modify the layout of input and output

app.py

@@ -16,7 +16,7 @@ model = AutoModelForCausalLM.from_pretrained(
 ).eval()
 
 # define chat function
-def chat(user_input, max_new_tokens=102400):
+def chat(user_input, max_new_tokens=2048):
     # chat history
     messages = [
         {"role": "system", "content": "You are Ling, an assistant created by inclusionAI"},
@@ -44,23 +44,56 @@ def chat(user_input, max_new_tokens=102400):
 
     thread.join()
 
+# Create a custom layout using Blocks
+with gr.Blocks() as demo:
+    gr.Markdown(
+        "## Ling-lite-1.5 AI助手\n"
+        "基于 [inclusionAI/Ling-lite-1.5](https://huggingface.co/inclusionAI/Ling-lite-1.5)  的对话式文本生成演示。"
+    )
+
+    with gr.Row():
+        max_tokens_slider = gr.Slider(minimum=100, maximum=2048, step=50, label="生成长度")
+
+    output_box = gr.Textbox(lines=10, label="模型回复")
+
+    input_box = gr.Textbox(lines=8, label="输入你的问题")
+
+    examples = gr.Examples(
+        examples=[
+            ["介绍大型语言模型的基本概念"],
+            ["如何解决数学问题中的长上下文依赖？"]
+        ],
+        inputs=input_box
+    )
+
+    interface = gr.Interface(
+        fn=chat,
+        inputs=[input_box, max_tokens_slider],
+        outputs=output_box,
+        live=False  # disable auto-triggering on input change
+    )
+
+# launch Gradio Service
+demo.queue()
+demo.launch()
+
 # Construct Gradio Interface
-interface = gr.Interface(
-    fn=chat,
-    inputs=[
-        gr.Textbox(lines=8, label="输入你的问题"),
-        gr.Slider(minimum=100, maximum=102400, step=50, label="生成长度")
-    ],
-    outputs=[
-        gr.Textbox(lines=8, label="模型回复")
-    ],
-    title="Ling-lite-1.5 AI助手",
-    description="基于 [inclusionAI/Ling-lite-1.5](https://huggingface.co/inclusionAI/Ling-lite-1.5)  的对话式文本生成演示。",
-    examples=[
-        ["介绍大型语言模型的基本概念"],
-        ["如何解决数学问题中的长上下文依赖？"]
-    ]
-)
+#interface = gr.Interface(
+#    fn=chat,
+#    inputs=[
+#        gr.Textbox(lines=8, label="输入你的问题"),
+#        gr.Slider(minimum=100, maximum=102400, step=50, label="生成长度")
+#    ],
+#    outputs=[
+#        gr.Textbox(lines=8, label="模型回复")
+#    ],
+#    title="Ling-lite-1.5 AI助手",
+#    description="基于 [inclusionAI/Ling-lite-1.5](https://huggingface.co/inclusionAI/Ling-lite-1.5)  的对话式文本生成演示。",
+#    examples=[
+#        ["介绍大型语言模型的基本概念"],
+#        ["如何解决数学问题中的长上下文依赖？"]
+#    ]
+#)
 
 # launch Gradion Service
-interface.launch()
+#interface.launch()