update app

app.py

@@ -3,9 +3,10 @@ from transformers import AutoTokenizer, T5ForConditionalGeneration
 tokenizer = AutoTokenizer.from_pretrained("CodeTed/CGEDit")
 model = T5ForConditionalGeneration.from_pretrained("CodeTed/CGEDit")
 
-
 def cged_correction(sentence, function):
-    input_ids = tokenizer('糾正句子裡的錯字：' + sentence, return_tensors="pt").input_ids
+    prompt = {"錯別字校正":"糾正句子中的錯字：", "文法校正":"糾正句子中的錯誤：", 
+    "文本重構":"在不改動文意的情況下改寫句子：", "文本簡化":"在不改動文意的情況下改寫句子：", "整體校正":"修改句子的錯誤或使其更通順："}
+    input_ids = tokenizer(prompt[function] + sentence, return_tensors="pt").input_ids
     outputs = model.generate(input_ids, max_length=200)
     edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return edited_text
@@ -13,12 +14,12 @@ def cged_correction(sentence, function):
 with gr.Blocks() as demo:
     gr.Markdown(
         """
-    # 中文錯別字校正 - Chinese Spelling Correction
-    ### Find Spelling Error and get the correction！
+    # Chinese Grammarly - 中文文本自動編輯器
+    ### 貼上中文文章來使你的句子更順暢～
     Start typing below to see the correction.
     """
     )
-    funt = gr.Radio(["add", "subtract", "multiply", "divide"])
+    funt = gr.Radio(["錯別字校正", "文法校正", "文本重構", "文本簡化", "整體校正"])
     #設定輸入元件
     sent = gr.Textbox(label="Sentence", placeholder="input the sentence")
     # 設定輸出元件