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Source channel @githubtrending · Post #15131 · Sep 9

#python#agent#llms AutoAgent lets you create and use powerful AI agents easily by just using natural language—no coding needed. It supports many large language models (LLMs) like OpenAI and Anthropic, and performs as well as top research AI systems on benchmarks. You can build tools, agents, and workflows quickly, manage data efficiently with its built-in vector database, and interact flexibly through different modes. It’s lightweight, customizable, and cost-effective, making it a personal AI assistant that helps automate complex tasks simply and efficiently. This saves you time and technical effort while giving you advanced AI capabilities. https://github.com/HKUDS/AutoAgent

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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