Making an application using OpenAI and Streamlit

In software development, the convergence of advanced AI technologies and user-friendly frameworks has sparked a revolution in application development. OpenAI, a leading organization in artificial intelligence research, and Streamlit, a powerful framework for building data-driven web applications, have emerged as dynamic tools that empower developers to create innovative and interactive applications.

The power of OpenAI

With the goal of ensuring that artificial general intelligence (AGI) benefits all people, OpenAI is at the forefront of artificial intelligence research. OpenAI has created cutting-edge models for image identification, natural language processing, and other applications through its innovative research and development initiatives. These models are enormously beneficial for application development because they have proven to be exceptionally adept at comprehending and producing text that resembles that of a human, such as the GPT (Generative Pre-trained Transformer) series.

Streamlit: A user-friendly framework

Streamlit, on the other hand, provides a streamlined framework for building web applications with Python. Its simplicity and ease of use allow developers to focus on creating engaging user experiences without getting bogged down by the complexities of web development. With Streamlit, developers can effortlessly transform their Python scripts into interactive web apps, complete with widgets, plots, and other components.

Combining OpenAI and Streamlit

Combining OpenAI and Streamlit enables developers to create applications that leverage the power of AI while maintaining a user-friendly interface. Here’s how you can embark on the journey of building an application using these two technologies:

Defining the problem: Begin by identifying the problem you want to solve or the task you want your application to perform. Whether it’s text generation, image classification, or data analysis, clarifying the objectives of your application is crucial for the development process.
Choosing the OpenAI model: Select the appropriate OpenAI model that aligns with your application requirements. For text-based applications, GPT models offer remarkable capabilities in natural language understanding and generation. For text-related tasks, models like GPT-3.5-turbo can be utilized.
Integrating OpenAI with Streamlit: Utilize Streamlit to create a user-friendly interface for your application. You can incorporate Streamlit widgets to allow users to input text, upload images, or interact with the application in various ways. Integrate the OpenAI model into your Streamlit application to perform the desired tasks, such as generating text based on user input or providing image analysis results.

Demo application

This Python code utilizes the Streamlit framework and OpenAI’s GPT-3 model to create a simple web application that generates product descriptions based on user input.

Note: Add your OpenAI key at line 5 in the placeholder: openai.api_key = "Your API key"

import streamlit as st
import openai


openai.api_key = "Your API key"


def generate_product_description(product_name, features, benefits):
    prompt = f"As an e-commerce business, you need a compelling product description for your new '{product_name}'. Here's a draft:\n\nProduct name: {product_name}\nFeatures: {features}\nBenefits: {benefits}\n\nDescription:"
    response = openai.Completion.create(
        engine="gpt-3.5-turbo-instruct",
        prompt=prompt,
        temperature=0.7,
        max_tokens=150,
        n=1,
        stop="\n"
    )
    description = response.choices[0].text.strip()
    return description


def main():
    st.title("E-commerce Product Description Generator")

    
    product_name = st.text_input("Enter the product name:")
    features = st.text_area("Enter the features of the product:")
    benefits = st.text_area("Enter the benefits of the product:")

    
    if st.button("Generate Description"):
        if product_name and features and benefits:
            with st.spinner("Generating Description..."):
                generated_description = generate_product_description(product_name, features, benefits)
            st.success("Description Generated Successfully!")
            st.write(generated_description)
        else:
            st.error("Please fill in all the fields.")

if __name__ == "__main__":
    main()

Application using OpenAI and Streamlit

Code explanation

Lines 1–2: We import the required libraries, streamlit and openai, to enable building the application and utilizing OpenAI’s services for text generation.
Line 5: We set the API key required to authenticate with OpenAI’s services. This key should be kept secure and not shared publicly.
Lines 8–19: def generate_product_description(product_name, features, benefits) defines a function called generate_product_description that takes the product name, features, and benefits as input parameters.
Lines 22–38: This function defines the user interface using Streamlit. It includes an input area for users to enter their prompt and a button to trigger text generation.
- It checks for the click event on the "Generate Description" button.
- It ensures all input fields are filled before generating the description.
- It calls the text generation function with user input to generate the product description.

Conclusion

Developers can create cutting-edge applications that push the limits of AI-driven technology by utilizing Streamlit and OpenAI together. With OpenAI’s sophisticated models and Streamlit’s intuitive architecture, developers can create intelligent and engaging applications for a wide range of tasks, including text generation, image analysis, and dataset exploration. Accept the ways that AI and web development work together and set out to create innovative applications.

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