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import gradio as gr | |
from EmotionClassifier.EmotionPredictor import EmotionPredictor | |
from NER_Wrapper.NER_Wrapper import FullNERPipeline | |
import pandas as pd | |
emotion_predictor,ner_pipe = EmotionPredictor(),FullNERPipeline() | |
def predict(description): | |
ner_text = ner_pipe.process_text(description) | |
emotions = emotion_predictor(ner_text) | |
return pd.DataFrame(emotions) | |
iface = gr.Interface( | |
fn=predict, | |
inputs=gr.Textarea(), | |
outputs="dataframe", | |
live=False, | |
title="Emotion Prediction" | |
) | |
iface.launch(inline=False) |