Delete app.py

app.py

@@ -1,196 +0,0 @@
-import streamlit as st
-from PIL import Image
-import io
-import torch
-from transformers import BlipProcessor, BlipForConditionalGeneration, pipeline
-from gtts import gTTS
-import os
-import base64
-import time
-
-# Set page configuration
-st.set_page_config(
-    page_title="Storyteller for Kids",
-    page_icon="📚",
-    layout="centered"
-)
-
-# Custom CSS
-st.markdown("""
-<style>
-    .main {
-        background-color: #f5f7ff;
-    }
-    .stTitle {
-        color: #3366cc;
-        font-family: 'Comic Sans MS', cursive;
-    }
-    .stHeader {
-        font-family: 'Comic Sans MS', cursive;
-    }
-    .stImage {
-        border-radius: 15px;
-        box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
-    }
-    .story-container {
-        background-color: #e6f2ff;
-        padding: 20px;
-        border-radius: 10px;
-        border: 2px dashed #3366cc;
-        font-size: 18px;
-        line-height: 1.6;
-    }
-</style>
-""", unsafe_allow_html=True)
-
-# Title and description
-st.title("🧸 Kid's Storyteller 🧸")
-st.markdown("### Upload an image and I'll tell you a magical story about it!")
-
-# Function to load image captioning model
-@st.cache_resource
-def load_caption_model():
-    try:
-        with st.spinner("Loading image captioning model... (This may take a minute)"):
-            processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-            model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
-            return processor, model, None
-    except Exception as e:
-        return None, None, str(e)
-
-# Function to load story generation model
-@st.cache_resource
-def load_story_model():
-    try:
-        with st.spinner("Loading story generation model... (This may take a minute)"):
-            story_generator = pipeline("text-generation", model="gpt2")
-            return story_generator, None
-    except Exception as e:
-        return None, str(e)
-
-# Function to generate caption from image
-def generate_caption(image, processor, model):
-    inputs = processor(image, return_tensors="pt")
-    out = model.generate(**inputs, max_length=50)
-    caption = processor.decode(out[0], skip_special_tokens=True)
-    return caption
-
-# Function to generate story from caption
-def generate_story(caption, story_generator):
-    # Make the prompt child-friendly and whimsical
-    prompt = f"Once upon a time in a magical land, {caption}. The children were amazed when "
-    
-    result = story_generator(prompt, max_length=150, num_return_sequences=1, temperature=0.8)
-    story = result[0]['generated_text']
-    
-    # Make sure the story is between 50-100 words
-    story_words = story.split()
-    if len(story_words) > 100:
-        story = ' '.join(story_words[:100])
-        # Add a closing sentence
-        story += ". And they all lived happily ever after."
-    elif len(story_words) < 50:
-        # If too short, generate more
-        additional = story_generator(story, max_length=150, num_return_sequences=1)
-        story = additional[0]['generated_text']
-        story_words = story.split()
-        if len(story_words) > 100:
-            story = ' '.join(story_words[:100])
-        story += ". And they all lived happily ever after."
-    
-    return story
-
-# Function to convert text to speech and create audio player
-def text_to_speech(text):
-    try:
-        tts = gTTS(text=text, lang='en', slow=False)
-        audio_file = "story_audio.mp3"
-        tts.save(audio_file)
-        
-        # Create audio player
-        with open(audio_file, "rb") as file:
-            audio_bytes = file.read()
-        
-        audio_b64 = base64.b64encode(audio_bytes).decode()
-        audio_player = f"""
-            <audio controls autoplay>
-                <source src="data:audio/mp3;base64,{audio_b64}" type="audio/mp3">
-                Your browser does not support the audio element.
-            </audio>
-        """
-        return audio_player, None
-    except Exception as e:
-        return None, str(e)
-
-# Main application flow
-try:
-    # Load models with status checks
-    with st.spinner("Loading AI models... This may take a moment the first time you run the app."):
-        caption_processor, caption_model, caption_error = load_caption_model()
-        story_model, story_error = load_story_model()
-        
-        if caption_error:
-            st.error(f"Error loading caption model: {caption_error}")
-        if story_error:
-            st.error(f"Error loading story model: {story_error}")
-    
-    # If models loaded successfully
-    if caption_processor and caption_model and story_model:
-        # Show example images for kids to understand
-        st.markdown("### 🌟 Examples of images you can upload:")
-        col1, col2, col3 = st.columns(3)
-        with col1:
-            st.markdown("🐱 Pets")
-        with col2:
-            st.markdown("🏰 Places")
-        with col3:
-            st.markdown("🧩 Toys")
-        
-        # File uploader
-        uploaded_file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
-        
-        if uploaded_file is not None:
-            # Display the uploaded image
-            image_bytes = uploaded_file.getvalue()
-            image = Image.open(io.BytesIO(image_bytes))
-            st.image(image, caption='Uploaded Image', use_column_width=True, output_format="JPEG")
-            
-            with st.spinner('Creating your story... 📝'):
-                # Generate caption
-                caption = generate_caption(image, caption_processor, caption_model)
-                
-                # Generate story
-                story = generate_story(caption, story_model)
-                
-                # Display the story with some styling
-                st.markdown("## 📖 Your Magical Story")
-                st.markdown(f"<div class='story-container'>{story}</div>", 
-                            unsafe_allow_html=True)
-                
-                # Convert to speech and play
-                st.markdown("## 🔊 Listen to the Story")
-                audio_player, audio_error = text_to_speech(story)
-                
-                if audio_player:
-                    st.markdown(audio_player, unsafe_allow_html=True)
-                else:
-                    st.error(f"Could not generate audio: {audio_error}")
-                
-                # Download options
-                st.download_button(
-                    label="Download Story (Text)",
-                    data=story,
-                    file_name="my_story.txt",
-                    mime="text/plain"
-                )
-    else:
-        st.warning("Some AI models didn't load correctly. Please refresh the page or try again later.")
-
-except Exception as e:
-    st.error(f"An error occurred: {e}")
-    st.markdown("Please try again with a different image.")
-
-# Footer
-st.markdown("---")
-st.markdown("Created for young storytellers aged 3-10 years old 🌈")
-st.markdown("Powered by Hugging Face Transformers 🤗")