Build a ChatGPT-like App

Build a ChatGPT-like App

Table of Contents:

1. Introduction
2. Building a Conversational App Using OpenAI and Streamlit
3. Setting up the Environment
4. Importing the Required Libraries
5. Defining the Title of the App
6. Initializing the OpenAI Model
7. Storing User and Assistant Messages
8. Displaying Messages
9. Adding Chat History
10. Implementing the ChatBot UI
11. Integrating OpenAI Chatbot
12. Conclusion

Article:

Introduction

In this article, we will guide You through the process of building a conversational app using OpenAI and Streamlit. The release of OpenAI's conversational features in Streamlit has opened up new opportunities for developers to Create interactive and engaging chat apps. By following this tutorial, you will be able to build a simple chat app and integrate a chatbot powered by OpenAI's GPT models.

Building a Conversational App Using OpenAI and Streamlit

In this section, we will cover the step-by-step process of building a conversational app using OpenAI and Streamlit. We will begin by setting up the environment, importing the necessary libraries, and defining the title of the app. Then, we will initialize the OpenAI model and create a way to store user and assistant messages. Next, we will implement the chat history feature and display the messages on the app. Finally, we will integrate OpenAI's chatbot and create a user-friendly UI.

Setting up the Environment

Before we begin, make sure you have the necessary environment set up to build the conversational app. We recommend using VS Code and creating a new environment specifically for this project. Once you have set up the environment, you can proceed to the next step.

Importing the Required Libraries

To build the conversational app, we will need to import the necessary libraries. This includes OpenAI, Streamlit, and OS. These libraries will provide us with the tools and functionality needed to create an interactive chat app. Make sure you have these libraries installed before moving forward.

Defining the Title of the App

Every app needs a title. In this case, we will define the title of the app as "Simple Conversational App." This title will be displayed at the top of the app, giving users a clear understanding of what the app is all about.

Initializing the OpenAI Model

The Core of our chatbot functionality lies in the OpenAI model. We will initialize the OpenAI GPT-3.5 Turbo model to power our chatbot. By utilizing the power of GPT-3.5 Turbo, we can create a chatbot that can provide realistic and engaging responses to user input.

Storing User and Assistant Messages

To create a realistic chat experience, we need to store user and assistant messages. By storing these messages, we can display a chat history and create a Sense of continuity in the conversation. Using the provided code, we can append user and assistant messages to a list and store them for future reference.

Displaying Messages

Once we have stored the messages, we need to display them on the app. By using the provided code, we can create chat message containers that will display the messages from the user and the assistant. This will create a visually appealing and easy-to-follow chat interface for users.

Adding Chat History

To enhance the chat experience, we can add a chat history feature. This feature will allow users to view previous messages sent in the conversation. By utilizing a list to store the messages and appending them with each new message, we can create a comprehensive chat history that users can refer back to.

Implementing the Chatbot UI

Now that we have set up the basic functionality of the app, we can focus on creating an intuitive and user-friendly UI. By utilizing Streamlit's interactive widgets, we can create a chat input box where users can Type their messages. This input box will be connected to the chatbot functionality, allowing users to receive responses Based on their input.

Integrating OpenAI Chatbot

The final step in building our conversational app is integrating the OpenAI chatbot. By utilizing the OpenAI API, we can send user messages to the chatbot and receive responses. By following the provided code, we can establish a connection between the user input and the OpenAI chatbot, allowing for a seamless and natural conversation.

Conclusion

In conclusion, building a conversational app using OpenAI and Streamlit opens up exciting possibilities in the field of chatbot development. By following this tutorial, you can create your own interactive and engaging chat app powered by OpenAI's GPT models. Remember to experiment with different models and features to enhance the functionality of your app. Get started today and embrace the world of conversational AI.