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import re
import json
import requests
import os
import gradio as gr
HF_TOKEN = os.getenv("HF_TOKEN")
task_options = ["重點整理", "問答", "翻譯"]
MODEL_URLS = {
"重點整理": {
"翻譯": "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-zh",
"摘要": "https://api-inference.huggingface.co/models/csebuetnlp/mT5_multilingual_XLSum"
},
"問答": "https://api-inference.huggingface.co/models/luhua/chinese_pretrain_mrc_roberta_wwm_ext_large",
"翻譯": "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-en-zh"
}
def clean_rtf(text):
text = re.sub(r"\'.", "", text)
text = re.sub(r"\[a-z]+[0-9]* ?", "", text)
text = re.sub(r"[{}]", "", text)
return text.strip()
def run_model(task, text, question=None):
headers = {
"Authorization": f"Bearer {HF_TOKEN}",
"Content-Type": "application/json"
}
if task == "重點整理":
translation_payload = {"inputs": text}
translation_url = MODEL_URLS["重點整理"]["翻譯"]
translation_response = requests.post(translation_url, headers=headers, json=translation_payload)
if translation_response.status_code != 200:
return "❌ 翻譯失敗：" + translation_response.text
try:
translated_text = translation_response.json()[0]['translation_text']
except Exception as e:
return f"❌ 翻譯結果解析錯誤：{str(e)}"
summarization_payload = {"inputs": f"summarize: {translated_text}"}
summarization_url = MODEL_URLS["重點整理"]["摘要"]
summarization_response = requests.post(summarization_url, headers=headers, json=summarization_payload)
if summarization_response.status_code != 200:
return "❌ 摘要失敗：" + summarization_response.text
try:
summary_text = summarization_response.json()[0]['summary_text']
except Exception as e:
return f"❌ 摘要結果解析錯誤：{str(e)}"
return summary_text
elif task == "問答":
if not question:
return "❌ 請輸入問題"
qa_payload = {
"inputs": {
"question": question,
"context": text
}
}
qa_url = MODEL_URLS["問答"]
qa_response = requests.post(qa_url, headers=headers, json=qa_payload)
if qa_response.status_code != 200:
return "❌ 問答失敗：" + qa_response.text
try:
answer = qa_response.json().get("answer", "⚠️ 找不到答案")
trans_payload = {"inputs": answer}
trans_url = MODEL_URLS["翻譯"]
trans_response = requests.post(trans_url, headers=headers, json=trans_payload)
if trans_response.status_code == 200:
return trans_response.json()[0]['translation_text']
else:
return answer
except Exception as e:
return f"❌ 回答解析錯誤：{str(e)}"
elif task == "翻譯":
translation_payload = {"inputs": text}
translation_url = MODEL_URLS["翻譯"]
translation_response = requests.post(translation_url, headers=headers, json=translation_payload)
if translation_response.status_code != 200:
return "❌ 翻譯失敗：" + translation_response.text
try:
return translation_response.json()[0]['translation_text']
except Exception as e:
return f"❌ 翻譯結果解析錯誤：{str(e)}"
else:
return "❌ 不支援的任務"
with gr.Blocks() as demo:
gr.Markdown("# 🌐 多功能語言處理器（繁體中文）\n支援：重點整理（英文→中）、問答、翻譯（英翻中）")
with gr.Row():
task = gr.Dropdown(choices=task_options, label="請選擇任務")
with gr.Row():
text_input = gr.Textbox(lines=10, label="輸入文章 / 內容")
with gr.Row():
question_input = gr.Textbox(label="問題（問答任務用）", placeholder="選擇問答任務時必填")
with gr.Row():
output = gr.Textbox(lines=5, label="輸出結果")
with gr.Row():
run_button = gr.Button("執行")
run_button.click(fn=run_model, inputs=[task, text_input, question_input], outputs=output)
if __name__ == "__main__":
demo.launch()
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