Update app.py

app.py

@@ -0,0 +1,58 @@
+import streamlit as st
+from transformers import pipeline
+from gtts import gTTS
+import os
+
+def generate_caption(image):
+    # Load the image captioning model
+    caption_model = pipeline("image-to-text", model="facebook/blip-image-captioning-base")
+    
+    # Generate the caption for the uploaded image
+    caption = caption_model(image)[0]["generated_text"]
+    
+    return caption
+
+def generate_story(caption):
+    # Load the text generation model
+    text_generation_model = pipeline("text-generation", model="gpt2")
+    
+    # Generate the story based on the caption
+    story = text_generation_model(caption, max_length=200, num_return_sequences=1)[0]["generated_text"]
+    
+    return story
+
+def convert_to_audio(story):
+    # Convert the story to audio using gTTS
+    tts = gTTS(text=story, lang="en")
+    tts.save("story_audio.mp3")
+
+def main():
+    st.title("Storytelling Application")
+    
+    # File uploader for the image
+    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+    
+    if uploaded_image is not None:
+        # Display the uploaded image
+        st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
+        
+        # Generate the caption for the image
+        caption = generate_caption(uploaded_image)
+        st.subheader("Generated Caption:")
+        st.write(caption)
+        
+        # Generate the story based on the caption
+        story = generate_story(caption)
+        st.subheader("Generated Story:")
+        st.write(story)
+        
+        # Convert the story to audio
+        convert_to_audio(story)
+        
+        # Display the audio player
+        audio_file = open("story_audio.mp3", "rb")
+        audio_bytes = audio_file.read()
+        st.audio(audio_bytes, format="audio/mp3")
+
+if __name__ == "__main__":
+    main()