Update app.py

app.py

@@ -25,8 +25,11 @@ class SentimentAnalyzer:
         sentiment_scores_str = f"Positive: {sentiment_scores['positive']:.2f}, Neutral: {sentiment_scores['neutral']:.2f}, Negative: {sentiment_scores['negative']:.2f}"
         return sentiment_scores_str
     def emotion_analysis(self,text):
-        prompt = f""" Your task is to analyze {text} and predict the emotion using scores. Emotions are categorized into the following list: Sadness, Happiness, Joy, Fear, Disgust, and Anger. You need to provide the emotion with the highest score. The scores should be in the range of 0.0 to 1.0, where 1.0 represents the highest intensity of the emotion.
-Please analyze the text and provide the output in the following format: emotion: score [with one result having the highest score]."""
+        prompt = f""" Your task is find the top 3 emotion : <Sadness, Happiness, Joy, Fear, Disgust, Anger> and it's emotion score of the text.\
+        your are analyze the text and provide the output in the following format: emotion: score [with top 3 result having the highest score]
+        The scores should be in the range of 0.0 to 1.0, where 1.0 represents the highest intensity of the emotion.\
+        analyze the text : '''{text}'''
+        """
         response = openai.Completion.create(
             model="text-davinci-003",
             prompt=prompt,
@@ -206,7 +209,7 @@ class LangChain_Document_QA:
       history_state.clear()
 
     def gradio_interface(self):
-      with gr.Blocks(css="style.css",theme=gr.themes.Soft()) as demo:
+      with gr.Blocks(css="style.css",theme=gr.themes.dark-glass()) as demo:
           with gr.Row():
             gr.HTML("""<center><img class="image" src="https://www.syrahealth.com/images/SyraHealth_Logo_Dark.svg" alt="Image" width="210" height="210"></center>
             """)