Update app.py

app.py

@@ -25,10 +25,7 @@ politeness_bench = Benchmark(politeness_model, politeness_tokenizer)
 
 # Initialize pipelines for translation and classifiers
 translator = pipeline("translation", model="Helsinki-NLP/opus-mt-is-en")
-sentiment_classifier = pipeline("text-classification", model="Birkir/electra-base-igc-is-sentiment-analysis")
-formality_classifier = pipeline("text-classification", model="svanhvit/formality-classification-icebert")
 detoxify_pipeline = pipeline('text-classification', model='unitary/toxic-bert', tokenizer='bert-base-uncased', function_to_apply='sigmoid', top_k=None)
-politeness_classifier = pipeline("text-classification", model="Genius1237/xlm-roberta-large-tydip")
 
 def replace_encoding(tokens):
     return [token.replace('Ġ', ' ')
@@ -64,26 +61,18 @@ def analyze_with_influence(text, bench):
 
 def analyze_text(icelandic_text):
     translated_text = translator(icelandic_text, max_length=512)[0]['translation_text']
-    sentiment_label, sentiment_score = analyze_sentiment(icelandic_text)
-    formality_label, formality_score = analyze_formality(icelandic_text)
-    toxicity_label, toxicity_score = analyze_toxicity(translated_text)
-    politeness_label, politeness_score = analyze_politeness(translated_text)
 
-    sentiment_influential_words = analyze_with_influence(icelandic_text, sentiment_bench)
-    formality_influential_words = analyze_with_influence(icelandic_text, formality_bench)
-    toxicity_influential_words = analyze_with_influence(translated_text, toxicity_bench)
-    politeness_influential_words = analyze_with_influence(translated_text, politeness_bench)
+    sentiment_analysis = analyze_with_influence(icelandic_text, sentiment_bench)
+    formality_analysis = analyze_with_influence(icelandic_text, formality_bench)
+    toxicity_analysis = analyze_with_influence(translated_text, toxicity_bench)
+    politeness_analysis = analyze_with_influence(translated_text, politeness_bench)
 
     analysis_results = f"""
     Translated Text: {translated_text}\n\n
-    Sentiment: {sentiment_label}, Score: {round(sentiment_score, 2)}\n
-    Influential Words in Sentiment: {sentiment_influential_words}\n
-    Formality: {formality_label}, Score: {round(formality_score, 2)}\n
-    Influential Words in Formality: {formality_influential_words}\n
-    Toxicity: {toxicity_label}, Score: {round(toxicity_score, 2)}\n
-    Influential Words in Toxicity: {toxicity_influential_words}\n
-    Politeness: {politeness_label}, Score: {round(politeness_score, 2)}\n
-    Influential Words in Politeness: {politeness_influential_words}
+    Sentiment Analysis with Influential Words: {sentiment_analysis}\n
+    Formality Analysis with Influential Words: {formality_analysis}\n
+    Toxicity Analysis with Influential Words: {toxicity_analysis}\n
+    Politeness Analysis with Influential Words: {politeness_analysis}
     """
     return analysis_results.strip()
 
@@ -91,7 +80,7 @@ demo = gr.Interface(fn=analyze_text,
                     inputs=gr.Textbox(lines=2, placeholder="Enter Icelandic Text Here..."), 
                     outputs=gr.Textbox(label="Analysis Results"),
                     title="Icelandic Text Analysis",
-                    description="This app translates Icelandic text to English and performs sentiment, formality, toxicity, and politeness analysis along with influential words analysis.")
+                    description="This app translates Icelandic text to English and performs analysis with influential words for sentiment, formality, toxicity, and politeness.")
 
 if __name__ == "__main__":
     demo.launch()