问HN：你是如何让大型语言模型生成优质代码的？
最近，我想看看能否让这个机器人帮助我整理我的音乐收藏。具体来说，我希望它编写一个Python函数，该函数接受一首歌曲的音频文件路径，并返回该歌曲的首张专辑（即规范专辑）的名称。如果忽略重制版、现场录音、盗版等，这实际上是一个简单的启发式映射：例如，《Smoke on the Water》对应《Machine Head》，《Come as You Are》对应《Nevermind》，《Fools Gold》对应《The Stone Roses》。
我可以快速使用MusicBrainz API编写这个函数，我相信其他许多HN的读者也可以。然而，经过许多个小时的尝试，无论我如何提示机器人，我都无法让它完成这个任务。这是ChatGPT生成的内容——其他机器人也给出了类似的无用回复：
https://chatgpt.com/share/6a396ea9-44d4-83eb-bdfd-216dfcc87e99
它们抱怨问题模糊（其实并不模糊）或MusicBrainz没有数据（实际上是有的）。我是在错误地提示机器人，还是没有使用足够强大的编码模型？结果让我感到非常失望。
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Lately, I wanted to see if I could get the bot to help me organize my music collection. Specifically, I want it to code a Python function that takes the path to an audio file of a song and returns the name of the canonical (i.e., first) album of that song. If one ignores remasters, live recordings, bootlegs, etc., this is an easy heuristic surjective mapping: Smoke on the Water -> Machine Head, Come as You Are -> Nevermind, Fools Gold -> The Stone Roses.<p>I can code this function quickly using the MusicBrainz API and I believe most other HN readers can too. Yet many hours later, no matter how I prompt the bot I can't get it to do it. This is what ChatGPT generates---other bots reply with similar garbage:<p>https://chatgpt.com/share/6a396ea9-44d4-83eb-bdfd-216dfcc87e99<p>They complain about how the problem is ambiguous (is not) or how MusicBrainz doesn't have the data (it does). Am I prompting the bot incorrectly or not using powerful enough coding models? The results are very underwhelming.