Update app.py

app.py

@@ -153,7 +153,6 @@ class ContentAnalyzer:
             print("[DEBUG]", error_msg)
             return {"error": error_msg}
 
-
 def create_interface():
     analyzer = ContentAnalyzer()
 
@@ -162,29 +161,11 @@ def create_interface():
         gr.Markdown("Analyze text content from various sources using AI.")
 
         with gr.Tabs():
-            # Text Input Tab
-            with gr.Tab("Text Input"):
-                text_input = gr.Textbox(
-                    label="Enter Text",
-                    placeholder="Paste your text here...",
-                    lines=5
-                )
-
-            # URL Input Tab
-            with gr.Tab("Web URL"):
-                url_input = gr.Textbox(
-                    label="Enter URL",
-                    placeholder="https://example.com"
-                )
+            # Tabs for Text Input, Web URL, File Upload...
+            text_input = gr.Textbox(label="Enter Text", placeholder="Paste your text here...", lines=5)
+            url_input = gr.Textbox(label="Enter URL", placeholder="https://example.com")
+            file_input = gr.File(label="Upload File", file_types=[".txt", ".pdf", ".docx"])
 
-            # File Upload Tab
-            with gr.Tab("File Upload"):
-                file_input = gr.File(
-                    label="Upload File",
-                    file_types=[".txt", ".pdf", ".docx"]
-                )
-
-        # Analysis Options
         analysis_types = gr.CheckboxGroup(
             choices=["summarize", "sentiment", "topics"],
             value=["summarize"],
@@ -193,7 +174,6 @@ def create_interface():
 
         analyze_btn = gr.Button("Analyze", variant="primary")
 
-        # Output Sections
         with gr.Tabs():
             with gr.Tab("Original Text"):
                 original_text = gr.Markdown()
@@ -205,15 +185,17 @@ def create_interface():
                 topics_output = gr.Markdown()
 
         def process_analysis(text, url, file, types, progress=gr.Progress()):
-            """
-            This function is wrapped by gradio to handle user inputs.
-            We use progress to show step-by-step updates.
-            """
-            steps_total = 4  # We have up to 4 possible steps
-
-            def progress_callback(step, desc):
-                progress((step, desc), total=steps_total)
-            
+            steps_total = 4
+
+            def progress_callback(step: int, desc: str):
+                """
+                step: integer step index (1 to steps_total)
+                desc: a short description of the current step
+                """
+                # Pass the integer 'step' as iteration, and the string 'desc' as desc.
+                progress(step, total=steps_total, desc=desc)
+
+            # Call your analyzer
             results = analyzer.analyze_content(
                 text=text, 
                 url=url, 
@@ -222,26 +204,21 @@ def create_interface():
                 progress_callback=progress_callback
             )
 
-            # If there's an error, show it in "Original Text" tab for clarity
             if "error" in results:
                 return results["error"], "", "", ""
 
             # Format outputs
             original = results.get("original_text", "")
             summary = results.get("summary", "")
-            
             sentiment = ""
             if "sentiment" in results:
-                sent = results["sentiment"]
-                sentiment = f"**Sentiment:** {sent['label']} (Confidence: {sent['score']})"
+                s = results["sentiment"]
+                sentiment = f"**Sentiment:** {s['label']} (Confidence: {s['score']})"
 
             topics = ""
             if "topics" in results:
-                topics_list = "\n".join([
-                    f"- {t['label']}: {t['score']}"
-                    for t in results["topics"]
-                ])
-                topics = "**Detected Topics:**\n" + topics_list
+                t_list = "\n".join([f"- {t['label']}: {t['score']}" for t in results["topics"]])
+                topics = "**Detected Topics:**\n" + t_list
 
             return original, summary, sentiment, topics
 
@@ -249,11 +226,11 @@ def create_interface():
             fn=process_analysis,
             inputs=[text_input, url_input, file_input, analysis_types],
             outputs=[original_text, summary_output, sentiment_output, topics_output],
-            show_progress=True  # Enable the progress bar in Gradio
+            show_progress=True
         )
 
     return demo
 
 if __name__ == "__main__":
     demo = create_interface()
-    demo.launch()
+    demo.launch()