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Agentverse UI

UI Overview

Once you create your Hosted Agent on Agentverse, you will see a box for it within the My Agents tab. By clicking on this box, you will open up the Agent Editor and you will be able to modify a bunch of details related to the Agent you created.

There are multiple tabs within the Editor:

1️⃣ Overview: It displays general information about the Agent, including its README file, description, and basic details.

2️⃣ Stats: It provides insights into the Agent’s interactions, ratings, and overall performance across the Marketplace.

3️⃣ Build: This is the Code Editor tab. It helps developers to modify or update the Agent’s configuration and code.

4️⃣ Deploy: This tab is dedicated to the Agent’s Functions and registration into the Agentverse so to make them discoverable by the AI Engine for interaction.

Considering the Code Editor window, there are some additional features available to help you setting up your Agents with ease:

Let’s unpack this:

1️⃣ Agent Secrets: This tab is used to manage environment variables and credentials securely (e.g., API keys stored in .env).

2️⃣ Agent Storage: This tab handles data storage for the Agent.

3️⃣ Agent Logs: This is the Agent’s Terminal. In here you can display execution logs, errors, and debugging information for troubleshooting.

Multi-file Support

The Agentverse Code Editor enhances your agent development experience with multi-file support, enabling you to tackle complex projects with ease. Leverage this feature to:

  • Interact between files: simply import functions, classes, and variables from one file to another.
  • Modular development: divide your projects into manageable components for streamlined creation.
  • Code reuse: utilize modules across various sections of your project for efficient development.
  • Enhanced organization: maintain a structured and organized codebase for easier maintenance.

If you want to create new files you just need to click on + New File on Agentverse inside your hosted Agent.

You can create a Python message file with the following Model class:

from uagents import Model
 
class Sentence(Model):
    text: str

Then, you can just import the Sentence data model to your agent.py file and make use of it:

from uagents import Context
from message import Sentence
 
@agent.on_interval(period=2.0)
async def print_message(ctx: Context):
    msg = Sentence(text=f"Hello there my wallet address is {ctx.wallet}.")
    print(msg.text)

For additional information on Agent Functions, head over to Agent Functions and Register Agent Functions ↗️ resources.

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