VocabLine / app.py
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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)
## 🧑‍💻 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
)
with gr.Group(elem_id="card-group"):
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")
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")
with gr.Tab("英文小考"):
quiz_source_dropdown = gr.Dropdown(
choices=get_sources(),
value="common3000",
label="選擇單字庫"
)
quiz_num_slider = gr.Slider(minimum=1, maximum=10, value=2, step=1, label="題目數量")
quiz_generate_button = gr.Button("📄 生成試卷")
quiz_submit_button = gr.Button("✅ 提交試卷")
quiz_questions_container = gr.Column()
quiz_score_display = gr.HTML()
quiz_questions_state = gr.State([])
def display_exam(source, num):
questions = generate_fill_in_blank_exam(source, num)
quiz_questions_state.value = questions
radios = []
for i, q in enumerate(questions):
radios.append(
gr.Radio(
choices=q['options'],
label=f"第 {i + 1} 題:{q['sentence']}",
interactive=True
)
)
return radios
def submit_exam(*user_answers):
questions = quiz_questions_state.value
score_html = check_exam(user_answers, questions)
return score_html
quiz_generate_button.click(
display_exam,
inputs=[quiz_source_dropdown, quiz_num_slider],
outputs=quiz_questions_container
)
quiz_submit_button.click(
submit_exam,
inputs=quiz_questions_container,
outputs=quiz_score_display
)
demo.launch()