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Source channel @githubtrending · Post #15518 · Feb 24

#rust#ai#ai_ocr#attention_mechanism#gnn#gnn_model#gnns#graph#graph_neural_networks#llm_inference#low_latency#mincut#neo4j#ocr#onnx#rust#vector#wasm RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in. https://github.com/ruvnet/ruvector

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#rust #ai #ai_ocr #attention_mechanism #gnn #gnn_model #gnns #graph #graph_neural_networks #llm_inference #low_latency #mincut #neo4j #ocr #onnx #vector #wasm

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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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#pygotham #async #coroutines