app.py

import gradio as gr
from transformers import pipeline

# Initialize the text generation pipeline with a pre-trained model
text_generator = pipeline('text-generation', model='gpt2')  # You can use other models as well

def generate_text(prompt, max_length):
    # Generate text
    generated_text = text_generator(prompt, max_length=max_length, num_return_sequences=1)[0]['generated_text']
    return generated_text

# Define the Gradio interface
interface = gr.Interface(
    fn=generate_text,
    inputs=[
        gr.Textbox(label="Enter a prompt", placeholder="Type something..."),
        gr.Number(value=50, label="Max Length", precision=0, minimum=10, maximum=200)  # Using Number instead of Slider
    ],
    outputs="text",
    title="Text Generation with GPT-2",
    description="Generate text based on the provided prompt using the earliest version of ChatGPT. (Made By Nihal Gazi)"
)

# Launch the interface
interface.launch()