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Show HN:为你的 AI agent 提供屏幕引导,告诉用户该点击哪里

Show HN: Give your AI agent on-screen guides that show users where to click

· 34天前
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嗨,HN。我是 Christian,Frigade(YC W23)的联合创始人之一。我注意到,许多应用内 AI agent 很难真正理解它们所在的产品。 例如,假设用户询问 agent 如何在某个 SaaS 产品中完成某项操作。理想情况下,agent 可能会回复说它有一个工具可以完成这项任务,然后直接替用户自动完成整个操作。这无疑是很好的结果。 但很多时候情况并非如此。可能没有针对该确切任务的工具调用,或者用户的问题最好通过特定的 UI 工作流或界面来解决。在这些情况下,许多 agent 往往会退回到对帮助中心进行基础 RAG,有时甚至会搜索互联网,以了解它们自己的产品。这一过程可能非常缓慢,而且如今产品迭代速度往往快于帮助中心文章的更新速度,因此这些文章大多数时候都已经过时。更糟糕的是,没有人喜欢阅读一长串项目符号列表,然后再将其对应到 UI 上。 我的工具(Assist API)通过一次工具调用解决了这一空缺,定义如下: const frigade_guide_tool = { description: 'Call this tool to answer product questions or guide the user through a task.', parameters: { query: { type: 'string', description: 'What the user is asking or wants to do', }, }, run: ({ query }) => frigade.assist({ query }), } 这是我录制的一个演示,介绍如何使用 Vercel AI SDK 进行设置: https://www.youtube.com/watch?v=9WQ0UbLjC6I 调用后,该工具会执行以下操作: 1)收集用户在屏幕上看到的内容、用户权限、功能标志等上下文信息。然后执行以下某一项操作: 2a)如果问题可以解决:生成屏幕引导,指导用户如何解决给定问题 2b)如果是概念性问题:返回文本,向父 agent 说明如何解决问题 2c)拒绝(即无法提供帮助) 该工具如何知道该做什么? 该工具通过浏览器 agent 学习给定应用的 UI。你需要为自己的软件提供一个测试账户(即 staging 或 preview 环境),然后浏览器 agent 会登录并遍历整个产品。之后,它会建立自己的应用工作方式地图,可以据此回答任何与产品相关的问题,或说明如何在 UI 中从 A 进入 B。它还会根据这张地图自行编写文档。该 agent 会按计划重新运行,也可以通过 CI/CD 触发。 文档及更多详情: https://frigade.com/assist-api 评论 URL: https://news.ycombinator.com/item?id=49627872 得分:5 评论数:0

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Show HN: Give your AI agent on-screen guides that show users where to click
5 points by pancomplex 1 hour ago | hide | past | favorite | discuss
Hey HN. I'm Christian, one of the founders of Frigade (YC W23). I've noticed that a lot of in-app AI agents struggle to actually understand the products they exist in.

For instance, let's say a user asks an agent how to do something in a given SaaS product. In an ideal case, maybe that agent replies saying it has a tool to do the task and just automates that work entirely for the user. That's a great outcome.

But often that's not the case. Maybe there is no tool call for that exact task, or maybe the user's question is best solved by a specific UI workflow or interface. In these cases, many agents tend to fall back on basic RAG on their help center, or sometimes even searching the internet for an understanding of their own product. This can be a very slow process and most of the time help center articles are outdated as products evolve faster than them today. Even worse, no one likes reading a long list of bullets and mapping that back to a UI.

My tool (Assist API) solves this gap with a single tool call defined like this:

  const frigade_guide_tool = {
    description: 'Call this tool to answer product questions or guide the user through a task.',
    parameters: {
      query: {
        type: 'string',
        description: 'What the user is asking or wants to do',
      },
    },
    run: ({ query }) => frigade.assist({ query }),
  }
Here's a demo I recorded on how to set it up with the Vercel AI SDK: https://www.youtube.com/watch?v=9WQ0UbLjC6I

When called, the tool will do the following:

1) Gather context on what the user is seeing on screen, their permissions, feature flags, and more. Then one of the following:

2a) If solvable: Generate an on screen guide for how to fix a given problem

2b) If conceptual: Return text describing to the parent agent how to solve the problem

2c) Reject (i.e. unable to help)

How does the tool know what to do?

The tool learns a given application UI by using a browser-based agent. You provide a test account to your software (i.e. staging og preview), and a browser agent logs in and works its way through the entire product. It then builds its own map of how the application works which can the be queried about any product-related question or how to get from A to B in the UI. It also writes its own documentation from this map. The agent re-runs on a schedule or can be triggered through CI/CD.

Docs and more details: https://frigade.com/assist-api





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