app.py

import gradio as gr
import random
from vocab import get_sources, get_words_from_source
from sentences import generate_sentences
from ai_sentence import MODEL_LIST
from quiz import generate_fill_in_blank_exam, check_exam, render_exam_interface

def process_sentence(mode, word, source, num, use_ai, model_name):
    try:
        if mode == '查詢單字':
            if not word:
                return "<p style='color:red;'>❌ 請輸入單字</p>", "未輸入單字"
            words = [word.strip()]
        elif mode == '隨機抽單字':
            num = int(num)
            if num <= 0:
                return "<p style='color:red;'>❌ 抽取數量須大於0</p>", "數量錯誤"
            words_data = get_words_from_source(source)
            words = [w['word'] for w in words_data]
            words = random.sample(words, num)
        else:
            return "<p style='color:red;'>❌ 模式錯誤</p>", "模式選擇異常"

        result_display, status_log = generate_sentences(words, source, use_ai, model_name)

        return result_display, status_log

    except Exception as e:
        return f"<p style='color:red;'>❌ 發生錯誤：{str(e)}</p>", f"錯誤：{str(e)}"

def project_description():
    return """
    # 📖 VocabLine 單字例句工具
    支援單字例句查詢，AI 自動生成句子。適合作為 LINE 單字推播、英文學習輔助工具。
    ## 🔍 核心功能
    - 查詢單字 → 獲取例句
    - 抽取單字 → 批量獲取例句
    - 可選 AI 生成句子（模型：GPT2 / Pythia）
    - 英文小考 → 單字填空選擇題，自動批改計分
    ## 🧑‍💻 技術架構
    - Gradio Blocks + Transformers (Hugging Face)
    - SQLite 句庫管理
    - 支援多單字庫擴展
    ## 📚 資料來源
    - 常用 3000 單字表
    - 英文例句資料庫 (Tatoeba)
    ## 👨‍💻 開發資訊
    - 開發者：余彦志 (大宇 ian)
    - 信箱：[email protected]
    - GitHub：[https://github.com/dayuian](https://github.com/dayuian)
    """

with gr.Blocks(css="""
    #card-group { padding: 15px; border-radius: 12px; background-color: rgba(255, 255, 255, 0.05); box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); margin-bottom: 15px; }
    .gradio-container { max-width: 800px; margin: auto; }
""") as demo:
    gr.Markdown(project_description())

    with gr.Tab("單字查詢/生成例句"):
        with gr.Group():
            with gr.Row():
                mode_radio = gr.Radio(
                    ["查詢單字", "隨機抽單字"],
                    label="選擇模式",
                    value="查詢單字",
                    interactive=True
                )

            word_input = gr.Textbox(label="輸入單字", visible=True)
            num_input = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="抽取單字數量", visible=False)
            source_dropdown = gr.Dropdown(
                choices=get_sources(),
                value="common3000",
                label="選擇單字庫"
            )

        with gr.Group(elem_id="card-group"):
            use_ai_checkbox = gr.Checkbox(label="使用 AI 生成句子（較慢，約 30 秒）", elem_id="use-ai-checkbox")

            with gr.Row():
                model_dropdown = gr.Dropdown(
                    choices=MODEL_LIST,
                    value="gpt2",
                    label="選擇 AI 模型",
                    visible=False
                )
                gr.Markdown("🔷 **建議使用 GPT2（表現較佳），Pythia-410m 很爛慎選！**", visible=False)

        ai_warning = gr.Textbox(
            value="⚠️ 使用 AI 生成句子為功能測試，每一個單字的生成過程可能需要 30 秒以上，請耐心等待。",
            visible=False,
            interactive=False,
            label=""
        )

        result_output = gr.HTML(label="結果")
        status_output = gr.Textbox(label="處理狀態", interactive=False)

        with gr.Row():
            generate_button = gr.Button("✨ 生成句子", elem_id="generate-button")

        def switch_mode(mode):
            return gr.update(visible=(mode == '查詢單字')), gr.update(visible=(mode == '隨機抽單字'))

        mode_radio.change(
            switch_mode,
            inputs=[mode_radio],
            outputs=[word_input, num_input]
        )

        generate_button.click(
            process_sentence,
            inputs=[mode_radio, word_input, source_dropdown, num_input, use_ai_checkbox, model_dropdown],
            outputs=[result_output, status_output]
        )

    with gr.Tab("英文小考"):
        model_note = gr.Markdown(visible=True)

        quiz_source_dropdown = gr.Dropdown(
            choices=get_sources(),
            value="common3000",
            label="選擇單字庫"
        )
        quiz_num_slider = gr.Slider(minimum=1, maximum=5, value=2, step=1, label="題目數量")
        quiz_model_dropdown = gr.Dropdown(
            choices=MODEL_LIST,
            value="gpt2",
            label="選擇 AI 模型"
        )

        quiz_generate_button = gr.Button("📄 生成試卷")
        quiz_submit_button = gr.Button("✅ 提交試卷")

        quiz_score_display = gr.HTML()
        quiz_questions_state = gr.State([])

        radios = [gr.Radio(choices=[], label=f"第 {i + 1} 題", visible=False, interactive=True) for i in range(5)]

        def update_model_note(model):
            return f"本功能目前使用 **{model}** 作為語言模型生成題目。"

        quiz_model_dropdown.change(update_model_note, inputs=[quiz_model_dropdown], outputs=[model_note])

        def display_exam(source, num, model):
            questions = generate_fill_in_blank_exam(source, num)
            quiz_questions_state.value = questions

            updates = []
            for i, q in enumerate(questions):
                updates.append(gr.update(choices=q["options"], label=f"第 {i + 1} 題：{q['sentence']}", visible=True))
            for i in range(len(questions), 5):
                updates.append(gr.update(visible=False))

            return updates

        def submit_exam(*user_answers):
            questions = quiz_questions_state.value
            score_html = check_exam(user_answers[:len(questions)], questions)
            return score_html

        quiz_generate_button.click(display_exam, inputs=[quiz_source_dropdown, quiz_num_slider, quiz_model_dropdown], outputs=radios)
        quiz_submit_button.click(submit_exam, inputs=radios, outputs=quiz_score_display)

    demo.launch()