# Creating your first Agent

*Prerequisites: Up and Running instance of **EDDI** (see:* [*Getting started*](/getting-started/getting-started.md)*)*

## How does it work?

In order to build an Agent with **EDDI**, you will have to create a few configuration files and `POST` them to the corresponding REST APIs.

![](/files/-M69UTDQDilb54yzlw-1)

A agent can consists of the following elements:

1. (Regular) **`Dictionary`** to define the inputs from the users as well as their meanings in respective categories, expressed by a expression language `e.g. apple -> fruit(apple)`
2. **`Behavior Rules`** triggering **actions** based on execution of behavior rules checking on certain conditions within the current conversation
3. **`Http Connector`** requests/sends data to a Rest API and makes the json response available within the conversation (e.g for Output\*\*`)`\*\*
4. **`Output`** to answer the user's request based on **actions** triggered by behavior rules
5. **`Workflow`** to define which **\`LifecycleTasks**\` (such as the parser, behavior rules, rest api connector, output generation, ...) should be executed in order by how they are defined
6. **`Agent`** to define which packages should be executed in this agent

### Example of a resource reference

`eddi://ai.labs.regulardictionary/regulardictionarystore/regulardictionaries/ID?version=VERSION`

`eddi://` URI resources starting with this protocol are to be related with in EDDI

`ai.labs.regulardictionary` Type of resource

`/regulardictionarystore/regulardictionaries` API path

`ID` ID of the resources

`VERSION` Read-only version of the resource (each change is a new version)

Version of this resource (each update operation will create a new version of the resource)


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# Agent Instructions: 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:

```
GET https://docs.labs.ai/getting-started/creating-your-first-agent.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.