app.py

import gradio as gr
from transformers import pipeline

# 使用预训练的情感分析模型充当“作文打分器”
scorer = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")

def grade_essay(essay):
    if not essay.strip():
        return "⚠️ Please enter an essay text."
    
    # 模型输出情感预测结果
    result = scorer(essay[:512])[0]  # 限制长度以防过长
    score = result['score']
    label = result['label']

    # 模拟作文评分逻辑
    if label == "POSITIVE":
        final_score = round(60 + 40 * score, 2)  # 高分作文
    else:
        final_score = round(40 * (1 - score), 2)  # 低分作文

    feedback = f"📊 Sentiment: {label}\n🧾 Estimated Essay Score: {final_score}/100"
    return feedback

# 构建 Gradio 前端
demo = gr.Interface(
    fn=grade_essay,
    inputs=gr.Textbox(lines=10, placeholder="Paste your essay here..."),
    outputs="text",
    title="AI Essay Grader",
    description="A simple demo using Hugging Face Transformers to auto-grade essays (simulated).",
)

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