update app

app.py

@@ -1,12 +1,12 @@
 # app.py
 """
-Gradio App for Smart Web Analyzer Plus
+Gradio App for Smart Web Analyzer Plus - Human-Readable Outputs
 
 Key Features:
 - Accepts a URL
 - Lets users select analysis modes (Clean Text, Summarization, Sentiment, Topic)
-- Fetches and processes content
-- Displays JSON output with results
+- Fetches and processes content (smart_web_analyzer.py)
+- Displays each result in its own tab for readability
 - Includes example URLs
 """
 
@@ -29,50 +29,67 @@ def analyze_url(url, modes):
         modes (list): list of selected modes
     
     Returns:
-        dict: a dictionary of results or an error message
+        tuple of str: (clean_text_result, summarization_result, sentiment_result, topics_result)
     """
-    results = {}
+    # Default messages if a mode is not selected
+    clean_text_result = "Mode not selected."
+    summarization_result = "Mode not selected."
+    sentiment_result = "Mode not selected."
+    topics_result = "Mode not selected."
     
-    # Attempt to fetch the web content
+    # 1) Fetch/clean the web content
     try:
         html_content = fetch_web_content(url)
     except Exception as e:
-        return {"error": str(e)}  # show error in JSON output
+        # Return the error in each field for clarity
+        error_msg = f"**Error fetching URL**: {e}"
+        return (error_msg, error_msg, error_msg, error_msg)
     
-    # Clean the content
+    # Clean the text (keeping <script> and <style>)
     cleaned = clean_text(html_content)
     
-    # Perform selected analyses
+    # 2) If the user requested a text preview
     if "Clean Text Preview" in modes:
-        results["Clean Text Preview"] = preview_clean_text(cleaned, max_chars=500)
+        clean_text_result = preview_clean_text(cleaned, max_chars=500)
     
+    # 3) Summarization
     if "Summarization" in modes:
-        results["Summarization"] = summarize_text(cleaned)
+        result = summarize_text(cleaned)
+        # If the result starts with "Error", we can highlight it
+        if isinstance(result, str) and "Error" in result:
+            summarization_result = f"**Error during summarization**: {result}"
+        else:
+            summarization_result = result
     
+    # 4) Sentiment Analysis
     if "Sentiment Analysis" in modes:
-        results["Sentiment Analysis"] = analyze_sentiment(cleaned)
+        result = analyze_sentiment(cleaned)
+        if isinstance(result, str) and "Error" in result:
+            sentiment_result = f"**Error during sentiment analysis**: {result}"
+        else:
+            sentiment_result = f"**Predicted Sentiment**: {result}"
     
+    # 5) Topic Detection
     if "Topic Detection" in modes:
         topics = detect_topic(cleaned)
+        # Check if there's an error
         if isinstance(topics, dict) and "error" in topics:
-            results["Topic Detection"] = topics["error"]
+            topics_result = f"**Error during topic detection**: {topics['error']}"
         else:
-            # Format detected topics into a readable string
-            # for the output
-            topics_formatted = "\n".join([f"{t}: {s:.2f}" for t, s in topics.items()])
-            results["Topic Detection"] = topics_formatted
+            # Format the topics into a readable string
+            formatted = ""
+            for t, score in topics.items():
+                formatted += f"- **{t}**: {score:.2f}\n"
+            topics_result = formatted if formatted else "No topics detected."
     
-    return results
+    return (clean_text_result, summarization_result, sentiment_result, topics_result)
 
-# Build Gradio Interface
 def build_app():
     with gr.Blocks(title="Smart Web Analyzer Plus") as demo:
-        gr.Markdown("# Smart Web Analyzer Plus")
-        gr.Markdown(
-            "Analyze web content for summarization, sentiment, and topics. "
-            "Choose your analysis modes and enter a URL below."
-        )
-        
+        gr.Markdown("## Smart Web Analyzer Plus\n"
+                    "Analyze web content for **summarization**, **sentiment**, and **topics**. "
+                    "Choose your analysis modes and enter a URL below.")
+
         with gr.Row():
             url_input = gr.Textbox(
                 label="Enter URL",
@@ -84,17 +101,25 @@ def build_app():
                 choices=["Clean Text Preview", "Summarization", "Sentiment Analysis", "Topic Detection"],
                 value=["Clean Text Preview", "Summarization", "Sentiment Analysis", "Topic Detection"]
             )
+
+        # We'll display results in separate tabs for clarity
+        with gr.Tabs():
+            with gr.Tab("Clean Text Preview"):
+                preview_output = gr.Markdown()
+            with gr.Tab("Summarization"):
+                summary_output = gr.Markdown()
+            with gr.Tab("Sentiment Analysis"):
+                sentiment_output = gr.Markdown()
+            with gr.Tab("Topic Detection"):
+                topic_output = gr.Markdown()
         
-        output_box = gr.JSON(label="Analysis Results")
-        
-        # Button to run analysis
         analyze_button = gr.Button("Analyze")
         
-        # On click, run the analysis function
+        # The "analyze_url" function returns a tuple of four strings
         analyze_button.click(
             fn=analyze_url,
             inputs=[url_input, mode_selector],
-            outputs=output_box
+            outputs=[preview_output, summary_output, sentiment_output, topic_output]
         )
         
         # Example URLs
@@ -107,8 +132,9 @@ def build_app():
             inputs=url_input,
             label="Click an example to analyze"
         )
+    
     return demo
 
 if __name__ == "__main__":
-    demo_app = build_app()
-    demo_app.launch()
+    demo = build_app()
+    demo.launch()