This repository provides code examples and tutorials for building AI applications, targeting developers and AI enthusiasts. It offers practical implementations of various LLM providers, frameworks, agents, and cloud services, enabling users to quickly learn and apply cutting-edge AI technologies.

How It Works

The project is structured around a collection of tutorials, each demonstrating specific AI concepts and tools. It leverages popular libraries like LlamaIndex, LangGraph, and CrewAI, integrating with LLM providers such as OpenAI and Google Gemini. The code is organized by framework and includes practical examples for agents, RAG systems, and cloud deployments, often with accompanying YouTube videos for in-depth explanations.

Quick Start & Requirements

• Installation typically involves cloning the repository and installing dependencies via requirements.txt or package.json.
• Specific tutorials may require API keys for LLM providers (OpenAI, Google), Docker for services like Milvus, or specific Python versions.
• Links to official documentation, YouTube tutorials, and demos are provided for each example.

Highlighted Details

• Demonstrates building AI agents with LangGraph, including memory management with PostgreSQL and pgvector.
• Features practical applications of CrewAI for tasks like podcast preparation and personalized poem writing.
• Includes examples for integrating with cloud platforms like Google Cloud Vertex AI and Snowflake Cortex LLM functions.
• Showcases observability with LangSmith and vector database interactions with Milvus.

Maintenance & Community

The repository is maintained by Rok Benko, creator of the "Code AI with Rok" YouTube channel. Contributions are welcomed for reporting issues, fixing typos, and suggesting new topics.

Licensing & Compatibility

This project is open-source and available under the MIT license, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

The project's primary focus is on educational content linked to YouTube tutorials. While comprehensive, some advanced features or specific configurations might require further exploration beyond the provided code snippets. The use of AI voiceover in accompanying videos is a stylistic choice.