🧪 Testing Your Financial Analyst Agent Module

Note: This agent module demonstrates advanced concepts but will be broken down further before deployment. In the next course, we'll explore how to decompose this complex module into smaller agent modules that can execute tasks in parallel, coordinated by an agent orchestrator module for improved performance and scalability.

Understanding the Deployment Journey

When we develop AI agent modules with Naptha, we follow a progression from local testing to full production deployment. This journey ensures our agent performs reliably at each stage.

We can test our agent in a few different ways:

Test the module locally without the Naptha Node
Test the module on a local Naptha Node (with a local Hub)
Test the module on a hosted Naptha Node (with the hosted Naptha Hub)

This progression helps us catch issues early when they're easier to fix, just like how financial analysts practice with historical data before making real recommendations.

1. Local Development - Testing without a Naptha Node

You can test your agent directly by running the CLI command below:

This will run the module locally and output the results to the console.

Since we enabled verbose mode i.e verbose=True, you'll see detailed console output for each agent's execution.

Sample CLI output:

Note: This agent module demonstrates advanced concepts but will be broken down further before deployment. In the next course, we'll explore how to break this complex module into smaller agent modules that can execute tasks in parallel, coordinated by an agent orchestrator module for improved performance and scalability.