Update src/streamlit_app.py

src/streamlit_app.py

@@ -69,11 +69,17 @@ def query_similar_images(image_file, top_k=5):
         tmp.flush()
         res = image_collection.query(query_uris=[tmp.name], n_results=top_k)
     os.remove(tmp.name)
+    # Safe check for results
+    if not res or 'uris' not in res or not res['uris'] or not res['uris'][0]:
+        return []
     return res['uris'][0]
 
 # --- Text-to-Image search ---
 def search_images_by_text(text, top_k=5):
     res = image_collection.query(query_texts=[text], n_results=top_k)
+    # Safe check for results
+    if not res or 'uris' not in res or not res['uris'] or not res['uris'][0]:
+        return []
     return res['uris'][0]
 
 # --- Load CIFAR-10 Demo Dataset (500 images) ---
@@ -141,9 +147,12 @@ if q:
     st.image(q, caption="Query Image", width=200)
     with st.spinner("Finding similar images..."):
         results = query_similar_images(q, top_k=5)
-    st.subheader("🔁 Top Matches:")
-    for u in results:
-        st.image(u, width=150)
+    if not results:
+        st.warning("No similar images found.")
+    else:
+        st.subheader("🔁 Top Matches:")
+        for u in results:
+            st.image(u, width=150)
 
 st.divider()
 st.subheader("📝 Text-to-Image Search")
@@ -151,6 +160,9 @@ txt = st.text_input("Describe what you’re looking for (e.g., 'a beach', 'a cat
 if txt:
     with st.spinner("Finding images by semantic similarity..."):
         results = search_images_by_text(txt, top_k=5)
-    st.subheader("🔍 Semantic Matches:")
-    for u in results:
-        st.image(u, width=150)
+    if not results:
+        st.warning("No semantic matches found.")
+    else:
+        st.subheader("🔍 Semantic Matches:")
+        for u in results:
+            st.image(u, width=150)