update app and requirements

app.py

@@ -1,7 +1,30 @@
 import gradio as gr
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+tokenizer = AutoTokenizer.from_pretrained("CodeTed/CGEDit")
+model = T5ForConditionalGeneration.from_pretrained("CodeTed/CGEDit")
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def cged_correction(sentence, function):
+    input_ids = tokenizer('糾正句子裡的錯字：' + 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
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # 中文錯別字校正 - Chinese Spelling Correction
+    ### Find Spelling Error and get the correction！
+    Start typing below to see the correction.
+    """
+    )
+    funt = gr.Radio(["add", "subtract", "multiply", "divide"])
+    #設定輸入元件
+    sent = gr.Textbox(label="Sentence", placeholder="input the sentence")
+    # 設定輸出元件
+    output = gr.Textbox(label="Result", placeholder="correction")
+    #設定按鈕
+    greet_btn = gr.Button("Correction")
+    #設定按鈕點選事件
+    greet_btn.click(fn=cged_correction, inputs=[sent, funt], outputs=output)
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+torch
+sentencepiece
+transformers