This repository offers a curated collection of practical, AI-powered applications and agentic systems, demonstrating the use of Large Language Models (LLMs) from various providers and self-hosted options. It targets AI engineers and developers seeking to build production-ready, scalable AI solutions, showcasing use cases for AI agents and Retrieval-Augmented Generation (RAG).

How It Works

The project showcases diverse LLM applications, including agent-based systems and RAG implementations. It emphasizes practical use cases and best practices for building scalable, production-ready AI solutions, leveraging models from providers like Google, Anthropic, and OpenAI, as well as self-hosted open-source alternatives.

Highlighted Details

• Demonstrates practical use cases for AI agents.
• Features implementations of Retrieval-Augmented Generation (RAG).
• Focuses on best practices for scalable AI solutions.

Maintenance & Community

Contributions are welcomed via pull requests.

Licensing & Compatibility

Licensed under the MIT License, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

The repository is a curated collection of examples and does not provide a unified framework or platform. Specific setup and dependencies will vary per application showcased.