This repository provides in-depth tutorials and practical examples for Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and real-world AI agent applications. It targets beginners, practitioners, and researchers seeking to implement, adapt, and scale AI solutions in their projects.

How It Works

The hub focuses on practical, hands-on learning through detailed tutorials and runnable code examples. It aims to bridge the gap between theoretical understanding and real-world application of AI technologies, enabling users to gain experience and build complex AI systems.

Highlighted Details

• In-depth tutorials on LLMs and RAGs.
• Real-world AI agent application examples.
• Resources for implementation, adaptation, and scaling.

Maintenance & Community

The project encourages community contributions through pull requests and issue reporting. Users can connect via the issue tracker for discussions and suggestions.

Licensing & Compatibility

This repository is licensed under the MIT License, permitting commercial use and integration into closed-source projects.

Limitations & Caveats

The repository primarily serves as a collection of tutorials and examples; it is not a runnable application or framework itself.