Configure Modules

This guide will help you to configure modules in the NYRA-Agent Playground.

Configure Modules

  1. To configure your agent, open the playground at localhost:3000.

  2. Choose a graph type (e.g., Voice Agent, Realtime Agent).

  3. Click the button next to the graph selection to open the module selection menu.

  4. Based on the selected graph type, choose the appropriate modules from the dropdown list.

  5. Click Save Changes to apply the selected module to the graph.

  6. If you see a success toast notification, the module has been successfully applied to the graph.

Available Modules

The following module types are available for the NYRA-Agent Playground:

Speech Recognition (STT)

The Speech Recognition module converts spoken language into text.

Text-to-Speech (TTS)

The Text-to-Speech module converts text into spoken language.

Large Language Model (LLM)

The Large Language Model module generates text based on the input text with influence.

Voice to Voice Model (V2V)

The Voice to Voice Model module generates voice based on the input voice with influence.

Tool (TOOL)

The Tool module provides a set of tools for the agent to use. The tools can be binded to LLM module or V2V module.

Blind Tool Modules

In the Nyra-Agent Playground, you can bind tool modules to LLM or V2V modules to extend the agent’s capabilities, such as adding weather checks, news updates, or other functionalities. You can also create custom tool extensions if necessary.

To configure your agent, open the playground at localhost:3000:

  1. Select a graph type (e.g., Voice Agent, Realtime Agent).

  2. Click the button next to the graph selection to open the module picker.

  3. Depending on the chosen graph type, you will see either LLM or V2V modules in the module selection.

  4. Click the button next to the module to open the tool selection menu.

  5. Select a tool from the available options to bind it to the selected module.

  6. Click Save Changes to apply the tool to the module.

  7. If a success toast appears, the tool has been successfully applied to the module.

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