app.py

import gradio as gr
from transformers import pipeline
import time

# 尝试更强的模型（如 flan-t5-large）；如果内存不够，可改回 base
model = pipeline(
    "text2text-generation",
    model="google/flan-t5-large",
    device_map="auto"
)

def analyze_text(text):
    """分析英文原著文本，每句分析时显示进度。"""
    if not text.strip():
        yield "⚠️ 请先输入英文文本。"
        return
    
    sentences = [s.strip() for s in text.split('.') if s.strip()]
    total = len(sentences)
    
    yield f"📖 共检测到 {total} 句，开始分析中...\n"

    all_results = []
    for i, sentence in enumerate(sentences, start=1):
        prompt = f"""
You are an advanced English literature analysis assistant.
Please analyze the following sentence from a literary perspective.
Explain:
1. Grammar and sentence structure
2. Vocabulary richness
3. Idiomatic/natural usage
4. Possible literary meaning or tone
Then give a short summary (in English).

Sentence:
"{sentence}"
"""
        result = model(
            prompt,
            max_length=512,
            do_sample=True,
            temperature=0.7
        )[0]['generated_text']

        all_results.append(f"Sentence {i}:\n{result}\n")

        progress = int(i / total * 100)
        yield f"⏳ 分析进度：{i}/{total} ({progress}%)\n\n" + "\n".join(all_results)
        time.sleep(0.5)

    yield f"✅ 分析完成！共 {total} 句。\n\n" + "\n".join(all_results)


# 界面
demo = gr.Interface(
    fn=analyze_text,
    inputs=gr.Textbox(label="输入英文原著片段", lines=10, placeholder="例如：It was the best of times, it was the worst of times..."),
    outputs=gr.Textbox(label="分析结果", lines=15),
    title="📚 英文原著阅读与分析助手",
    description="逐句分析英文原著的语法、词汇和文体特征，并实时显示进度。",
)

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