app.py

import gradio as gr
import json
import random
from transformers import AutoModelForCausalLM, AutoTokenizer
import os
import re

# 模型初始化
model_name = "EleutherAI/pythia-410m"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# 資料夾
DATA_DIR = "./data"

# 自動掃描資料夾生成選單
def get_sources():
    files = os.listdir(DATA_DIR)
    sources = [f.split(".json")[0] for f in files if f.endswith(".json")]
    return sources

# 清理 GPT 生成句子的雜訊
def clean_sentence(output):
    output = re.sub(r"Write.*?beginners\.", "", output, flags=re.IGNORECASE).strip()
    output = re.sub(r"\*\*?\d+\.*\*\*", "", output).strip()
    if not output.endswith("."):
        output += "."
    return output

# 核心函數
def get_words_with_sentences(source, n):
    status = []
    try:
        data_path = os.path.join(DATA_DIR, f"{source}.json")
        with open(data_path, 'r', encoding='utf-8') as f:
            words = json.load(f)

        selected_words = random.sample(words, n)
        results = []

        for i, word_data in enumerate(selected_words):
            status.append(f"正在生成第 {i+1}/{n} 個單字 [{word_data['word']}] 例句...")
            word = word_data['word']

            prompt = f"Use the word '{word}' in a simple English sentence suitable for beginners. Output only the sentence."

            inputs = tokenizer(prompt, return_tensors="pt")
            outputs = model.generate(**inputs, max_new_tokens=30)
            sentence = tokenizer.decode(outputs[0], skip_special_tokens=True)

            clean_output = clean_sentence(sentence)

            results.append({
                "word": word,
                "phonetic": word_data["phonetic"],
                "sentence": clean_output
            })

        status.append("✅ 完成！")
        return results, status

    except Exception as e:
        status.append(f"❌ 發生錯誤: {str(e)}")
        return [], status

# Gradio 介面
demo = gr.Interface(
    fn=get_words_with_sentences,
    inputs=[
        gr.Dropdown(choices=get_sources(), value="common3000", label="選擇單字庫", interactive=True, show_clear_button=False),
        gr.Number(value=10, label="抽幾個單字")
    ],
    outputs=[
        gr.JSON(label="生成結果"),
        gr.JSON(label="生成進度")
    ]
)

demo.launch()