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app.py

@@ -381,13 +381,14 @@ const LQ_PRESETS = __PRESETS__;
 
 CSS = """
 :root { --lq-orange:#ff7a00; --lq-amber:#ffb000; --lq-lime:#c6e600; }
-.gradio-container { max-width: 1280px !important; margin: 0 auto !important; }
+.gradio-container { max-width: 1280px !important; margin: 0 auto !important; --layout-gap: 20px !important; }
 #lq-schema-store, #lq-preset-store { display: none !important; }
+#lq-fields { padding: 0 !important; border: none !important; }
 
 #lq-hero { padding: 6px 2px 2px; margin-bottom: 2px; }
 #lq-hero h1 { margin:0; font-size: 1.75rem; font-weight: 800; letter-spacing:-.02em;
   color:#e0590a; -webkit-text-fill-color:#e0590a; }
-#lq-hero p { margin:.3rem 0 0; color:#8a6a2a; font-size:.95rem; max-width: 72ch; }
+#lq-hero p { margin:.3rem 0 0; color:#8a6a2a; font-size:.95rem; white-space:nowrap; }
 
 /* schema builder */
 #lq-schema-builder { display:block; }
@@ -483,10 +484,10 @@ with gr.Blocks(title="Liquid Image → JSON") as demo:
             model_key = gr.Radio(
                 choices=[("450M · ⚡ fastest", "450M"), ("1.6B · 🎯 most accurate", "1.6B")],
                 value="1.6B",
-                label="Model",
+                show_label=False,
             )
             gr.Markdown("**Extraction schema** — name a field and describe what to pull out")
-            gr.HTML('<div id="lq-schema-builder"></div>')
+            gr.HTML('<div id="lq-schema-builder"></div>', elem_id="lq-fields")
             schema_store = gr.Textbox(elem_id="lq-schema-store", value="[]")
             preset_store = gr.Textbox(elem_id="lq-preset-store", value="")
             go = gr.Button("💧 Extract JSON", variant="primary", elem_id="lq-go")