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Guide: Creating an AI-powered web app


Guide: Creating an AI-powered web app

In today’s digital age, the fusion of AI and app development empowers even beginners to craft innovative solutions with minimal coding. If you’re fascinated by the prospects of integrating AI into applications and unsure where to start, you’re in the right place. This guide will walk you through creating a simple app using Streamlit for the web interface and OpenAI to add intelligence. Streamlit is a python framework that helps us easily transform our data and machine learning projects into interactive web applications, without requiring extensive coding knowledge. We’ll develop an application that leverages OpenAI’s powerful models for answering questions based on a given text. Let’s embark on this coding journey.

Introduction to Streamlit and OpenAI

Before diving into coding, so let’s briefly understand the tools we’re about to use:

  • Streamlit is an open-source app framework designed for Machine Learning and Data Science projects. It allows you to turn data scripts into shareable web apps in minutes, with minimal coding.
  • OpenAI offers cutting-edge AI models like GPT-3, which can understand and generate natural language. Through the OpenAI API, you can easily integrate these models into applications.


  • Basic understanding of Python
  • An OpenAI API key (you can obtain one by signing up on their platform)

How to start :

Below are the steps to Integrate the OpenAI in the Streamlit web application.

  • Step 1: Setting Up Your Environment

    1. Install Streamlit: If you haven’t already, you need to install Streamlit. Open your terminal or command prompt and run:
      pip install openai
      pip install streamlit
    2. Get OpenAI API Key: Ensure you have your OpenAI API key ready. Securely store this key, as you’ll need it to authenticate your API requests.
  • Step 2: Creating Your Streamlit App

    • Create a Python file: Start by creating a new Python file for your project (e.g.,
    • Import Streamlit: At the top of your, import Streamlit along with any other necessary packages:
      import streamlit as st
      from openai import OpenAI# Initialize your OpenAI object with your API key
      open_ai = OpenAI(api_key="YOUR_API_KEY")


    • Designing Your App Interface: Streamlit makes it incredibly simple to create an interactive web interface. Here’s an example to create a basic interface that takes user input:
      # Set the title of your app 
      st.title('AI Content Generator with OpenAI')
      # Create a text input box 
      user_input = st.text_input("Enter your text here", "Type Here") 
      # Create a button that generates the response 
      if st.button('Generate'): 
          response = generate_response(user_input) 
          st.text_area("AI Response:", value=response, height=200)


  • Integrating OpenAI: Now, let’s define a function that communicates with OpenAI’s API to generate responses based on the input:
    # Define a function to get a response from the selected model for a given user input 
    def generate_response(user_input): 
        # Request a chat completion from the OpenAI API 
        chat_completion = 
                {"role": "user", 
                 "content": user_input,
                 }, ], 
            model='gpt-3.5-turbo' ) 
        # Check if a response is received 
        if chat_completion: 
            # Extract the content of the response 
            response = chat_completion.choices[0].message.content 
            # Return the response 
            return response
            # Display an error message in Streamlit and return an error response 
            return "Error getting a response."


  • Step 3: Running Your App

Once you have everything set up, it’s time to run your app. To run the application, navigate to your project directory in the terminal and execute:

streamlit run
streamlit run


Streamlit will start a local web server and open your default web browser to display your app. Congratulations, you’ve just created an AI-powered web app!


output of OpenAI we application using Streamlit


You’ve taken your first steps into the exciting world of AI-powered web apps. With Streamlit and OpenAI, you can transform your ideas into interactive AI web apps with ease. Moreover, remember, this is just the beginning. Both platforms offer extensive documentation and features to explore. Keep experimenting and learning to build more complex and impactful applications.

Happy coding!


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Akshay Mokalwar

Akshay Mokalwar works as ETL Developer at Perficient in the Nagpur GDC, India. Akshay is passionate about exploring new technologies. He understands technologies like PySpark, Python, Django, HTML, CSS, Bootstrap, JavaScript, web development, Big Data, Databricks, Machine Learning, SQL, and AWS services.

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