2. 将元素均匀分配到对应桶中
SelectWhat's included
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Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.，推荐阅读safew官方下载获取更多信息
The web project is intended to contain the code for actually running the service in Azure. Controller actions that act as the entry point for individual HTTP requests. Service startup code preparing the IoC container. Various middlewares providing additional telemetry and debugging information. And so forth.