> For the complete documentation index, see [llms.txt](https://ray-evolv.gitbook.io/ray_evolv-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ray-evolv.gitbook.io/ray_evolv-docs/systems/nora.md).

# 对话操作体系

对话是调用 Evolv 功能的共同入口。你不用先记住所有页面和按钮，先说目标，Nora 再结合当前对象与已有资料决定怎样完成。

## 三类请求，三种处理

| 你说什么                    | Nora 怎样处理           | 结果在哪里        |
| ----------------------- | ------------------- | ------------ |
| “我还有多少待投资金？”            | 查询现有记录，解释组成         | 会话结果与资金概览    |
| “把这笔买入记一下，金额改成五百。”      | 整理或修正候选，需要时补问，交给你核对 | 确认卡及正式交易     |
| “研究这个问题，重点看成本，别展开个股推荐。” | 发起研究，明确需求与大纲        | 研究任务、报告和后续讨论 |

普通查询不必变成确认卡；草稿只是准备；研究按自己的审批流程推进。关键是理解请求与当前状态，而不是要求你背固定口令。

## 连续说，不必每次从头来

可以接着说“还是改成三个月”“只改金额，其他照旧”，沿用当前对象和已知信息。涉及多件事时，Nora 会处理已有条件的部分，并在依赖真实结果或必要确认时继续衔接。

报告中的选文、当前基金、手动提供的图片和过去讨论，都可以成为这次提问的背景。切换内置与桌面形态仍是同一个会话伙伴。

## 对话与页面配合

页面负责清楚地展示结果、提供细致核对和管理。批量交易逐行校正、部分已存在记录的修改删除、凭据和权限设置仍在相应页面完成；Nora 可以解释和带你进入，不把未执行说成完成。

[场景教程](/ray_evolv-docs/scenes.md) · [提问与图片](/ray_evolv-docs/systems/nora/nora-ask.md) · [操作卡](/ray_evolv-docs/systems/nora/nora-cards.md) · [历史会话与分叉](/ray_evolv-docs/systems/nora/nora-history.md) · [桌面宠物与陪伴](/ray_evolv-docs/pet.md)

***

返回[整体结构与功能体系](/ray_evolv-docs/systems.md) · [认识 Evolv](/ray_evolv-docs/home.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://ray-evolv.gitbook.io/ray_evolv-docs/systems/nora.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.