Creating a Chat Bot with OpenAI GPT-3 Model

In this Tutorial, we will learn how to create a chat bot using the OpenAI GPT-3 model and integrate it within a Streamlit app. The chat bot will be able to generate responses based on user input and engage in conversations. We will walk through the process step by step, starting from setting up the API key to running the app locally. So, let's get started!

1. Introduction

Chat bots have become increasingly popular in various domains, from Customer Service to virtual assistants. They can provide Instant responses, answer questions, and engage users in Meaningful conversations. In this tutorial, we will leverage the power of the OpenAI GPT-3 model to create our Own Chat bot using the Streamlit framework.

2. Setting up the API Key

Before we begin, we need to set up the API key for using the OpenAI GPT-3 model. You can create your own API key by visiting the OpenAI website and following the instructions provided. It is important to note that there may be some usage restrictions and charges associated with the API key. It is advisable to use your own API key and use it responsibly.

3. Installing Dependencies

To create our chat bot, we need to install the necessary dependencies. We will be using OpenAI and Streamlit libraries for this purpose. You can install them using the pip Package manager.

pip install streamlit
pip install openai

4. Writing the Streamlit App

Now that we have set up our API key and installed the required dependencies, we can start writing the Streamlit app. The app will serve as the platform for our chat bot. We will begin by importing the necessary libraries.

import streamlit as st
import openai
from streamlit_chat import message

Next, we need to initialize our API key using the openai.API method. We will also define a function called generate_response that will interact with the API and generate responses based on user input.

openai.api_key = 'your-api-key'

def generate_response(prompt):
    completions = openai.Completion.create(
        engine='text-davinci-003',
        prompt=prompt,
        max_tokens=100,
        temperature=0.5
    )
    message = completions.choices[0].text
    return message

5. Storing Interaction with the Chat Bot

To enable the chat bot to remember the previous conversation, we will use the st.session_state feature provided by Streamlit. This allows us to store and retrieve values within a session. We will create a session state variable called past_conversation to store the past conversation between the user and the chat bot.

session_state = st.session_state.get('past_conversation', {'Prompt': '', 'past': []})
past_conversation = session_state['past']

6. Running the Chat Bot App

Finally, we can run our chat bot app using the Streamlit syntax. We will use the st.title method to display the title of the app.

st.title('Chat Bot')

Next, we will define the user input section where the user can interact with the chat bot.

user_input = st.text_input('User Input')

We will also add a button to submit the user input and generate a response from the chat bot.

if st.button('Submit'):
    past_conversation.append(user_input)
    session_state['past'] = past_conversation
    output = generate_response('\n'.join(past_conversation))
    st.write(f'Chat Bot: {output}')

7. Conclusion

In this tutorial, we have learned how to create a chat bot using the OpenAI GPT-3 model and integrate it within a Streamlit app. We have covered the steps from setting up the API key to running the app locally. With the chat bot, you can engage in conversations, ask questions, and get instant responses. Feel free to explore and modify the chat bot according to your requirements.

FAQ

Q: Can I use my own API key for the OpenAI GPT-3 model? A: Yes, it is recommended to use your own API key for better control over usage and charges.

Q: Are there any charges associated with using the OpenAI GPT-3 model? A: Yes, there may be charges associated with using the OpenAI GPT-3 model. It is advisable to refer to the official OpenAI documentation for more information on pricing.

Q: How can I make the chat bot more interactive? A: You can enhance the chat bot's interactivity by adding more prompts, customizing responses, and incorporating additional functionalities.

Q: Can I deploy the chat bot app to a live server? A: Yes, you can deploy the chat bot app to a live server by following the deployment instructions provided by Streamlit.

Q: Can I integrate the chat bot with other applications or platforms? A: Yes, you can integrate the chat bot with other applications or platforms by using the OpenAI API and appropriate integration methods.

Resources: