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import gradio as gr | |
from setfit import AbsaModel | |
# Load the ABSA model (assuming indo-setfit-absa-bert-base-restaurants is the aspect extraction model) | |
model = AbsaModel.from_pretrained( | |
"firqaaa/indo-setfit-absa-bert-base-restaurants-aspect", | |
"firqaaa/indo-setfit-absa-bert-base-restaurants-polarity", | |
spacy_model="id_core_news_trf", | |
) | |
def analyze_text(text): | |
""" | |
Analyzes the input text using the ABSA model and returns aspects and sentiment. | |
Args: | |
text: The text to be analyzed. | |
Returns: | |
A dictionary containing aspects and sentiment. | |
""" | |
aspects, sentiments = model.predict(text) | |
return {"Aspek": aspects, "Sentimen": sentiments} | |
description = "Analisa Aspek dan Sentimen Review Restoran" | |
title = "Analisa Review Restoran Anda" | |
examples = [["Makanannya enak, tapi pelayanannya lambat."]] | |
interface = gr.Interface( | |
fn=analyze_text, | |
inputs="textbox", | |
outputs="dict", | |
interpretation="text", | |
description=description, | |
title=title, | |
examples=examples | |
) | |
interface.launch() |