ishandutta2007/Top-AI-repos

What it solves

The problem of discovering and keeping track of the most useful open-source AI and machine learning projects on GitHub. With hundreds of thousands of repositories, it's hard to find the influential ones. This list curates 217 of the top repos, sorted by GitHub stars, and organizes them into specialized categories so you can quickly find what you need in generative AI, LLMs, computer vision, agents, and more.

How it works

The repository maintains a table of repos with name, stars, language, description, and creation year. The list is sorted in decreasing order of stars. To make navigation easier, it groups the repos into eight categories (e.g., Agents & Automation, Workflow & App Frameworks, Inference & Serving, RAG & Data, Web UIs, Vision & Audio, Core ML & Training, Research & Evaluation) and provides dedicated guides for each category with their own tables and subcategories. You can explore the full list directly or dive into a category file. The project accepts contributions — you can open an issue or submit a pull request to add or update projects.

Who it's for

Anyone researching or building with open-source AI/ML: developers, researchers, hobbyists, and teams looking to discover new tools, libraries, and frameworks across the AI landscape. It's also useful for those who want a quick overview of the most popular projects in a given area.

Highlights

• 217 curated repositories covering the breadth of AI/ML, including Generative AI, LLMs, deep learning, NLP, computer vision, and more.
• Sorted by number of GitHub stars, giving a sense of community adoption.
• Eight category-specific guides with dedicated tables and deep links for focused exploration.
• Actively maintained — contributions are welcome via issues or pull requests.
• Projects range from foundational frameworks (TensorFlow, PyTorch) to cutting-edge agents (AutoGPT, Claude Code) and tools (Ollama, ComfyUI).