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import streamlit as st |
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from emotions import get_emotion, get_sentiment_arc_evaluation |
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from stats import get_repetitions |
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from nltk.tokenize import sent_tokenize, word_tokenize |
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import nltk |
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nltk.download('punkt') |
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st.title("Strange Story Critique service") |
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text = st.text_area("Submit your story and I'll tell you my unprofessional opinion", '''Words and symbols are meant to be here''') |
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if text != 'Words and symbols are meant to be here': |
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emotion_result = get_emotion(text) |
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st.write(f"🔮 Overall emotion of your story: {emotion_result[0]['label']}") |
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joy, sad = 0, 0 |
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for emo in emotion_result: |
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if emo['label'] == 'joy': |
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if emo['score'] > joy: |
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joy = emo['score'] |
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elif emo['label'] == 'love': |
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if emo['score'] > joy: |
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joy = emo['score'] |
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elif emo['label'] == 'sadness': |
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sad = emo['score'] |
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st.write(f"😸 Joy level: {joy*100:.2f}%") |
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st.write(f"😿 Sadness level: {sad*100:.2f}%") |
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sents = sent_tokenize(text) |
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emo_arc = [] |
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for sent in sents: |
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emotion_result = get_emotion(sent) |
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emo_arc.append(emotion_result[0]['label']) |
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sentiment_arc_eval = get_sentiment_arc_evaluation(emo_arc) |
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st.write(f"📈 Emotional arc of your story: {' - '.join(emo_arc)}") |
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st.write('📈 ' + sentiment_arc_eval) |
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words = word_tokenize(text) |
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if len(words) < 5: |
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st.write("Isn't your story a bit too short?") |
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if len(words) > 0: |
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rep_ratio = get_repetitions(words) |
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if rep_ratio < 0.7: |
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st.write("Seems too repetitive!") |
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st.write(f"Repetition ratio: {rep_ratio:.2f}") |
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else: |
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st.write("A story with no words? Interesting choice.") |
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