Deploy Multimodal Clinical AI app

app.py

@@ -3,18 +3,42 @@ Hugging Face Spaces Deployment App
 Multimodal Clinical AI - Chest X-ray Analysis
 """
 import os
+import sys
 import torch
 import torch.nn.functional as F
 from PIL import Image
 import streamlit as st
-from demo.utils.load_model import load_fusion_model
-from demo.utils.grad_cam import GradCAM, overlay_cam
-from demo.utils.saliency import (
-    compute_text_saliency,
-    merge_wordpieces,
-    filter_tokens,
-    highlight_text,
-)
+
+# Add current directory to path for imports
+sys.path.insert(0, os.path.dirname(__file__))
+
+# Try importing from demo.utils, with fallback handling
+try:
+    from demo.utils.load_model import load_fusion_model
+    from demo.utils.grad_cam import GradCAM, overlay_cam
+    from demo.utils.saliency import (
+        compute_text_saliency,
+        merge_wordpieces,
+        filter_tokens,
+        highlight_text,
+    )
+except ImportError as e:
+    # If demo folder structure doesn't exist, show helpful error
+    import traceback
+    st.error(f"❌ Import error: {e}")
+    st.info("💡 Please ensure the following files are in your Space:")
+    st.code("""
+    demo/
+      __init__.py
+      utils/
+        __init__.py
+        load_model.py
+        grad_cam.py
+        saliency.py
+    """)
+    with st.expander("🔍 Full error details"):
+        st.code(traceback.format_exc())
+    st.stop()
 
 # --------------------------------------------------
 # Page configuration

checkpoints/fusion_model/fusion_layer4_tuned.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89dcb3f9e5fba4eb0746851c2e2326c6368c9aabc231b60b12b2b639bfe97cd7
+size 480755648

demo/__init__.py

@@ -0,0 +1 @@
+# Demo package

demo/utils/__init__.py

@@ -0,0 +1 @@
+# Demo utils package

demo/utils/saliency.py

@@ -56,6 +56,7 @@ def merge_wordpieces(tokens, scores):
         merged_scores.append(current_score)
 
     return merged_tokens, merged_scores
+
 def filter_tokens(tokens, scores, attention_mask):
     clean_tokens = []
     clean_scores = []