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Source channel @githubtrending · Post #14808 · Jun 8

#rust#ai#ai_engineering#anthropic#artificial_intelligence#deep_learning#genai#generative_ai#gpt#large_language_models#llama#llm#llmops#llms#machine_learning#ml#ml_engineering#mlops#openai#python#rust TensorZero is a free, open-source tool that helps you build and improve large language model (LLM) applications by using real-world data and feedback. It gives you one simple API to connect with all major LLM providers, collects data from your app’s use, and lets you easily test and improve prompts, models, and strategies. You can see how your LLMs perform, compare different options, and make them smarter, faster, and cheaper over time—all while keeping your data private and under your control. This means you get better results with less effort and cost, and your apps keep improving as you use them[1][2][3]. https://github.com/tensorzero/tensorzero

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djangoproject

@djangoproject · Post #270 · 02/26/2017, 08:08 AM

https://www.obeythetestinggoat.com/testing-async-asyncio-and-performance.html #Testing, #async, #asyncio, and #performance Sun 27 December 2015 By Harry I recently did some experimenting with asyncio, and wanted to report back on how I got on with writing tests for it. While I was at it I was also able to compare its performance with a couple of other approaches to #mutlitasking in Python, namely #threads and #gevent, so I'll report on that here too. (tl;dr: it's much of a muchness).