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import gradio as gr
from transformers import pipeline
from gtts import gTTS
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont
from IPython.display import Audio
# 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})
# Convert text to speech
tts = gTTS(text=story_reply, lang='en', slow=False)
audio_io = BytesIO()
tts.save(audio_io)
audio_io.seek(0)
# Convert text to image
image = generate_dynamic_image(story_reply)
return story_reply, Audio(data=audio_io.read(), autoplay=True), image
# Function to generate a dynamic image based on the story text
def generate_dynamic_image(story_text):
# Create a blank image
image = Image.new("RGB", (500, 300), (255, 255, 255))
draw = ImageDraw.Draw(image)
# Use a truetype font file, replace "arial.ttf" with the path to your font file
font = ImageFont.truetype("arial.ttf", 20)
# Write the story text on the image
lines = [story_text[i:i+40] for i in range(0, len(story_text), 40)]
y_position = 10
for line in lines:
draw.text((10, y_position), line, font=font, fill=(0, 0, 0))
y_position += 30
return image
# Create the Gradio Interface
demo = gr.Interface(
fn=StorytellerGPT,
inputs="text",
outputs=["text", "audio", "image"],
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()
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