> For the complete documentation index, see [llms.txt](https://omira-documentations.gitbook.io/omira-documentations/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://omira-documentations.gitbook.io/omira-documentations/0.07-agent-model/introduction.md).

# Introduction

Omira’s 0.07 model is an AI Agent trained by Omira Labs’ with direct access to both the B.B4 & B.B4-dL price prediction models. Acting as your personalized trading assistant, 0.07 adapts itself to your individual profile as a trader - taking into account things such as your risk tolerance, trade frequency, and overall trading habits.

0.07 is designed to provide customized assistance to enhance your trading strategy. Whether it’s recommending portfolio rebalancing approaches, buy/sell quantities, take-profit or DCA strategies, or ideal entry and exit points, Omira 0.07 provides insights and recommendations tailored to you and no one else.

Designed to be useful for both long term investors and high frequency traders, Omira 0.07 can interpret potential market reactions to a variety of events and trends using data-based simulations. For instance, users might ask how a major catalyst or a surge in community activity could impact the price of an asset.

Personalized insights provided by 0.07 are immediately actionable by the agent, should approval be given by the user. For example, a suggested DCA maneuver may be automatically executed by 0.07 should the user give wallet approval. This allows users to take advantage of optimal entry and exit strategies with a single click.

Omira’s 0.07 model is conveniently accessible via both Omira’s web application and Telegram interface.


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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://omira-documentations.gitbook.io/omira-documentations/0.07-agent-model/introduction.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.