3 Powerful Applications Using Streamlit: A Comprehensive Tutorial

Creating Your Own Web Application with GPT-3

Are you ready to whip up some AI magic? In this tutorial, we'll guide you through the steps of crafting your very own web application powered by the impressive GPT-3 from OpenAI. Using Streamlit, Python, and GitHub, you'll learn the essentials of launching a GPT-3-powered application. This tutorial is perfect for those with a basic understanding of Python, so let's get started!

Understanding GPT-3

GPT-3, or Generative Pre-trained Transformer 3, is a powerful AI text generator developed by OpenAI. With a staggering 175 billion parameters, it can generate coherent and contextually relevant text based on the input it receives.

Step 1: Getting Your OpenAI API Key

The first step is to get your OpenAI API key. You can obtain one by signing up at OpenAI's website. After creating your account, navigate to your profile and select the "API Keys" tab. Alternatively, you can follow this link to manage your OpenAI API Keys.

Step 2: Clone the GPT-3 Boilerplate from GitHub

Next, we'll use a GPT-3 boilerplate that simplifies the process of building your application. You can copy this repository: GPT-3-Boilerplate onto your local machine and add it to your own repositories. This boilerplate will help you build a GPT-3 powered application in just 20 minutes!

Step 3: Running the Project Locally

Follow these steps to run the project locally:

1. Navigate to your project folder and create a virtual environment of your choice. Use the venv documentation for guidance.
2. Activate the virtual environment by running the command: ./venv/Scripts/activate
3. Install the necessary dependencies using the command: pip install -r requirements.txt
4. Finally, run the application with: streamlit run gpt_app.py. The application will open in a browser window where you can input your API key.

About the Boilerplate Application

The boilerplate application is a poem generator that creates a poem based on your input words. It utilizes the text-davinci-002 model from OpenAI, which you can find in the model.py file. Feel free to experiment with different model parameters or even change the entire prompt to customize the poem generation process.

Step 4: Deploying the Application on Streamlit

To deploy your application, follow these steps:

1. Visit Streamlit Sharing and register for an account.
2. Click on "New app".
3. Select your repository, choose the branch name, and specify the main file path (e.g., gpt_app.py).
4. Click on "Deploy!" and your application will be live!

Conclusion

Congratulations on building and deploying your GPT-3 powered application! With the power of OpenAI and a little bit of Python, you’ve created an impressive piece of technology that can generate poetry or any text you desire. Continue to experiment and enhance your understanding of AI and web development!