Update app.py

app.py

@@ -1,15 +1,28 @@
+import re
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, T5Tokenizer, MT5ForConditionalGeneration
 
 tokenizer = T5Tokenizer.from_pretrained("engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1")
 model = AutoModelForSeq2SeqLM.from_pretrained("engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1")
 
-def output(raw_input_sentence):
-    target_sentence = ["en2ja: " + str(raw_input_sentence)]
-    translated = model.generate(**tokenizer(target_sentence, return_tensors="pt"), max_length = 1000)
-    tgt_text = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
-    translated_phrase = tgt_text[0]
-    translated_phrase = translated_phrase.replace(" ", "")
+def output(input_text):
+    input_text = re.sub('(!|！)', '.', input_text)
+    target_sentence_list = []
+    for part in input_text.split("."):
+        sentence = part.strip()
+        if sentence != '':
+            target_sentence_list.append(sentence)
+
+    translation_subject_list = []
+    for i in target_sentence_list:
+        target_sentence = ["en2ja: " + str(i)]
+        translated = model.generate(**tokenizer(target_sentence, return_tensors="pt"), max_length=1000)
+        tgt_text = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
+        translated_phrase = tgt_text[0] + "。" ## "\n"も入れると改行も
+        translated_phrase = translated_phrase.replace(" ", "")
+        translation_subject_list.append(translated_phrase)
+    translated_phrase = "\n".join(translation_subject_list)
+
     return translated_phrase
     
 interface = gr.Interface(fn=output, inputs=gr.inputs.Textbox(lines=3, placeholder="Write what you want to say in Japanese.")