. Make sure you comply with OpenAI's use-case policies and monitor your API usage to manage costs.

🌟 Contributing

Feel free to open a pull request if you have any suggestions for additions or improvements to this list. Let's collaborate to keep this resource up-to-date and valuable for the community!

📄 License

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

📊 Last edited: 2025-03-19

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