How to Create Chatbots
In this tutorial, we'll walk you through creating a chatbot using Xircuits, utilizing the converse
component library. This step-by-step guide is beginner-friendly and aimed at helping you launch your own AI chatbot on the platform.
For a quicker start, you can use the Simple Chat Bot
project template which comes with a pre-configured workflow ready for deployment.
Step 1: Open a New Xircuits File
Start by opening the Xircuits interface within the Xpress AI Agent Studio. If this is your first time with Xircuits, take a moment to check out the Getting Started section in the Xircuits guide for an overview.
Step 2: Utilize the Converse Library
The converse
component library is essential for creating chatbots. To get started, we suggest using the provided example workflow. Right-click the converse
library in the component sidebar and select Show Example
Step 3: Copy the Workflow File to the Base Directory
To ensure your new chatbot is recognized by the platform, the workflow file must reside in the base working directory. You can manually move the file or use the right-click context menu Copy to Root Directory
option.
Step 4: Customize Your Workflow
Now that you have the example workflow, it's time to make it your own. Customize it by dragging and dropping components, connecting them, and adjusting their properties to shape your chatbot's behavior and responses.
Step 5: Deploy Your Chatbot
Your chatbot is now running!
Step 6: Interact with Your Chatbot
It's time to start the conversation. Test its responses using the chat interface and refine its capabilities as you go.
Congratulations! You've taken your first steps into the world of chatbot creation with Xircuits. As you become more comfortable with the platform and its components, you'll discover the potential to craft increasingly sophisticated and personalized chatbots.
You might be wondering why we're focusing on chatbots and not agents. The key difference is that chatbots are designed to respond with text, making them ideal for conversations.
Agents, on the other hand, are built to perform actions. We'll explore agents and their capabilities in another tutorial, expanding your toolkit for creating dynamic AI solutions.