Update app.py

app.py

@@ -21,23 +21,21 @@ def load_models():
     captioner = pipeline(
         "image-to-text",
         model="Salesforce/blip-image-captioning-base",
-        device=-1
+        device=-1  # Force CPU usage
     )
     
-    # Story generation model with optimized settings
+    # Story generation model with updated parameters
     storyteller = pipeline(
         "text-generation",
         model="Qwen/Qwen3-1.7B",
         device_map="auto",
         trust_remote_code=True,
         torch_dtype="auto",
-        model_kwargs={
-            "revision": "main",
-            "temperature": 0.7,
-            "top_p": 0.9,
-            "repetition_penalty": 1.1,
-            "pad_token_id": 151645
-        }
+        temperature=0.7,
+        top_p=0.9,
+        repetition_penalty=1.1,
+        pad_token_id=151645,
+        max_new_tokens=300
     )
     
     return captioner, storyteller
@@ -82,12 +80,16 @@ uploaded_image = st.file_uploader(
 )
 
 if uploaded_image:
-    # Display uploaded image
+    # Display uploaded image with modern parameter
     image = Image.open(uploaded_image).convert("RGB")
-    st.image(image, use_column_width=True)
+    st.image(image, use_container_width=True)  # Updated parameter
     
     # Load models only when needed
-    caption_pipe, story_pipe = load_models()
+    try:
+        caption_pipe, story_pipe = load_models()
+    except Exception as e:
+        st.error(f"❌ Model loading failed: {str(e)}")
+        st.stop()
     
     # Generate image caption
     with st.spinner("🔍 Analyzing image..."):
@@ -96,11 +98,11 @@ if uploaded_image:
             image_caption = caption_result[0].get("generated_text", "").strip()
             
             if not image_caption:
-                raise ValueError("Couldn't generate caption")
+                raise ValueError("Empty caption generated")
                 
             st.success(f"**Image Understanding:** {image_caption}")
         except Exception as e:
-            st.error("❌ Failed to analyze image. Please try another.")
+            st.error("❌ Image analysis failed. Please try another image.")
             st.stop()
     
     # Create story prompt
@@ -123,8 +125,6 @@ if uploaded_image:
         try:
             story_result = story_pipe(
                 story_prompt,
-                max_new_tokens=300,
-                do_sample=True,
                 num_return_sequences=1
             )
             raw_story = story_result[0]['generated_text']
@@ -151,4 +151,3 @@ if uploaded_image:
 # Footer
 st.markdown("---")
 st.caption("Made with ♥ by The Story Wizard • [Report Issues](https://example.com)")
-