Once the basic stuff was working, I wanted to load TAP files directly, simulating cassette loading. This was the first time the agent missed a few things, specifically about the timing the Spectrum loading routines expected, and here we are in the territory where LLMs start to perform less efficiently: they can’t easily run the SDL emulator and see the border changing as data is received and so forth. I asked Claude Code to do a refactoring so that zx_tick() could be called directly and was not part of zx_frame(), and to make zx_frame() a trivial wrapper. This way it was much simpler to sync EAR with what it expected, without callbacks or the wrong abstractions that it had implemented. After such change, a few minutes later the emulator could load a TAP file emulating the cassette without problems.
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FunctionGemma 是 Google 最小的函数调用专用模型——2.7 亿个参数，288 MB，解码速度约为 126 tok/s。没错，它需要微调（准确率从 58% 提升到 85%），没错，它使用了一种奇怪的自定义格式，而不是 JSON。但它适用于任何手机，响应速度极快，而且确实有效。现在就可以构建带有离线 AI 代理的应用——体积小、速度快、可靠性高，足以满足生产环境的需求。无需等待模型体积更小、设备速度更快的“神奇未来”，未来已来！
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