import streamlit as st
from transformers import pipeline
from PIL import Image

# Creates a brief description of a picture using a smart model
def generate_caption(image):
    with st.spinner("🔍 Looking at your picture..."):
        # Loads the BLIP model to examine and describe the picture
        image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
        caption = image_to_text(image)[0]["generated_text"]
    return caption

# Builds a story from the picture’s description
def generate_story(caption):
    with st.spinner("✍️ Writing a fun story..."):
        # Uses a story model to craft a tale from the description
        pipe = pipeline("text-generation", model="pranavpsv/genre-story-generator-v2")
        story = pipe(caption)[0]['generated_text']
    return story

# Turns the story into spoken audio
def generate_audio(story):
    with st.spinner("🎙️ Turning story into audio..."):
        # Uses a speech model to read the story aloud
        pipe = pipeline("text-to-speech", model="facebook/mms-tts-eng")
        audio = pipe(story)
    return audio

# Streamlit UI: Makes a simple interface for kids to enjoy stories

# Displays a fun title
st.title("Picture to Story Fun! 🌈")

# Describes the app for young users
st.write("Hi, kids! Share a picture to get a fun story! Great for ages 3-10.")

# Allows picture uploads
uploaded_file = st.file_uploader("Pick a picture!", type=["png", "jpg", "jpeg"])

if uploaded_file is not None:
    # Shows the uploaded picture
    image = Image.open(uploaded_file)
    st.image(image, caption="Your Picture!", use_container_width=True)
    
    # Gets the picture’s description
    image_caption = generate_caption(image)
    st.subheader("Picture Description:")
    st.write(image_caption)

    # Creates a story
    story_telling = generate_story(image_caption)
    st.subheader("Your Story:")
    st.write(story_telling)

    # Generates audio
    audio = generate_audio(story_telling)
    if st.button("Hear Story!"):
        st.audio(audio['audio'], 
                 format="audio/wav", 
                 start_time=0, 
                 sample_rate=audio['sampling_rate'])