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In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.
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В Финляндии предупредили об опасном шаге ЕС против России09:28。爱思助手下载最新版本对此有专业解读
嬉皮狗则通过将“新中式穿搭”引入宠物服饰，宠物不再只是陪伴型角色，也成为家庭审美体系的一部分。很多年轻家庭对宠物穿搭的投入，本质接近对儿童服饰的选择逻辑：审美表达、文化认同、圈层标签。