Update app.py

app.py

@@ -28,7 +28,7 @@ def analyze_sentiment(text):
     if not text or not text.strip():
         return {"Error: Please enter text for analysis": 0.0}
     
-    # Escape HTML tags (Protection against injections)
+    # Escape HTML tags to protect against injections
     safe_text = html_lib.escape(text)
     
     try:
@@ -37,6 +37,7 @@ def analyze_sentiment(text):
         # Return label and score as a dictionary
         return {result["label"]: result["score"]}
     except Exception as e:
+        # Return processing error inside the result dictionary
         return {f"Processing Error: {str(e)[:100]}": 0.0}
 
 def summarize_text(text):
@@ -71,6 +72,7 @@ def summarize_text(text):
         summary = sum_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
         return warning + summary
     except Exception as e:
+        # Return processing error as string
         return f"Processing Error: {str(e)[:100]}"
 
 def translate_en_to_uk(text):
@@ -91,6 +93,7 @@ def translate_en_to_uk(text):
         # Decode translated tokens back to text
         return trans_tokenizer.decode(translated_ids[0], skip_special_tokens=True)
     except Exception as e:
+        # Return processing error as string
         return f"Processing Error: {str(e)[:100]}"
 
 # Create Gradio blocks interface with a soft theme
@@ -101,79 +104,68 @@ with gr.Blocks(title="NLP Toolkit", theme=gr.themes.Soft()) as demo:
     # Add application description
     gr.Markdown('A comprehensive AI-powered tool that allows you to analyze text sentiment, generate short summaries for long articles, and translate text from English to Ukrainian.')
     
-    # Create tabs
+    # Create main tabs container
     with gr.Tabs():
         # Create Sentiment Analysis tab
         with gr.Tab("Sentiment Analysis"):
-            # Create column layout
-            with gr.Column():
-                input_text = gr.Textbox(label="Input Text", lines=3, placeholder="Type something in English... (e.g., I absolutely love this product!)")
-                output_label = gr.Label(label="Analysis Result")
-                btn_sentiment = gr.Button("Analyze Sentiment", variant='primary')
-                btn_sentiment.click(fn=analyze_sentiment, inputs=input_text, outputs=output_label)
-                
-                gr.Examples(
-                    examples=[
-                        ["I absolutely love this new update! It's fantastic."], 
-                        ["I'm very disappointed with the service, it was terrible."],
-                        ["The weather today is completely ordinary."]
-                    ],
-                    inputs=input_text
-                )
+            input_text = gr.Textbox(label="Input Text", lines=3, placeholder="Type something in English... (e.g., I absolutely love this product!)")
+            output_label = gr.Label(label="Analysis Result")
+            btn_sentiment = gr.Button("Analyze Sentiment", variant='primary')
+            
+            # Link button click to sentiment analysis function
+            btn_sentiment.click(fn=analyze_sentiment, inputs=input_text, outputs=output_label)
+            
+            # Configure examples for sentiment analysis tab
+            gr.Examples(
+                examples=[
+                    ["I absolutely love this new update! It's fantastic."], 
+                    ["I'm very disappointed with the service, it was terrible."],
+                    ["The weather today is completely ordinary."]
+                ],
+                inputs=input_text,
+                cache_examples=False
+            )
                 
         # Create Summarization tab
         with gr.Tab("Summarization"):
-            # Create column layout
-            with gr.Column():
-                input_long = gr.Textbox(label="Long Text (EN)", lines=6, placeholder="Paste a long English article to summarize here...")
-                output_summary = gr.Textbox(label="Short Summary", lines=3)
-                btn_summarize = gr.Button("Generate Summary", variant="primary")
-                btn_summarize.click(fn=summarize_text, inputs=input_long, outputs=output_summary)
-                
-                examples = gr.Dataset(
-                components=[input_long],
-                samples=[
-                    ["Artificial intelligence is transforming healthcare and transportation."],
-                    ["The James Webb Space Telescope is the largest space telescope ever built."],
-                    ["Climate change is a long-term shift in global temperatures."]
+            input_long = gr.Textbox(label="Long Text (EN)", lines=6, placeholder="Paste a long English article to summarize here...")
+            output_summary = gr.Textbox(label="Short Summary", lines=3)
+            btn_summarize = gr.Button("Generate Summary", variant="primary")
+            
+            # Link button click to summarization function
+            btn_summarize.click(fn=summarize_text, inputs=input_long, outputs=output_summary)
+            
+            # Configure examples for summarization tab with formatting bug fixes
+            gr.Examples(
+                examples=[
+                    ["Artificial intelligence (AI) has become a transformative force in modern society, influencing everything from healthcare to transportation. In the medical field, AI algorithms can analyze complex data to assist doctors in diagnosing diseases more accurately and quickly. For instance, machine learning models are trained on thousands of medical images to detect early signs of conditions like cancer. Meanwhile, in transportation, autonomous vehicles use AI to navigate roads, avoid obstacles, and reduce the likelihood of accidents caused by human error."],
+                    ["The James Webb Space Telescope (JWST) is the largest and most powerful space science telescope ever built. Launched on December 25, 2021, it represents a major leap forward in our quest to understand the universe. Unlike its predecessor, the Hubble Space Telescope, which primarily observes visible light, the JWST is designed to detect infrared radiation. This capability allows it to peer through dense clouds of cosmic dust and observe the very first galaxies that formed after the Big Bang."],
+                    ["Climate change is a long-term shift in global or regional climate patterns. Often climate change refers specifically to the rise in global temperatures from the mid-20th century to present. It is primarily caused by human activities, especially the burning of fossil fuels, which increases levels of heat-trapping greenhouse gases in Earth's atmosphere. The impacts are already being felt globally, including more frequent and severe weather events, rising sea levels, and shifts in wildlife populations."]
                 ],
-                label="Examples"
-                )
-                
-                examples.click(
-                    lambda x: x,
-                    inputs=[examples],
-                    outputs=[input_long]
-                )
+                inputs=input_long,
+                cache_examples=False
+            )
 
         # Create Translation tab
         with gr.Tab("Translation (EN -> UK)"):
-            # Create column layout
-            with gr.Column():
-                input_trans = gr.Textbox(label="English Text", lines=4, placeholder="Enter text in English to translate into Ukrainian...")
-                output_trans = gr.Textbox(label="Ukrainian Translation", lines=4)
-                btn_translate = gr.Button("Translate to Ukrainian", variant="primary")
-                btn_translate.click(fn=translate_en_to_uk, inputs=input_trans, outputs=output_trans)
-                
-                example1 = gr.Button("AI Example")
-                example2 = gr.Button("Space Example")
-                example3 = gr.Button("Climate Example")
-                
-                example1.click(
-                    fn=lambda: "Artificial intelligence is rapidly changing the world.",
-                    outputs=input_long
-                )
-                
-                example2.click(
-                    fn=lambda: "I would like to order a cup of coffee, please.",
-                    outputs=input_long
-                )
-                
-                example3.click(
-                    fn=lambda: "The results of the recent testing phase exceeded all our initial expectations.",
-                    outputs=input_long
-                )
+            input_trans = gr.Textbox(label="English Text", lines=4, placeholder="Enter text in English to translate into Ukrainian...")
+            output_trans = gr.Textbox(label="Ukrainian Translation", lines=4)
+            btn_translate = gr.Button("Translate to Ukrainian", variant="primary")
+            
+            # Link button click to translation function
+            btn_translate.click(fn=translate_en_to_uk, inputs=input_trans, outputs=output_trans)
+            
+            # Configure examples for translation tab targeting the correct input component
+            gr.Examples(
+                examples=[
+                    ["Artificial intelligence is rapidly changing the world."],
+                    ["I would like to order a cup of coffee, please."],
+                    ["The results of the recent testing phase exceeded all our initial expectations."]
+                ],
+                inputs=input_trans,
+                cache_examples=False
+            )
 
 if __name__ == "__main__":
-    # Launch application with public share link
+    # Launch application with active debug mode
     demo.launch(debug=True)