Delete app.py

app.py

@@ -1,194 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-from PIL import Image
-import io, textwrap, numpy as np, soundfile as sf
-import logging
-
-# Set up logging for debugging
-logging.basicConfig(level=logging.INFO)
-
-# ------------------ Streamlit Page Configuration ------------------
-st.set_page_config(
-    page_title="Picture to Story Magic",
-    page_icon="🦄",
-    layout="centered"
-)
-
-# ------------------ Custom CSS for a Colorful Background ------------------
-st.markdown(
-    """
-    <style>
-    body {
-        background-color: #FDEBD0;
-    }
-    </style>
-    """,
-    unsafe_allow_html=True
-)
-
-# ------------------ Playful Header for Young Users ------------------
-st.markdown(
-    """
-    <h1 style='text-align: center; color: #ff66cc;'>Picture to Story Magic!</h1>
-    <p style='text-align: center; font-size: 24px;'>
-      Hi little artist! Upload your picture and let us create a fun story just for you! 🎉
-    </p>
-    """,
-    unsafe_allow_html=True
-)
-
-# ------------------ Lazy Model Loading ------------------
-def load_models():
-    """
-    Lazy-load the required pipelines and store them in session state.
-    """
-    if "captioner" not in st.session_state:
-        st.session_state.captioner = pipeline(
-            "image-to-text",
-            model="Salesforce/blip-image-captioning-large"
-        )
-    if "storyer" not in st.session_state:
-        try:
-            st.session_state.storyer = pipeline(
-                "text-generation",
-                model="aspis/gpt2-genre-story-generation"
-            )
-        except Exception as e:
-            logging.error(f"Failed to load aspis/gpt2-genre-story-generation: {e}")
-            raise Exception("Text generation model could not be loaded.")
-    if "tts" not in st.session_state:
-        st.session_state.tts = pipeline(
-            "text-to-speech",
-            model="facebook/mms-tts-eng"
-        )
-
-# ------------------ Caching Functions ------------------
-@st.cache_data(show_spinner=False)
-def get_caption(image_bytes):
-    """
-    Converts image bytes into a lower resolution image (maximum 256x256)
-    and generates a caption.
-    """
-    image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
-    image.thumbnail((256, 256))
-    caption = st.session_state.captioner(image)[0]["generated_text"]
-    return caption
-
-@st.cache_data(show_spinner=False)
-def get_story(caption):
-    """
-    Generates a humorous children's story (50-100 words) based on the caption.
-    Optimized for faster generation with aspis/gpt2-genre-story-generation.
-    """
-    prompt = (
-        f"Write a funny, warm children's story (50-100 words) for ages 3-10 based on: {caption}. "
-        f"Third-person narrative, playful tone."
-    )
-    try:
-        result = st.session_state.storyer(
-            prompt,
-            max_new_tokens=80,     # Reduced for faster generation
-            do_sample=True,
-            temperature=0.7,       # Balanced creativity
-            top_k=40,              # Faster sampling with smaller k
-            top_p=0.85,            # Tighter sampling for coherence
-            return_full_text=False
-        )
-        logging.info(f"Story generation raw result: {result}")
-        
-        # Extract and clean generated text
-        raw_story = result[0].get("generated_text", "").strip()
-        
-        # Ensure story is 50-100 words
-        words = raw_story.split()
-        if len(words) < 50 or not raw_story:
-            logging.warning("Generated story too short or empty. Using fallback.")
-            raw_story = (
-                f"In a land of {caption}, a silly bunny named Bouncy found a shiny star! "
-                f"It sparkled, making Bouncy giggle and hop high. The star said, 'Dance!' "
-                f"So Bouncy twirled with squirrels and birds. They threw a forest party, "
-                f"singing silly songs under the twinkling sky, laughing all night."
-            )
-            words = raw_story.split()
-        
-        # Truncate to 100 words if too long
-        story = " ".join(words[:100])
-        # Pad if too short
-        if len(words) < 50:
-            story += " And they all lived happily ever after!"
-        
-        return story
-    except Exception as e:
-        logging.error(f"Story generation failed: {e}")
-        # Fallback story
-        return (
-            f"In a land of {caption}, a silly bunny named Bouncy found a shiny star! "
-            f"It sparkled, making Bouncy giggle and hop high. The star said, 'Dance!' "
-            f"So Bouncy twirled with squirrels and birds. They threw a forest party, "
-            f"singing silly songs under the twinkling sky, laughing all night."
-        )
-
-@st.cache_data(show_spinner=False)
-def get_audio(story):
-    """
-    Converts the generated story text into audio.
-    Splits the text into 300-character chunks to reduce repeated TTS calls.
-    """
-    chunks = textwrap.wrap(story, width=300)
-    audio_chunks = []
-    for chunk in chunks:
-        try:
-            output = st.session_state.tts(chunk)
-            if isinstance(output, list):
-                output = output[0]
-            if "audio" in output:
-                audio_array = np.array(output["audio"]).squeeze()
-                audio_chunks.append(audio_array)
-        except Exception:
-            continue
-
-    if not audio_chunks:
-        sr = st.session_state.tts.model.config.sampling_rate
-        audio = np.zeros(sr, dtype=np.float32)
-    else:
-        audio = np.concatenate(audio_chunks)
-    
-    buffer = io.BytesIO()
-    sf.write(buffer, audio, st.session_state.tts.model.config.sampling_rate, format="WAV")
-    buffer.seek(0)
-    return buffer
-
-# ------------------ Main App Logic ------------------
-uploaded_file = st.file_uploader("Choose a Picture...", type=["jpg", "jpeg", "png"])
-if uploaded_file is not None:
-    try:
-        load_models()  # Ensure models are loaded
-        image_bytes = uploaded_file.getvalue()
-        image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
-        st.image(image, caption="Your Amazing Picture!", use_column_width=True)
-        st.markdown("<h3 style='text-align: center;'>Ready for your story?</h3>", unsafe_allow_html=True)
-        
-        if st.button("Story, Please!"):
-            with st.spinner("Generating caption..."):
-                caption = get_caption(image_bytes)
-            st.markdown("<h3 style='text-align: center;'>Caption:</h3>", unsafe_allow_html=True)
-            st.write(caption)
-            
-            with st.spinner("Generating story..."):
-                story = get_story(caption)
-            st.markdown("<h3 style='text-align: center;'>Your Story:</h3>", unsafe_allow_html=True)
-            if not story.strip():
-                st.write("No story was generated. Please try again.")
-            else:
-                st.write(story)
-            
-            with st.spinner("Generating audio..."):
-                audio_buffer = get_audio(story)
-            st.audio(audio_buffer, format="audio/wav", start_time=0)
-            st.markdown(
-                "<p style='text-align: center; font-weight: bold;'>Enjoy your magical story! 🎶</p>",
-                unsafe_allow_html=True
-            )
-    except Exception as e:
-        st.error("Oops! Something went wrong. Please try a different picture or check the file format!")
-        st.error(f"Error details: {e}")