10 Simple Tools for Building LLM Apps with Python Code Examples

Discover 10 essential tools and Python libraries for building powerful LLM applications in this 19-minute video tutorial. Learn about generating structured outputs with PydanticAI, routing models through OpenRouter, implementing load balancing with LiteLLM, and other industry-standard technologies. Perfect for both beginners starting their first LLM projects and experienced developers looking to enhance their applications. The tutorial covers structured outputs, LLM routing, load balancing, monitoring and logging, parsing and chunking, vector databases, web search integration, deep learning frameworks, and deployment strategies—all with practical Python code examples. Additional resources include links to related videos on Retrieval Augmented Generation, fine-tuning language models, DSPy, and PyTorch, plus a comprehensive article on vector databases.