Upload app.py with huggingface_hub

app.py

@@ -151,12 +151,36 @@ def predict(question, schema, num_beams, max_length):
     return sql, raw_output, parsed, perf
 
 
-theme = gr.themes.Soft(
+theme = gr.themes.Base(
     primary_hue="indigo",
     secondary_hue="purple",
     neutral_hue="slate",
     font=gr.themes.GoogleFont("Inter"),
     font_mono=gr.themes.GoogleFont("Fira Code"),
+).set(
+    body_background_fill="#0f0d23",
+    body_text_color="#e2e8f0",
+    block_background_fill="#16132d",
+    block_border_color="#312e81",
+    block_border_width="1px",
+    block_label_text_color="#c7d2fe",
+    block_title_text_color="#e0e7ff",
+    block_radius="12px",
+    block_shadow="none",
+    input_background_fill="#1e1b4b",
+    input_border_color="#312e81",
+    input_border_width="1px",
+    input_text_color="#e2e8f0",
+    input_placeholder_color="#64748b",
+    input_radius="8px",
+    slider_color="#6366f1",
+    button_primary_background_fill="linear-gradient(135deg, #6366f1, #8b5cf6)",
+    button_primary_text_color="#ffffff",
+    button_secondary_background_fill="#1e1b4b",
+    button_secondary_text_color="#c7d2fe",
+    button_secondary_border_color="#312e81",
+    border_color_primary="#312e81",
+    color_accent_soft="#1e1b4b",
 )
 
 with gr.Blocks(title="Text-to-SQL | T5 on WikiSQL") as demo: