Update app.py

app.py

@@ -395,9 +395,9 @@ function refresh() {
 
 # Define custom colors for the labels
 color_map = {
-    "Positive": "#00FF00",  # Green for positive
-    "Neutral": "#0000FF",   # Blue for neutral
-    "Negative": "#FF0000"   # Red for negative
+    "POSITIVE": "#00FF00",  # Green for positive
+    "NEUTRAL": "#0000FF",   # Blue for neutral
+    "NEGATIVE": "#FF0000"   # Red for negative
 }
 
     
@@ -464,8 +464,8 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
                     # Summarize the selected paragraph from PDF 1
                     summarize_btn1.click(fn=lambda p: process_paragraph_1_sum(p), inputs=paragraph_1_dropdown, outputs=summary_textbox_1)
             
-                    sentiment_btn1 = gr.Button("Classify Financial Tone from PDF 1")
-                    sentiment_textbox_1 = gr.Label(label="Classification for paragrapg from PDF 1")
+                    sentiment_btn1 = gr.Button("Classify Financial Tone for paragraph from PDF 1")
+                    sentiment_textbox_1 = gr.Label(label="Classification from PDF 1")
             
                     # Classify the financial tone of the selected paragraph from PDF 1
                     sentiment_btn1.click(fn=lambda p: process_paragraph_1_sent(p), inputs=paragraph_1_dropdown, outputs=sentiment_textbox_1)
@@ -499,8 +499,8 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
                     # Summarize the selected paragraph from PDF 2
                     summarize_btn2.click(fn=lambda p: process_paragraph_2_sum(p), inputs=paragraph_2_dropdown, outputs=summary_textbox_2)
             
-                    sentiment_btn2 = gr.Button("Classify Financial Tone from PDF 2")
-                    sentiment_textbox_2 = gr.Label(label="Classification for paragraph from PDF 2")
+                    sentiment_btn2 = gr.Button("Classify Financial Tone for paragraph from PDF 2")
+                    sentiment_textbox_2 = gr.Label(label="Classification from PDF 2")
             
                     # Classify the financial tone of the selected paragraph from PDF 2
                     sentiment_btn2.click(fn=lambda p: process_paragraph_2_sent(p), inputs=paragraph_2_dropdown, outputs=sentiment_textbox_2)