Delete app.py

app.py

@@ -1,93 +0,0 @@
-# import part
-import streamlit as st
-from transformers import pipeline
-import textwrap
-import numpy as np
-import soundfile as sf
-import tempfile
-import os
-from PIL import Image
-import string
-
-# Initialize pipelines with caching
-@st.cache_resource
-def load_pipelines():
-    captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
-    storyer = pipeline("text-generation", model="aspis/gpt2-genre-story-generation")
-    tts = pipeline("text-to-speech", model="facebook/mms-tts-eng")
-    return captioner, storyer, tts
-
-captioner, storyer, tts = load_pipelines()
-
-# Function part
-# Function to generate content from an image
-def generate_content(image):
-    pil_image = Image.open(image)
-    
-    # Generate caption
-    caption = captioner(pil_image)[0]["generated_text"]
-    st.write("**🌟 What's in the picture: 🌟**")
-    st.write(caption)
-
-    # Create prompt for story
-    prompt = (
-        f"Write a funny, warm children's story that precisely centered on this scene {caption}\nStory:"
-        f"in third-person narrative, that describes this scene exactly: {caption} "
-        f"mention the exact place, location or venue within {caption}"
-    )
-    
-    # Generate raw story
-    raw = storyer(
-        prompt,
-        max_new_tokens=150,
-        temperature=0.7,
-        top_p=0.9,
-        no_repeat_ngram_size=2,
-        return_full_text=False
-    )[0]["generated_text"].strip()
-
-    # Define allowed characters to keep (removes symbols like * and ~)
-    allowed_chars = string.ascii_letters + string.digits + " .,!?\"'-"
-    
-    # Clean the raw story by keeping only allowed characters
-    clean_raw = ''.join(c for c in raw if c in allowed_chars)
-    
-    # Split into words and trim to 100 words
-    words = clean_raw.split()
-    story = " ".join(words[:100])
-    
-    st.write("**📖 Your funny story: 📖**")
-    st.write(story)
-
-    # Generate audio from cleaned story
-    chunks = textwrap.wrap(story, width=200)
-    audio = np.concatenate([tts(chunk)["audio"].squeeze() for chunk in chunks])
-
-    # Save audio to temporary file
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file:
-        sf.write(temp_file.name, audio, tts.model.config.sampling_rate)
-        temp_file_path = temp_file.name
-
-    return caption, story, temp_file_path
-
-# Streamlit UI
-st.title("✨ Magic Story Maker ✨")
-st.markdown("Upload a picture to make a funny story and hear it too! 📸")
-
-uploaded_image = st.file_uploader("Choose your picture", type=["jpg", "jpeg", "png"])
-
-# Streamlit UI (modified image display section)
-if uploaded_image is None:
-    st.image("https://example.com/placeholder_image.jpg", caption="Upload your picture here! 📷", use_container_width=True)
-else:
-    st.image(uploaded_image, caption="Your Picture 🌟", use_container_width=True)
-
-if st.button("✨ Make My Story! ✨"):
-    if uploaded_image is not None:
-        with st.spinner("🔮 Creating your magical story..."):
-            caption, story, audio_path = generate_content(uploaded_image)
-            st.success("🎉 Your story is ready! 🎉")
-            st.audio(audio_path, format="audio/wav")
-            os.remove(audio_path)
-    else:
-        st.warning("Please upload a picture first! 📸")