initial code update

app.py

@@ -6,12 +6,12 @@ import os
 import pandas as pd
 import re
 
-#models
+# models
 from transformers import AutoTokenizer, AutoModelForTokenClassification,AutoModelForSequenceClassification, pipeline
 import torch
 
 aspdevice = "cpu"
-    # Your aspect extraction logic
+# Your aspect extraction logic
 model_id_ate = "gauneg/roberta-base-absa-ate-sentiment"
 tokenizer_ate = AutoTokenizer.from_pretrained(model_id_ate)
 model_ate = AutoModelForTokenClassification.from_pretrained(model_id_ate)
@@ -67,9 +67,7 @@ def extract_full_analysis(review):
     }
     return dynamic_result
 
-print("Current working directory:", os.getcwd())
-with open('yelp3k.json', 'r', encoding='utf-8') as fp:
-    static_reviews = json.load(fp)
+
 def highlight_aspects(text, aspects):
     aspects_sorted = sorted(aspects, key=len, reverse=True)
     aspects_regex = [re.escape(asp) for asp in aspects_sorted]
@@ -102,38 +100,11 @@ def format_review(review):
         {aspects_html}
         <h3>Sentiments</h3>
         {sentiments_html}
-        <h3>Sentiments Score</h3>
-        {sentiScor_html}
-
         <h3>Emotions</h3>
         {emotions_html}
-        <h3>Emotions Score</h3>
-        {emoScor_html}
-
     </div>
     """
 
-# Format dynamic reviews
-def format_dynamic_reviews(reviews):
-    return "<div>" + "".join(format_review(rev) for rev in reviews) + "</div>"
-
-def get_static_review(index):
-    review = static_reviews[index]
-    highlighted_text = highlight_aspects(review['text'], review['aspect_word'].split(','))
-    stars_html = f"Stars: {review['stars']}"
-    aspects = [asp.strip() for asp in review['aspect_word'].split(',')]
-    emotions = [emo.strip() for emo in review['emotion'].split(',')]
-
-    aspects_html = '<h3>Aspect Words</h3><div class="cell-grid">' + "".join(f'<div class="cell-item">{html.escape(asp)}</div>' for asp in aspects) + '</div>'
-    emotions_html = '<h3>Emotions Extracted</h3><div class="cell-grid">' + "".join(f'<div class="cell-item">{html.escape(emo)}</div>' for emo in emotions) + '</div>'
-    
-    info_text = f"Review {index+1} of {len(static_reviews)}"
-    return highlighted_text, stars_html, aspects_html, emotions_html, info_text
-
-def navigate(direction, current_index):
-    if direction == 'prev':
-        return max(current_index - 1, 0)
-    return min(current_index + 1, len(static_reviews) - 1)
 
 def submit_new_review(text):
     if not text.strip():
@@ -159,19 +130,6 @@ with gr.Blocks(css="""
     # Header
     gr.Markdown("# Yelp Review Demonstration for Aspect and Emotion Extracted")
 
-    # Static Reviews
-    with gr.Row():
-        with gr.Column(scale=11):
-            static_text = gr.HTML(label="Review Text")
-        with gr.Column(scale=1):
-            static_stars = gr.HTML(label="Stars")
-    static_aspects = gr.HTML(label=None)
-    static_emotions = gr.HTML(label="Emotions")
-    static_info = gr.Textbox(label="Review Info", interactive=False)
-    with gr.Row():
-        prev_button = gr.Button("Previous")
-        next_button = gr.Button("Next")
-
     # Submit Form
     gr.Markdown("## Submit Your Review")
     with gr.Row():
@@ -184,21 +142,10 @@ with gr.Blocks(css="""
     dynamic_display = gr.HTML()
 
     # States
-    current_static_index = gr.State(0)
     dynamic_reviews_state = gr.State()
-
-    # Load Initial Data
-    demo.load(get_static_review, inputs=current_static_index, outputs=[static_text, static_stars, static_aspects, static_emotions, static_info])
-
-    # Event Handlers
-    prev_button.click(lambda ci: navigate('prev', ci), inputs=current_static_index, outputs=current_static_index).then(
-        get_static_review, inputs=current_static_index, outputs=[static_text, static_stars, static_aspects, static_emotions, static_info])
-    next_button.click(lambda ci: navigate('next', ci), inputs=current_static_index, outputs=current_static_index).then(
-        get_static_review, inputs=current_static_index, outputs=[static_text, static_stars, static_aspects, static_emotions, static_info])
     submit_button.click(submit_new_review, inputs=submit_text, outputs=[dynamic_display, dynamic_reviews_state])
 
 # Launch
 if __name__ == "__main__":
-    port = int(os.environ.get('PORT', 7814))
-    demo.launch(server_name="0.0.0.0", server_port=port,share=True)
+    demo.launch()
 # 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