app.py

import streamlit as st
from transformers import pipeline

# Load Hugging Face pipelines
text_generator = pipeline("text-generation")
text_to_speech = pipeline("text-to-speech")
text_to_image = pipeline("text2image")

# Streamlit app
st.title("Children's Storytelling App")

# Input prompt for story
story_prompt = st.text_area("Write the beginning of your story:")

# Generate story button
if st.button("Generate Story"):
    if story_prompt:
        # Generate text
        generated_story = text_generator(story_prompt, max_length=100, num_return_sequences=1)
        st.write("Here's your story:")
        st.write(generated_story[0]["generated_text"])
    else:
        st.warning("Please enter a story prompt.")

# Text-to-speech button
if st.button("Text to Speech"):
    if story_prompt:
        # Convert text to speech
        st.audio(text_to_speech(story_prompt)[0]["audio"], format="audio/wav")
    else:
        st.warning("Please enter a story prompt.")

# Text-to-text button
if st.button("Text to Text"):
    if story_prompt:
        # Convert text to a different text
        transformed_text = text_to_image(story_prompt)[0]["generated_text"]
        st.write("Transformed text:")
        st.write(transformed_text)
    else:
        st.warning("Please enter a story prompt.")

# Text-to-image
st.sidebar.title("Text to Image")
image_prompt = st.sidebar.text_area("Enter text for image:")
if st.sidebar.button("Generate Image"):
    if image_prompt:
        # Convert text to image
        image = text_to_image(image_prompt)[0]["image"]
        st.sidebar.image(image, caption="Generated Image", use_column_width=True)
    else:
        st.sidebar.warning("Please enter text for the image.")