> For the complete documentation index, see [llms.txt](https://docs.aisera.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aisera.com/aiseragpt/how-to-set-up-an-aiseragpt-bot/view-conversational-ai-policy.md).

# View Conversational AI Policy

If your bot uses the Conversational AI 2.0 option, the **View Policy** button is now called the View Conversational AI Policy button. The parameter on a 1.0 bot that was called, **Agent Persona Snippet** has been renamed to  **Agent Response Format Instructions** and allows you to specify instructions for the 2.0 bot response.

<div align="left"><figure><img src="/files/rqMBPW8t03YIzk6gaRAa" alt="" width="217"><figcaption><p>Conversational AI 2.0 View Policy</p></figcaption></figure></div>

The Aisera **Conversational AI** **2.0** bots support an app policy variable where custom instructions can be entered to fine tune the generated LLM output.&#x20;

These instructions can be appended to the standard generation prompt. This way, the change will not impact other bot behavior:

* It will not be lost if the app is switched to a different LLM
* It will not inadvertently impact other features or data
* Any product updates to the prompt will be applied correctly to the app (regardless of the customization)

### Agent Response Format

This variable allows you to provide  context and tone for the conversation.\
\
**Example App Policy** - Please keep the tone formal. Never use bold or italics formatting. If the context includes any instructions, provide your response in a step-by-step manner using bullet points.

<div align="left"><figure><img src="/files/TL5BckKxyX4gl6UAydQf" alt="" width="435"><figcaption></figcaption></figure></div>

### Show Images in KB Output

If your **Knowledge Base Articles** have images embedded in the content, then those images may be used in generated RAG responses that are sent to users on Webchat, Teams, or Slack channels.

<div align="left"><figure><img src="https://docs.aisera.com/~gitbook/image?url=https%3A%2F%2F2983236984-files.gitbook.io%2F%7E%2Ffiles%2Fv0%2Fb%2Fgitbook-x-prod.appspot.com%2Fo%2Fspaces%252FiZkLJr3EjXkd2tHYiQJP%252Fuploads%252Fk3rAAcOksFIlrgW27FXl%252F2.png%3Falt%3Dmedia&#x26;width=768&#x26;dpr=4&#x26;quality=100&#x26;sign=bbe5f5f8&#x26;sv=2" alt="" width="563"><figcaption></figcaption></figure></div>

If you do not wish to use images in generated answers, you can turn **OFF** this feature by unchecking the option. You might choose not to use images in your fulfillment answers if you find that images are not relevant to your application/bot users or if the image size changes the formatting in unexpected ways.

In addition to the **Agent Response Format** and **Show Images in KB Output,** you can set your application/bot to work with ontologies, detect user countries, address users with profile information, use strict validation, and show images from KB Articles when relevant.


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# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.aisera.com/aiseragpt/how-to-set-up-an-aiseragpt-bot/view-conversational-ai-policy.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
