import gradio as gr
from transformers import pipeline
import re
text_pipe = pipeline("text-classification", model="karalif/myTestModel", return_all_scores=True)
def predict(text):
greeting_pattern = r"^(Halló|Hæ|Sæl|Góða|Kær|Daginn|Kvöldið|Ágæt|Elsku)"
greeting_feedback = ""
results = text_pipe(text)
all_scores = results[0]
response = ""
for result in all_scores:
label = result['label']
score = result['score']
if label in ["Politeness"]:
response += f"{label}: {score:.3f}
" # Light Green
if label in ["Sentiment"]:
response += f"{label}: {score:.3f}
" # Light Yellow
if label in ["Formality"]:
response += f"{label}: {score:.3f}
" # Light Blue
if label in ["Toxicity"]:
response += f"{label}: {score:.3f}
" # Light Red
else:
response += f"{label}: {score:.3f}
"
if not re.match(greeting_pattern, text, re.IGNORECASE):
greeting_feedback = "Heilsaðu dóninn þinn
"
response += greeting_feedback
return response
description_html = """