3 Powered Applications Using Streamlit: A Step-by-Step Tutorial

Unlocking the Power of AI: Creating Your Own GPT-3 Powered Web Application

Are you ready to embark on an exciting journey of building a web application with the remarkable capabilities of GPT-3 from OpenAI? In this comprehensive tutorial, we will guide you through the essential steps to launch your own AI-powered application using Python, Streamlit, and GitHub. Whether you're a seasoned developer or just starting with Python, this tutorial is designed to help you create an innovative web application in no time.

Getting Started: Obtain Your OpenAI API Key

The first step towards using GPT-3 is to obtain your OpenAI API key. Follow these simple steps:

1. Sign up for an account on OpenAI.
2. Once your account is created, navigate to your profile.
3. Click on the "API Keys" tab to generate your unique API key.

This API key will grant you access to the powerful capabilities of GPT-3.

Cloning the GPT-3 Boilerplate from GitHub

To simplify our development process, we will be utilizing a pre-built GPT-3 boilerplate. Here’s how to clone it:

1. Copy the GPT-3 Boilerplate repository onto your local machine.
2. Add it to your own GitHub repositories for future customization.

Running the Project Locally

Now that we have the boilerplate set up, let’s run our application locally. Follow these steps:

1. Navigate to your project folder and create a virtual environment using your preferred approach. For example, you can use the venv module.
2. Activate the virtual environment. If you used venv, run the command: ./venv/Scripts/activate
3. Install the necessary dependencies by executing: pip install -r requirements.txt
4. Start the application by running: streamlit run gpt_app.py

Your application will open in a new browser window. Don’t forget to input your API key!

Understanding the Boilerplate Application

The provided boilerplate features a poem generator that utilizes the text-davinci-002 model from OpenAI. You can find the model configuration in the model.py file. Feel free to explore the options:

• Change the model to any other of your choosing.
• Adjust model parameters, such as setting the temperature to 0.9 to generate more creative poems.
• Modify the prompt to customize the input for the poem generation.

Deploying the Application on Streamlit

To share your application with the world, it’s time to deploy it!

1. Visit Streamlit Share and create an account.
2. Click on New app.
3. Select your repository, enter the branch name, and specify the file path (for our case, gpt_app.py).
4. Click on Deploy! and watch your application come to life!

Conclusion: Your AI-Powered Adventure Awaits!

You've successfully set up and deployed your very own GPT-3 powered application! With the knowledge gained in this tutorial, you can continue to innovate and explore the full potential of AI technology. Don’t forget to engage with your users, analyze their feedback, and improve your application further. Happy coding!