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Source channel @githubtrending · Post #14936 · Jul 9

#jupyter_notebook This course guides you through building and deploying your own AI agents using popular tools like OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and MCP over six weeks. You’ll learn to create agents that can think, act, and work together, with clear setup instructions for Windows, Mac, and Linux, plus support if you get stuck. The benefit is that you gain hands-on experience in the latest AI agent technology, making you ready to develop smart, autonomous systems for real-world tasks, while also connecting with a helpful community and having fun along the way[1][2][3]. https://github.com/ed-donner/agents

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djangoproject

@djangoproject · Post #519 · 12/10/2017, 06:14 PM

https://blog.wallaroolabs.com/2017/12/stateful-multi-stream-processing-in-python-with-wallaroo/ #Wallaroo is a high-performance, open-source framework for building distributed stateful applications. In an earlier post, we looked at how Wallaroo scales #distributed_state. In this post, we’re going to see how you can use Wallaroo to implement multiple data processing #tasks performed over the same shared #state. We’ll be implementing an application we’ll call “Market Spread” that keeps track of the latest pricing information by stock while simultaneously using that state to determine whether stock order #requests should be rejected. #pipeline