app.py

# Import libraries
import gradio as gr
from transformers import pipeline

# Create a text generation pipeline with GPT-2
story_generator = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")

# Set the context for the storyteller
messages = [{"role": "system", "content": "You are a magical storyteller, creating wonderful tales for kids. Make them imaginative and full of joy!"}]

# Define the Storyteller function
def StorytellerGPT(tell_story):
    messages.append({"role": "user", "content": tell_story})
    
    # Generate story using Hugging Face's GPT-2
    story_reply = story_generator(tell_story, max_length=100, num_return_sequences=1)[0]['generated_text']
    
    messages.append({"role": "assistant", "content": story_reply})

    return story_reply

# Create the Gradio Interface
demo = gr.Interface(
    fn=StorytellerGPT,
    inputs="text",
    outputs="text",
    title="📖 Storytelling Magic",
    description="A magical storyteller app for kids! Type a sentence, and let the app create an enchanting story for you."
)

# Launch the Gradio Interface
demo.launch()