app.py

import gradio as gr
from transformers import pipeline
import os

def load_generator():
    return pipeline("text-generation", model="Qwen/Qwen3-4B-Instruct-2507", token=os.environ.get("HUGGINGFACEHUB_API_TOKEN"))

generator = load_generator()

def generate_text(prompt):
    if not prompt:
        return "Please enter a prompt."
    output = generator(prompt, max_new_tokens=500, prefix="用简体中文回应。")[0]['generated_text']
    return output

# Example prompts for better user guidance
examples = [
    ["寫一篇有關製作中式點心的說明文。"],
    ["寫一篇有關學校的描寫文。"],
    ["寫一篇有關與家人旅行的記敘文。"],
    ["寫一篇題為《地鐵眾生相》的描寫文。"]
]

with gr.Blocks(title="Chinese Text Generation Demo", theme=gr.themes.Soft()) as demo:
    gr.Markdown("# Chinese Text Generation Demo")
    gr.Markdown("Generate Chinese text using Qwen language model")
    
    with gr.Row():
        with gr.Column(scale=1):
            prompt_input = gr.Textbox(
                label="Enter your prompt",
                lines=4,
                placeholder="Enter your Chinese text prompt here...",
                max_lines=8
            )
            generate_btn = gr.Button("Generate", variant="primary", size="lg")
            
        with gr.Column(scale=2):
            output_text = gr.Textbox(
                label="Generated Text",
                lines=12,
                interactive=False,
                show_copy_button=True
            )
    
    # Event handler
    generate_btn.click(
        fn=generate_text,
        inputs=prompt_input,
        outputs=output_text,
        show_progress=True
    )
    
    # Examples section using gr.Examples
    gr.Examples(
        examples=examples,
        inputs=prompt_input,
        outputs=output_text,
        fn=generate_text,
        cache_examples=True,
        examples_per_page=4
    )

if __name__ == "__main__":
    demo.queue().launch()