Update app.py

app.py

@@ -8,7 +8,9 @@ def install_packages():
         'streamlit': 'streamlit',
         'transformers': 'transformers',
         'gtts': 'gtts',
-        'tensorflow': 'tensorflow'
+        'tensorflow': 'tensorflow',
+        'tf-keras': 'tf-keras',  # Required for compatibility
+        'torch': 'torch'  # Sometimes helps with transformer compatibility
     }
     
     for package in required_packages.values():
@@ -24,15 +26,29 @@ install_packages()
 from transformers import BlipProcessor, TFBlipForConditionalGeneration
 from gtts import gTTS
 import tensorflow as tf
+import warnings
+
+# Suppress unnecessary warnings
+warnings.filterwarnings('ignore')
 
 # Load the image captioning model
 @st.cache_resource
 def load_model():
+    # Verify TensorFlow is using the correct Keras
+    import keras
+    st.write(f"Keras version: {keras.__version__}")
+    st.write(f"TensorFlow version: {tf.__version__}")
+    
     processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
     model = TFBlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
     return processor, model
 
-processor, model = load_model()
+try:
+    processor, model = load_model()
+except Exception as e:
+    st.error(f"Failed to load model: {str(e)}")
+    st.error("Please ensure you have installed tf-keras with: pip install tf-keras")
+    st.stop()
 
 def generate_caption(image):
     inputs = processor(image, return_tensors="tf")
@@ -50,8 +66,15 @@ def text_to_speech(text):
 
 # Streamlit UI
 def main():
-    st.title("Storytelling Application")
+    st.title("📖 AI Storytelling Application")
     st.write("Upload an image and let AI generate a story for you!")
+    
+    with st.expander("ℹ️ Requirements"):
+        st.write("""
+        - Python 3.7+
+        - TensorFlow 2.x
+        - tf-keras (not Keras 3)
+        """)
 
     uploaded_file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
     
@@ -59,26 +82,27 @@ def main():
         image = Image.open(uploaded_file)
         st.image(image, caption="Your Uploaded Image", use_column_width=True)
 
-        if st.button("Generate Story"):
-            with st.spinner("Creating your story..."):
+        if st.button("✨ Generate Story"):
+            with st.spinner("Creating your magical story..."):
                 try:
                     # Generate caption
                     caption = generate_caption(image)
-                    st.subheader("Image Caption:")
-                    st.write(caption)
+                    with st.expander("🔍 Image Caption"):
+                        st.write(caption)
 
                     # Generate story
                     story = generate_story(caption)
-                    st.subheader("Generated Story:")
+                    st.subheader("📖 Generated Story")
                     st.write(story)
 
                     # Convert to speech
                     audio_file = text_to_speech(story)
-                    st.subheader("Audio Version:")
+                    st.subheader("🔊 Audio Version")
                     st.audio(audio_file, format='audio/mp3')
                     
                 except Exception as e:
                     st.error(f"An error occurred: {str(e)}")
+                    st.error("If this is a Keras-related error, try: pip install tf-keras")
 
 if __name__ == "__main__":
     main()