Update app.py

app.py

@@ -90,22 +90,31 @@ view = st.sidebar.radio("Go to", ["Artwork Explorer", "Visualizations", "Search
 if view == "Artwork Explorer":
     def generate_description(art):
         prompt = (
-            f"Title: {art['title']}\n"
-            f"Artist: {art['artist']}\n"
-            f"Date: {art['date']}\n"
-            f"Culture: {art['culture']}\n"
+            f"Title: {art['title']}
+"
+            f"Artist: {art['artist']}
+"
+            f"Date: {art['date']}
+"
+            f"Culture: {art['culture']}
+"
             f"Description:"
         )
+        )
         try:
             if model_type == "gpt":
                 result = describer(prompt, max_length=100, truncation=True, do_sample=True)[0]["generated_text"]
                 return result.strip()
             else:
-                flan_prompt = f"Write a short description of this artwork:\n\n{prompt}"
-                result = describer(flan_prompt, max_length=100, truncation=True)[0]["generated_text"]
+                prompt = f"Write a short description of this artwork:
+
+{prompt}"
+                result = describer(prompt, max_length=100, truncation=True)[0]["generated_text"]
                 return result.strip()
         except Exception as e:
             return f"[Description unavailable: {e}]"
+        except Exception as e:
+            return f"[Description unavailable: {e}]"
     query_idx = st.slider("Select a Painting Index to Explore", 0, len(image_titles) - 1)
     query_art = artworks[query_idx]
     st.image(query_art["image"], caption=f"🎨 Query: {query_art['title']} ({query_art['artist']})", use_container_width=True)
@@ -119,6 +128,34 @@ if view == "Artwork Explorer":
     with st.expander("🧠 AI-generated Description"):
         st.markdown(f"> {generate_description(query_art)}")
 
+    with st.expander("💬 Ask a question about this artwork"):
+        user_question = st.text_input("Your question")
+        if user_question:
+            qa_prompt = (
+                f"Context:
+"
+                f"Title: {query_art['title']}
+"
+                f"Artist: {query_art['artist']}
+"
+                f"Date: {query_art['date']}
+"
+                f"Culture: {query_art['culture']}
+"
+            )
+            if query_art.get("tags"):
+                tags = ", ".join(tag['term'] for tag in query_art['tags'])
+                qa_prompt += f"Tags: {tags}
+"
+            qa_prompt += f"
+Question: {user_question}
+Answer:"
+            try:
+                answer = describer(qa_prompt, max_length=100, truncation=True, do_sample=True)[0]["generated_text"]
+                st.markdown(f"**Answer:** {answer.strip()}")
+            except Exception as e:
+                st.error(f"[Answer unavailable: {e}]")
+
     sim_scores = cosine_similarity([features[query_idx]], features)[0]
     ranked = np.argsort(sim_scores)[::-1][1:6]