ask fashiondb

app.py

@@ -31,11 +31,11 @@ from io import BytesIO
 #@st.cache_data(show_spinner="Loading FashionDB...")
 def load_data_hf():
     # Load the Parquet file directly from Hugging Face
-    df_url = "https://huggingface.co/datasets/traopia/vogue_runway_small/resolve/main/VogueRunway.parquet"
+    df_url = "https://huggingface.co/datasets/traopia/vogue-runway/resolve/main/VogueRunway.parquet"
     df = pd.read_parquet(df_url)
 
     # Load the .npy file using requests
-    npy_url = "https://huggingface.co/datasets/traopia/vogue_runway_small/resolve/main/VogueRunway_image.npy"
+    npy_url = "https://huggingface.co/datasets/traopia/vogue-runway/resolve/main/VogueRunway_image.npy"
     response = requests.get(npy_url)
     response.raise_for_status()  # Raise error if download fails
     embeddings = np.load(BytesIO(response.content))
@@ -256,6 +256,14 @@ with gr.Blocks() as demo:
                 outputs=[uploaded_similar_gallery, uploaded_similar_metadata_output, uploaded_reference_image]
             )
 
+        with gr.Tab("Query on FashionDB"):
+            with gr.Row():
+                gr.Markdown(
+                    "### 🔗 Query FashionDB SPARQL Endpoint\n"
+                    "[Click here to open the SPARQL endpoint](https://fashionwiki.wikibase.cloud/query/)",
+                    elem_id="sparql-link"
+                )
+
     back_button = gr.Button("Back to Home")
 
     def back_to_home():