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Source channel @githubtrending · Post #15325 · Dec 10

#python#agent#llm#rag#tutorial You can learn to build smart AI agents from scratch with a free, open-source tutorial called Hello-Agents by Datawhale. It covers everything from basic concepts and history to hands-on projects like creating your own AI agent framework and multi-agent systems. The course includes practical skills such as memory, context handling, communication protocols, and training large language models. By following it, you gain deep understanding and real coding experience, moving from just using AI models to designing intelligent systems yourself. This helps you develop advanced AI skills useful for jobs, research, or building innovative AI applications. The materials are online and easy to access anytime. https://github.com/datawhalechina/hello-agents

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djangoproject

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

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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

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#wallaroo #distributed_state #tasks #state #requests #pipeline