> For the complete documentation index, see [llms.txt](https://docs.labs.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.labs.ai/getting-started/creating-your-first-agent.md).

# 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.

An **Agent** points at one or more **Workflows**, and each Workflow lists the lifecycle steps to run in order. Every step reads its own JSON configuration, so what the agent *does* lives in configuration rather than in code:

```mermaid
flowchart TD
    subgraph cfg ["What you POST (JSON configuration)"]
        direction LR
        A["Agent"] --> W["Workflow<br/><i>which steps, in what order</i>"]
        W --> D["Dictionary"]
        W --> B["Behavior Rules"]
        W --> H["Http Connector"]
        W --> O["Output"]
    end

    subgraph run ["What happens on every user message"]
        direction TB
        I["User input"] --> P["Parser<br/><i>text → expressions</i>"]
        P --> R["Behavior Rules<br/><i>conditions → actions</i>"]
        R --> C["Http Connector<br/><i>call an API</i>"]
        R --> G["Output Generation<br/><i>pick a reply</i>"]
        C --> G
        G --> Resp["Reply to the user"]
    end

    D -.configures.-> P
    B -.configures.-> R
    H -.configures.-> C
    O -.configures.-> G
```

The **actions** emitted by Behavior Rules are the whole orchestration mechanism: steps never call each other directly, they just react to actions. That is why adding a capability usually means adding a rule and an output, not writing Java.

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.dictionary/dictionarystore/dictionaries/ID?version=VERSION`

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

`ai.labs.dictionary` Type of resource

`/dictionarystore/dictionaries` 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)