Two-column layout (inputs left, outputs right) for each task tab

app.py

@@ -185,23 +185,26 @@ with gr.Blocks(title="GLiNER2.5 Multi — Information Extraction") as demo:
     with gr.Tabs():
         with gr.Tab("🏷️ Entity Extraction"):
             gr.Markdown("Extract named entities with custom labels.")
-            ner_text = gr.Textbox(
-                label="Input Text",
-                placeholder="Enter text to analyze…",
-                lines=5,
-                value="Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday. The event was held at Apple Park.",
-            )
-            ner_labels = gr.Textbox(
-                label="Entity Labels (comma-separated)",
-                value="company, person, product, location",
-                placeholder="person, organization, location…",
-            )
-            ner_btn = gr.Button("Extract Entities", variant="primary")
-            ner_output = gr.HighlightedText(
-                label="Extracted Entities",
-                combine_adjacent=True,
-                show_legend=True,
-            )
+            with gr.Row():
+                with gr.Column():
+                    ner_text = gr.Textbox(
+                        label="Input Text",
+                        placeholder="Enter text to analyze…",
+                        lines=5,
+                        value="Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday. The event was held at Apple Park.",
+                    )
+                    ner_labels = gr.Textbox(
+                        label="Entity Labels (comma-separated)",
+                        value="company, person, product, location",
+                        placeholder="person, organization, location…",
+                    )
+                    ner_btn = gr.Button("Extract Entities", variant="primary")
+                with gr.Column():
+                    ner_output = gr.HighlightedText(
+                        label="Extracted Entities",
+                        combine_adjacent=True,
+                        show_legend=True,
+                    )
 
             gr.Examples(
                 examples=[
@@ -218,19 +221,22 @@ with gr.Blocks(title="GLiNER2.5 Multi — Information Extraction") as demo:
 
         with gr.Tab("📋 Text Classification"):
             gr.Markdown("Classify text into custom categories (zero-shot).")
-            cls_text = gr.Textbox(
-                label="Input Text",
-                placeholder="Enter text to classify…",
-                lines=3,
-                value="This laptop has amazing performance but terrible battery life!",
-            )
-            cls_schema = gr.Textbox(
-                label="Classification Schema (one task per line: task: label1, label2, …)",
-                value="sentiment: positive, negative, neutral",
-                lines=3,
-            )
-            cls_btn = gr.Button("Classify Text", variant="primary")
-            cls_output = gr.Code(label="Result (JSON)", language="json", lines=8)
+            with gr.Row():
+                with gr.Column():
+                    cls_text = gr.Textbox(
+                        label="Input Text",
+                        placeholder="Enter text to classify…",
+                        lines=3,
+                        value="This laptop has amazing performance but terrible battery life!",
+                    )
+                    cls_schema = gr.Textbox(
+                        label="Classification Schema (one task per line: task: label1, label2, …)",
+                        value="sentiment: positive, negative, neutral",
+                        lines=3,
+                    )
+                    cls_btn = gr.Button("Classify Text", variant="primary")
+                with gr.Column():
+                    cls_output = gr.Code(label="Result (JSON)", language="json", lines=8)
 
             gr.Examples(
                 examples=[
@@ -247,22 +253,25 @@ with gr.Blocks(title="GLiNER2.5 Multi — Information Extraction") as demo:
 
         with gr.Tab("🔗 Relation Extraction"):
             gr.Markdown("Detect relationships between entities in text.")
-            rel_text = gr.Textbox(
-                label="Input Text",
-                placeholder="Enter text to analyze…",
-                lines=4,
-                value="Alice works for Acme Corp in Paris. Bob joined Acme last year and lives in London.",
-            )
-            rel_labels = gr.Textbox(
-                label="Relation Labels (comma-separated)",
-                value="works_for, located_in",
-                placeholder="works_for, located_in, founded_by…",
-            )
-            with gr.Accordion("Options", open=False):
-                rel_conf = gr.Checkbox(label="Include confidence scores", value=True)
-                rel_spans = gr.Checkbox(label="Include character spans", value=True)
-            rel_btn = gr.Button("Extract Relations", variant="primary")
-            rel_output = gr.Code(label="Result (JSON)", language="json", lines=15)
+            with gr.Row():
+                with gr.Column():
+                    rel_text = gr.Textbox(
+                        label="Input Text",
+                        placeholder="Enter text to analyze…",
+                        lines=4,
+                        value="Alice works for Acme Corp in Paris. Bob joined Acme last year and lives in London.",
+                    )
+                    rel_labels = gr.Textbox(
+                        label="Relation Labels (comma-separated)",
+                        value="works_for, located_in",
+                        placeholder="works_for, located_in, founded_by…",
+                    )
+                    with gr.Accordion("Options", open=False):
+                        rel_conf = gr.Checkbox(label="Include confidence scores", value=True)
+                        rel_spans = gr.Checkbox(label="Include character spans", value=True)
+                    rel_btn = gr.Button("Extract Relations", variant="primary")
+                with gr.Column():
+                    rel_output = gr.Code(label="Result (JSON)", language="json", lines=15)
 
             gr.Examples(
                 examples=[
@@ -279,19 +288,22 @@ with gr.Blocks(title="GLiNER2.5 Multi — Information Extraction") as demo:
 
         with gr.Tab("📦 Structured Data Extraction"):
             gr.Markdown("Parse text into structured JSON records with typed fields.")
-            json_text = gr.Textbox(
-                label="Input Text",
-                placeholder="Enter text to extract structured data from…",
-                lines=4,
-                value="iPhone 15 Pro Max with 256GB storage, A17 Pro chip, priced at $1199. Available in titanium and black colors.",
-            )
-            json_schema = gr.Textbox(
-                label="Schema (one field per line: field::type::description)",
-                value="name::str::Full product name and model\nstorage::str::Storage capacity\nprocessor::str::Chip or processor\nprice::str::Product price with currency\ncolors::list::Available color options",
-                lines=5,
-            )
-            json_btn = gr.Button("Extract Structured Data", variant="primary")
-            json_output = gr.Code(label="Result (JSON)", language="json", lines=12)
+            with gr.Row():
+                with gr.Column():
+                    json_text = gr.Textbox(
+                        label="Input Text",
+                        placeholder="Enter text to extract structured data from…",
+                        lines=4,
+                        value="iPhone 15 Pro Max with 256GB storage, A17 Pro chip, priced at $1199. Available in titanium and black colors.",
+                    )
+                    json_schema = gr.Textbox(
+                        label="Schema (one field per line: field::type::description)",
+                        value="name::str::Full product name and model\nstorage::str::Storage capacity\nprocessor::str::Chip or processor\nprice::str::Product price with currency\ncolors::list::Available color options",
+                        lines=5,
+                    )
+                    json_btn = gr.Button("Extract Structured Data", variant="primary")
+                with gr.Column():
+                    json_output = gr.Code(label="Result (JSON)", language="json", lines=12)
 
             gr.Examples(
                 examples=[