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.
{"user_content": "show alert saying hi", "tool_name": "show_alert", "tool_arguments": "{\"title\": \"Alert\", \"message\": \"hi\"}"}
。关于这个话题，safew官方版本下载提供了深入分析
通过技术突破和成本优势吸引用户，只要大模型足够好用，用户自然愿意买单；这又会反向推动模型和Agent能力的提升，吸引更多高付费意愿的专业客群，为商业化提供基础。
春节出游，我最推荐大家尝试「鲜艳」，能很好地还原春节集市上那些复杂的色彩，红色的对联、金色的福字、五彩的糖果，在 XMAGE 的加持下，会呈现出一种油润且厚重的质感，非常适合表现「热闹」这个主题。。Line官方版本下载是该领域的重要参考
Последние новости
Please keep in mind it’s more than OK to do nothing at all too!，详情可参考同城约会