Update app.py

app.py

@@ -2,31 +2,14 @@ import gradio as gr
 from transformers import pipeline
 from transformers import pipeline
 import re
+from utils import grammatical_cleaning
 
 dante = pipeline('text-generation',model='.', tokenizer='GroNLP/gpt2-small-italian-embeddings')
 
-def grammatical_cleaning(generated: str) -> str:
-	generated = re.sub("\.[^\s]",". ", generated)
-	generated = re.sub("\,[^\s]",", ", generated)
-	generated = re.sub("\;[^\s]","; ", generated)
-	generated = re.sub("\:[^\s]",": ", generated)
-	generated = re.sub("\![^\s]","! ", generated)
-	generated = list(generated)
-	for n in range(len(generated)-2):
-		if generated[n]=="." or generated[n]=="?":
-			if generated[n+1].islower() and generated[n+1].isalpha():
-				generated[n+1] = generated[n+1].upper()
-			elif generated[n+2].islower() and generated[n+2].isalpha():
-				generated[n+2] = generated[n+2].upper()
-	return ''.join(generated)
-
 def get_text(input):
 	generated = dante(input, max_length=128)[0]['generated_text']
 	generated = grammatical_cleaning(generated)
 	return generated
 
-inp = input()
-print(get_text(inp))
-
-#iface = gr.Interface(fn=get_text, inputs="text", outputs="text")
-#iface.launch()
+iface = gr.Interface(fn=get_text, inputs="text", outputs="text")
+iface.launch()