One by-product of weighing the candidates by their distance is that the resulting output image is prone to false contours or banding. Increasing reduces this effect at the cost of added granularity or high frequency noise due to the introduction of ever more distant colours to the set. I recommend taking a look at the original paper if you’re interested in learning a bit more about the algorithm[1].
Фото: Ramil Sitdikov / Pool / Reuters
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But that’s a lot of resetting! We can save a bunch of bandwidth by instead tracking the current foreground and background color in our renderer and only emitting a new color escape sequence when our desired color changes. This is an annoying amount of bookkeeping but it substantially cuts down on the amount of escape codes emitted.，更多细节参见旺商聊官方下载
I then added a few more personal preferences and suggested tools from my previous failures working with agents in Python: use uv and .venv instead of the base Python installation, use polars instead of pandas for data manipulation, only store secrets/API keys/passwords in .env while ensuring .env is in .gitignore, etc. Most of these constraints don’t tell the agent what to do, but how to do it. In general, adding a rule to my AGENTS.md whenever I encounter a fundamental behavior I don’t like has been very effective. For example, agents love using unnecessary emoji which I hate, so I added a rule:
Автор подчеркнул, что США больше не сражаются с противниками, которые не могут противостоять американским кораблям. При этом потенциальные противники вроде России или Китая обладают средствами для эффективного поражения плавучих авиабаз.