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Source channel @githubtrending · Post #14791 · Jun 5

#python#ai#ai_agents#ai_memory#cognitive_architecture#cognitive_memory#contributions_welcome#good_first_issue#good_first_pr#graph_database#graph_rag#graphrag#help_wanted#knowledge#knowledge_graph#neo4j#open_source#openai#rag#vector_database Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs. https://github.com/topoteretes/cognee

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djangoproject

@djangoproject · Post #132 · 09/01/2016, 02:47 PM

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https://bit.ly/coroutines At Open Source Bridge and #PyGotham in 2015, and at SCALE14x, I demonstrated that you can code a Python 3 #async framework in under an hour. I start the demo by writing a callback-based async framework, built on non-blocking sockets and a simple event loop. Then I adapt the framework to use generator-based #coroutines, which are cleaner than callbacks but still more efficient than threads for async I/O.

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