Update app.py

app.py

@@ -7,31 +7,37 @@ import tempfile
 import os
 from PIL import Image
 
-# Initialize pipelines
+# Initialize pipelines with caching to avoid reloading
 @st.cache_resource
 def load_pipelines():
-    captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    # Load pipeline for generating captions from images
+    captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+    # Load pipeline for generating stories from text prompts
     storyer = pipeline("text-generation", model="aspis/gpt2-genre-story-generation")
+    # Load pipeline for converting text to speech
     tts = pipeline("text-to-speech", model="facebook/mms-tts-eng")
     return captioner, storyer, tts
 
+# Load the pipelines once and reuse them
 captioner, storyer, tts = load_pipelines()
 
-# Main logic
+# Function to generate caption, story, and audio from an uploaded image
 def generate_content(image):
-    # Convert Streamlit uploaded image to PIL image
+    # Convert the uploaded image to a PIL image format
     pil_image = Image.open(image)
     
-    # Generate caption
+    # Generate a caption based on the image content
     caption = captioner(pil_image)[0]["generated_text"]
     st.write("**Caption:**", caption)
 
-    # Generate story
+    # Create a prompt for generating a children's story
     prompt = (
         f"Write a funny, warm children's story for ages 3-10, 50–100 words, "
         f"in third-person narrative, that describes this scene exactly: {caption} "
         f"mention the exact place or venue within {caption}"
     )
+    
+    # Generate the story based on the prompt
     raw = storyer(
         prompt,
         max_new_tokens=150,
@@ -41,33 +47,45 @@ def generate_content(image):
         return_full_text=False
     )[0]["generated_text"].strip()
 
-    # Trim to max 100 words
+    # Trim the generated story to a maximum of 100 words
     words = raw.split()
     story = " ".join(words[:100])
     st.write("**Story:**", story)
 
-    # Convert story to speech
+    # Split the story into chunks of 200 characters for text-to-speech processing
     chunks = textwrap.wrap(story, width=200)
+    
+    # Generate and concatenate audio for each text chunk
     audio = np.concatenate([tts(chunk)["audio"].squeeze() for chunk in chunks])
 
-    # Save audio to temporary file
+    # Save the concatenated audio to a temporary WAV 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
+# Streamlit UI for the application
 st.title("Image to Children's Story and Audio")
-st.write("Upload an image to generate a caption, a children's story, and an audio narration.")
+st.markdown("""
+    Upload an image below to generate a caption, a funny children's story, 
+    and an audio narration based on the image. The story will be tailored 
+    for children aged 3-10.
+""")
 
-uploaded_image = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
+# File uploader for image input
+uploaded_image = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"], help="Supported formats: JPG, JPEG, PNG")
 
 if uploaded_image is not None:
+    # Display the uploaded image with a caption
     st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
-    if st.button("Generate Story and Audio"):
-        with st.spinner("Generating content..."):
+    
+    # Button to trigger content generation
+    if st.button("Generate Story and Audio", help="Click to create the story and audio"):
+        # Show a spinner while content is being generated
+        with st.spinner("Generating your story and audio narration..."):
             caption, story, audio_path = generate_content(uploaded_image)
+            # Display the audio player with the generated narration
             st.audio(audio_path, format="audio/wav")
-            # Clean up temporary file
+            # Remove the temporary audio file after use
             os.remove(audio_path)