🦾 The Cleanest way to write GenAI applications (it's NOT Langchain)

In this tutorial, I show you how to easily integrate Large Language Models (LLMs) into your Python code using Magentic.

It explores the powerful features of Magentic, including the @prompt and @chatprompt decorators, structured output, function calling, asynchronous execution, and streaming.

You'll learn how to create complex LLM-powered applications with minimal boilerplate code, and leverage the capabilities of multiple LLM providers like OpenAI, Anthropic, LiteLLM, and Mistral.

The code is available on GitHub: https://github.com/bitswired/magentic...
And here is the Magentic repo: https://github.com/jackmpcollins/mage...

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00:00 Intro To Magentic
00:56 The @prompt Decorator
02:00 Choose Your Backend
03:51 The @chatprompt Decorator
04:51 Structured Output
07:41 Function Calling
10:55 Asynchronous Execution
13:04 Streaming
15:21 Object Streaming