Learn how to Create an LLM ChatBot with Gradio UI – Part 2 Tutorial

Introduction

In the first part of this tutorial series, we learned about building a Q&A bot using an open-source language model. In this second part, we will be focusing on building a chatbot UI using Radio application, which can be used to interact with the bot.

If you have not seen the first part, we encourage you to watch it for a better understanding of the chatbot’s workings.

Building the Chatbot UI Using Gradio

To get started, we need to create a UI with Gradio. Gradio is a simple UI that can be used to interact with machine learning models. You can start by downloading the Gradio library and installing it using the following command:

pip install gradio

Once installed, we can create the UI for our chatbot using Python. We can use Google Collab to demonstrate how to create the chatbot UI.

To do this, we need two core functions: “build the bot” and “chat”.

import gradio as gr

def build_bot(input_text):
    # code to build lambda index document and GPT simple vector index

def chat(input_text):
   # code to query the index and generate a bot response 

The “build the bot” function will use the input text to build a lambda index document and a GPT simple vector index. The “chat” function will use the chat history and user input to query the index and generate a bot response with streaming response capability.

Using Gradio, we can define the input and output of the chatbot UI. The input can be a text box where users can enter their questions, and the output can be a text box where the bot’s response is displayed.

# create the chatbot UI
chatbot_interface = gr.Interface(fn=chat, inputs="text", outputs="text")

# launch the chatbot UI
chatbot_interface.launch()

Demonstrating the Chatbot’s Ability to Answer Questions on Ashton Kutcher

To demonstrate the chatbot’s ability to answer questions, we can use a dataset of questions and answers about Ashton Kutcher. We can train our language model on this dataset and use it to generate responses to user queries.

Here are a few examples:

• User: “Who is Ashton Kutcher?”
  Chatbot: “Ashton Kutcher is an American actor, producer, and entrepreneur.”

• User: “What is Ashton Kutcher’s net worth?”
  Chatbot: “Ashton Kutcher’s net worth is estimated to be around $200 million.”

Conclusion

We hope that this tutorial has helped you to create a chatbot UI using Gradio and understand how it can be used to interact with a language model.

Remember to use the “build the bot” and “chat” functions to create an index for your language model and generate responses to user queries. And don’t forget to check out the first part of this tutorial series if you haven’t already!

FAQs

1. What is Gradio?
   Gradio is a simple UI that can be used to interact with machine learning models.

2. What are the core functions needed to build a chatbot using Gradio?
   The two core functions needed are “build the bot” and “chat”.

3. How do I install Gradio?
   You can install Gradio using the following command: pip install gradio

4. Can Gradio be used to build a chatbot UI?
   Yes, Gradio can be used to build a chatbot UI.

5. What is the benefit of using Gradio to build a chatbot UI?
   Gradio provides a simple and intuitive UI for users to interact with, making the chatbot experience more user-friendly.